Modifier and Type | Method and Description |
---|---|
static void |
ScriptExecutorUtils.executeRuntimeProgram(org.apache.sysml.runtime.controlprogram.Program rtprog,
org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
org.apache.sysml.conf.DMLConfig dmlconf,
int statisticsMaxHeavyHitters)
Execute the runtime program.
|
static void |
ScriptExecutorUtils.executeRuntimeProgram(ScriptExecutor se,
int statisticsMaxHeavyHitters)
Execute the runtime program.
|
static void |
DMLScript.initHadoopExecution(org.apache.sysml.conf.DMLConfig config) |
Modifier and Type | Method and Description |
---|---|
static String |
MLContextUtil.getHopDAG(MLContext mlCtx,
Script script,
ArrayList<Integer> lines,
boolean performHOPRewrites,
boolean withSubgraph)
Get HOP DAG in dot format for a DML or PYDML Script.
|
static String |
MLContextUtil.getHopDAG(MLContext mlCtx,
Script script,
ArrayList<Integer> lines,
org.apache.spark.SparkConf newConf,
boolean performHOPRewrites,
boolean withSubgraph)
Get HOP DAG in dot format for a DML or PYDML Script.
|
Modifier and Type | Class and Description |
---|---|
class |
DMLScriptException
This exception should be thrown to flag DML Script errors.
|
Modifier and Type | Method and Description |
---|---|
static void |
SpoofMultiAggregate.aggregatePartialResults(SpoofCellwise.AggOp[] aggOps,
MatrixBlock c,
MatrixBlock b) |
static Class<?> |
CodegenUtils.compileClass(String name,
String src) |
static SpoofOperator |
CodegenUtils.createInstance(Class<?> cla) |
org.apache.sysml.runtime.instructions.cp.ScalarObject |
SpoofOuterProduct.execute(ArrayList<MatrixBlock> inputs,
ArrayList<org.apache.sysml.runtime.instructions.cp.ScalarObject> scalarObjects) |
org.apache.sysml.runtime.instructions.cp.ScalarObject |
SpoofOperator.execute(ArrayList<MatrixBlock> inputs,
ArrayList<org.apache.sysml.runtime.instructions.cp.ScalarObject> scalars) |
org.apache.sysml.runtime.instructions.cp.ScalarObject |
SpoofOuterProduct.execute(ArrayList<MatrixBlock> inputs,
ArrayList<org.apache.sysml.runtime.instructions.cp.ScalarObject> scalarObjects,
int numThreads) |
org.apache.sysml.runtime.instructions.cp.ScalarObject |
SpoofOperator.execute(ArrayList<MatrixBlock> inputs,
ArrayList<org.apache.sysml.runtime.instructions.cp.ScalarObject> scalars,
int k) |
org.apache.sysml.runtime.instructions.cp.ScalarObject |
SpoofRowwise.execute(ArrayList<MatrixBlock> inputs,
ArrayList<org.apache.sysml.runtime.instructions.cp.ScalarObject> scalarObjects,
int k) |
org.apache.sysml.runtime.instructions.cp.ScalarObject |
SpoofCellwise.execute(ArrayList<MatrixBlock> inputs,
ArrayList<org.apache.sysml.runtime.instructions.cp.ScalarObject> scalarObjects,
int k) |
MatrixBlock |
SpoofOuterProduct.execute(ArrayList<MatrixBlock> inputs,
ArrayList<org.apache.sysml.runtime.instructions.cp.ScalarObject> scalarObjects,
MatrixBlock out) |
MatrixBlock |
SpoofMultiAggregate.execute(ArrayList<MatrixBlock> inputs,
ArrayList<org.apache.sysml.runtime.instructions.cp.ScalarObject> scalarObjects,
MatrixBlock out) |
abstract MatrixBlock |
SpoofOperator.execute(ArrayList<MatrixBlock> inputs,
ArrayList<org.apache.sysml.runtime.instructions.cp.ScalarObject> scalars,
MatrixBlock out) |
MatrixBlock |
SpoofRowwise.execute(ArrayList<MatrixBlock> inputs,
ArrayList<org.apache.sysml.runtime.instructions.cp.ScalarObject> scalarObjects,
MatrixBlock out) |
MatrixBlock |
SpoofCellwise.execute(ArrayList<MatrixBlock> inputs,
ArrayList<org.apache.sysml.runtime.instructions.cp.ScalarObject> scalarObjects,
MatrixBlock out) |
MatrixBlock |
SpoofRowwise.execute(ArrayList<MatrixBlock> inputs,
ArrayList<org.apache.sysml.runtime.instructions.cp.ScalarObject> scalarObjects,
MatrixBlock out,
boolean allocTmp,
boolean aggIncr) |
MatrixBlock |
SpoofOuterProduct.execute(ArrayList<MatrixBlock> inputs,
ArrayList<org.apache.sysml.runtime.instructions.cp.ScalarObject> scalarObjects,
MatrixBlock out,
int numThreads) |
MatrixBlock |
SpoofMultiAggregate.execute(ArrayList<MatrixBlock> inputs,
ArrayList<org.apache.sysml.runtime.instructions.cp.ScalarObject> scalarObjects,
MatrixBlock out,
int k) |
MatrixBlock |
SpoofOperator.execute(ArrayList<MatrixBlock> inputs,
ArrayList<org.apache.sysml.runtime.instructions.cp.ScalarObject> scalars,
MatrixBlock out,
int k) |
MatrixBlock |
SpoofRowwise.execute(ArrayList<MatrixBlock> inputs,
ArrayList<org.apache.sysml.runtime.instructions.cp.ScalarObject> scalarObjects,
MatrixBlock out,
int k) |
MatrixBlock |
SpoofCellwise.execute(ArrayList<MatrixBlock> inputs,
ArrayList<org.apache.sysml.runtime.instructions.cp.ScalarObject> scalarObjects,
MatrixBlock out,
int k) |
static Class<?> |
CodegenUtils.getClass(String name) |
static Class<?> |
CodegenUtils.getClass(String name,
byte[] classBytes) |
static byte[] |
CodegenUtils.getClassData(String name) |
static Class<?> |
CodegenUtils.getClassSync(String name,
byte[] classBytes) |
protected SpoofOperator.SideInput[] |
SpoofOperator.prepInputMatrices(ArrayList<MatrixBlock> inputs) |
protected SpoofOperator.SideInput[] |
SpoofOperator.prepInputMatrices(ArrayList<MatrixBlock> inputs,
boolean denseOnly) |
protected SpoofOperator.SideInput[] |
SpoofOperator.prepInputMatrices(ArrayList<MatrixBlock> inputs,
boolean denseOnly,
boolean tB1) |
protected SpoofOperator.SideInput[] |
SpoofOperator.prepInputMatrices(ArrayList<MatrixBlock> inputs,
int offset,
boolean denseOnly) |
protected SpoofOperator.SideInput[] |
SpoofOperator.prepInputMatrices(ArrayList<MatrixBlock> inputs,
int offset,
int len,
boolean denseOnly,
boolean tB1) |
Modifier and Type | Method and Description |
---|---|
MatrixValue |
CompressedMatrixBlock.aggregateBinaryOperations(MatrixIndexes m1Index,
MatrixValue m1Value,
MatrixIndexes m2Index,
MatrixValue m2Value,
MatrixValue result,
org.apache.sysml.runtime.matrix.operators.AggregateBinaryOperator op) |
MatrixValue |
CompressedMatrixBlock.aggregateBinaryOperations(MatrixValue mv1,
MatrixValue mv2,
MatrixValue result,
org.apache.sysml.runtime.matrix.operators.AggregateBinaryOperator op) |
MatrixBlock |
CompressedMatrixBlock.aggregateTernaryOperations(MatrixBlock m1,
MatrixBlock m2,
MatrixBlock m3,
MatrixBlock ret,
org.apache.sysml.runtime.matrix.operators.AggregateTernaryOperator op,
boolean inCP) |
MatrixValue |
CompressedMatrixBlock.aggregateUnaryOperations(org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
MatrixValue result,
int blockingFactorRow,
int blockingFactorCol,
MatrixIndexes indexesIn) |
MatrixValue |
CompressedMatrixBlock.aggregateUnaryOperations(org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
MatrixValue result,
int blockingFactorRow,
int blockingFactorCol,
MatrixIndexes indexesIn,
boolean inCP) |
MatrixBlock |
CompressedMatrixBlock.appendOperations(MatrixBlock that,
MatrixBlock ret) |
MatrixBlock |
CompressedMatrixBlock.appendOperations(MatrixBlock that,
MatrixBlock ret,
boolean cbind) |
void |
CompressedMatrixBlock.appendOperations(MatrixValue v2,
ArrayList<org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue> outlist,
int blockRowFactor,
int blockColFactor,
boolean cbind,
boolean m2IsLast,
int nextNCol) |
protected double[] |
ColGroupValue.applyScalarOp(org.apache.sysml.runtime.matrix.operators.ScalarOperator op)
Method for use by subclasses.
|
protected double[] |
ColGroupValue.applyScalarOp(org.apache.sysml.runtime.matrix.operators.ScalarOperator op,
double newVal,
int numCols) |
MatrixValue |
CompressedMatrixBlock.binaryOperations(org.apache.sysml.runtime.matrix.operators.BinaryOperator op,
MatrixValue thatValue,
MatrixValue result) |
void |
CompressedMatrixBlock.binaryOperationsInPlace(org.apache.sysml.runtime.matrix.operators.BinaryOperator op,
MatrixValue thatValue) |
MatrixBlock |
CompressedMatrixBlock.chainMatrixMultOperations(MatrixBlock v,
MatrixBlock w,
MatrixBlock out,
org.apache.sysml.lops.MapMultChain.ChainType ctype) |
MatrixBlock |
CompressedMatrixBlock.chainMatrixMultOperations(MatrixBlock v,
MatrixBlock w,
MatrixBlock out,
org.apache.sysml.lops.MapMultChain.ChainType ctype,
int k) |
org.apache.sysml.runtime.instructions.cp.CM_COV_Object |
CompressedMatrixBlock.cmOperations(org.apache.sysml.runtime.matrix.operators.CMOperator op) |
org.apache.sysml.runtime.instructions.cp.CM_COV_Object |
CompressedMatrixBlock.cmOperations(org.apache.sysml.runtime.matrix.operators.CMOperator op,
MatrixBlock weights) |
MatrixBlock |
CompressedMatrixBlock.compress()
Compress the contents of this matrix block.
|
MatrixBlock |
CompressedMatrixBlock.compress(int k)
Compress block.
|
protected int[] |
ColGroupOffset.computeOffsets(boolean[] ind)
Utility function of sparse-unsafe operations.
|
static void |
ColGroupDDC1.computeRowSums(ColGroupDDC1[] grps,
MatrixBlock result,
org.apache.sysml.runtime.functionobjects.KahanFunction kplus,
int rl,
int ru) |
org.apache.sysml.runtime.instructions.cp.CM_COV_Object |
CompressedMatrixBlock.covOperations(org.apache.sysml.runtime.matrix.operators.COVOperator op,
MatrixBlock that) |
org.apache.sysml.runtime.instructions.cp.CM_COV_Object |
CompressedMatrixBlock.covOperations(org.apache.sysml.runtime.matrix.operators.COVOperator op,
MatrixBlock that,
MatrixBlock weights) |
MatrixBlock |
CompressedMatrixBlock.decompress()
Decompress block.
|
MatrixBlock |
CompressedMatrixBlock.decompress(int k)
Decompress block.
|
MatrixBlock |
CompressedMatrixBlock.groupedAggOperations(MatrixValue tgt,
MatrixValue wghts,
MatrixValue ret,
int ngroups,
org.apache.sysml.runtime.matrix.operators.Operator op) |
MatrixBlock |
CompressedMatrixBlock.groupedAggOperations(MatrixValue tgt,
MatrixValue wghts,
MatrixValue ret,
int ngroups,
org.apache.sysml.runtime.matrix.operators.Operator op,
int k) |
void |
CompressedMatrixBlock.incrementalAggregate(org.apache.sysml.runtime.matrix.operators.AggregateOperator aggOp,
MatrixValue newWithCorrection) |
void |
CompressedMatrixBlock.incrementalAggregate(org.apache.sysml.runtime.matrix.operators.AggregateOperator aggOp,
MatrixValue correction,
MatrixValue newWithCorrection) |
MatrixBlock |
CompressedMatrixBlock.leftIndexingOperations(MatrixBlock rhsMatrix,
int rl,
int ru,
int cl,
int cu,
MatrixBlock ret,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject.UpdateType update) |
MatrixBlock |
CompressedMatrixBlock.leftIndexingOperations(org.apache.sysml.runtime.instructions.cp.ScalarObject scalar,
int rl,
int cl,
MatrixBlock ret,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject.UpdateType update) |
void |
ColGroupOLE.leftMultByRowVector(ColGroupDDC a,
MatrixBlock result) |
void |
ColGroupDDC2.leftMultByRowVector(ColGroupDDC a,
MatrixBlock result) |
abstract void |
ColGroupValue.leftMultByRowVector(ColGroupDDC vector,
MatrixBlock result) |
void |
ColGroupDDC1.leftMultByRowVector(ColGroupDDC a,
MatrixBlock result) |
void |
ColGroupRLE.leftMultByRowVector(ColGroupDDC a,
MatrixBlock result) |
void |
ColGroupOLE.leftMultByRowVector(MatrixBlock vector,
MatrixBlock result) |
abstract void |
ColGroup.leftMultByRowVector(MatrixBlock vector,
MatrixBlock result)
Multiply the slice of the matrix that this column group represents by a
row vector on the left (the original column vector is assumed to be
transposed already i.e.
|
void |
ColGroupDDC2.leftMultByRowVector(MatrixBlock vector,
MatrixBlock result) |
void |
ColGroupUncompressed.leftMultByRowVector(MatrixBlock vector,
MatrixBlock result) |
void |
ColGroupDDC1.leftMultByRowVector(MatrixBlock vector,
MatrixBlock result) |
void |
ColGroupRLE.leftMultByRowVector(MatrixBlock vector,
MatrixBlock result) |
void |
ColGroupUncompressed.leftMultByRowVector(MatrixBlock vector,
MatrixBlock result,
int k) |
void |
CompressedMatrixBlock.permutationMatrixMultOperations(MatrixValue m2Val,
MatrixValue out1Val,
MatrixValue out2Val) |
void |
CompressedMatrixBlock.permutationMatrixMultOperations(MatrixValue m2Val,
MatrixValue out1Val,
MatrixValue out2Val,
int k) |
MatrixValue |
CompressedMatrixBlock.quaternaryOperations(org.apache.sysml.runtime.matrix.operators.QuaternaryOperator qop,
MatrixValue um,
MatrixValue vm,
MatrixValue wm,
MatrixValue out) |
MatrixValue |
CompressedMatrixBlock.quaternaryOperations(org.apache.sysml.runtime.matrix.operators.QuaternaryOperator qop,
MatrixValue um,
MatrixValue vm,
MatrixValue wm,
MatrixValue out,
int k) |
MatrixBlock |
CompressedMatrixBlock.randOperationsInPlace(RandomMatrixGenerator rgen,
LongStream nnzInBlock,
org.apache.commons.math3.random.Well1024a bigrand,
long bSeed) |
MatrixBlock |
CompressedMatrixBlock.randOperationsInPlace(RandomMatrixGenerator rgen,
LongStream nnzInBlock,
org.apache.commons.math3.random.Well1024a bigrand,
long bSeed,
int k) |
MatrixBlock |
CompressedMatrixBlock.removeEmptyOperations(MatrixBlock ret,
boolean rows) |
MatrixBlock |
CompressedMatrixBlock.removeEmptyOperations(MatrixBlock ret,
boolean rows,
MatrixBlock select) |
MatrixValue |
CompressedMatrixBlock.reorgOperations(org.apache.sysml.runtime.matrix.operators.ReorgOperator op,
MatrixValue ret,
int startRow,
int startColumn,
int length) |
MatrixValue |
CompressedMatrixBlock.replaceOperations(MatrixValue result,
double pattern,
double replacement) |
MatrixBlock |
CompressedMatrixBlock.rexpandOperations(MatrixBlock ret,
double max,
boolean rows,
boolean cast,
boolean ignore,
int k) |
static void |
ColGroupDDC1.rightMultByVector(ColGroupDDC1[] grps,
MatrixBlock vector,
MatrixBlock result,
int rl,
int ru) |
void |
ColGroupUncompressed.rightMultByVector(MatrixBlock vector,
MatrixBlock result,
int k) |
void |
ColGroupOLE.rightMultByVector(MatrixBlock vector,
MatrixBlock result,
int rl,
int ru) |
abstract void |
ColGroup.rightMultByVector(MatrixBlock vector,
MatrixBlock result,
int rl,
int ru)
Multiply the slice of the matrix that this column group represents by a
vector on the right.
|
void |
ColGroupDDC2.rightMultByVector(MatrixBlock vector,
MatrixBlock result,
int rl,
int ru) |
void |
ColGroupUncompressed.rightMultByVector(MatrixBlock vector,
MatrixBlock result,
int rl,
int ru) |
void |
ColGroupDDC1.rightMultByVector(MatrixBlock vector,
MatrixBlock result,
int rl,
int ru) |
void |
ColGroupRLE.rightMultByVector(MatrixBlock vector,
MatrixBlock result,
int rl,
int ru) |
ColGroup |
ColGroupOLE.scalarOperation(org.apache.sysml.runtime.matrix.operators.ScalarOperator op) |
abstract ColGroup |
ColGroup.scalarOperation(org.apache.sysml.runtime.matrix.operators.ScalarOperator op)
Perform the specified scalar operation directly on the compressed column
group, without decompressing individual cells if possible.
|
ColGroup |
ColGroupDDC2.scalarOperation(org.apache.sysml.runtime.matrix.operators.ScalarOperator op) |
ColGroup |
ColGroupUncompressed.scalarOperation(org.apache.sysml.runtime.matrix.operators.ScalarOperator op) |
ColGroup |
ColGroupDDC1.scalarOperation(org.apache.sysml.runtime.matrix.operators.ScalarOperator op) |
ColGroup |
ColGroupRLE.scalarOperation(org.apache.sysml.runtime.matrix.operators.ScalarOperator op) |
MatrixValue |
CompressedMatrixBlock.scalarOperations(org.apache.sysml.runtime.matrix.operators.ScalarOperator sop,
MatrixValue result) |
MatrixBlock |
CompressedMatrixBlock.seqOperationsInPlace(double from,
double to,
double incr) |
MatrixBlock |
CompressedMatrixBlock.sliceOperations(int rl,
int ru,
int cl,
int cu,
org.apache.sysml.runtime.controlprogram.caching.CacheBlock ret) |
MatrixValue |
CompressedMatrixBlock.sortOperations(MatrixValue weights,
MatrixValue result) |
void |
CompressedMatrixBlock.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
double scalar,
double scalar2,
CTableMap resultMap,
MatrixBlock resultBlock) |
void |
CompressedMatrixBlock.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
double scalar,
MatrixValue that,
CTableMap resultMap,
MatrixBlock resultBlock) |
void |
CompressedMatrixBlock.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixIndexes ix1,
double scalar,
boolean left,
int brlen,
CTableMap resultMap,
MatrixBlock resultBlock) |
void |
CompressedMatrixBlock.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixValue that,
double scalar,
boolean ignoreZeros,
CTableMap resultMap,
MatrixBlock resultBlock) |
void |
CompressedMatrixBlock.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixValue that,
double scalar,
MatrixBlock resultBlock) |
void |
CompressedMatrixBlock.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixValue that,
MatrixValue that2,
CTableMap resultMap) |
void |
CompressedMatrixBlock.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixValue that,
MatrixValue that2,
CTableMap resultMap,
MatrixBlock resultBlock) |
MatrixBlock |
CompressedMatrixBlock.transposeSelfMatrixMultOperations(MatrixBlock out,
org.apache.sysml.lops.MMTSJ.MMTSJType tstype) |
MatrixBlock |
CompressedMatrixBlock.transposeSelfMatrixMultOperations(MatrixBlock out,
org.apache.sysml.lops.MMTSJ.MMTSJType tstype,
int k) |
MatrixBlock |
CompressedMatrixBlock.uaggouterchainOperations(MatrixBlock mbLeft,
MatrixBlock mbRight,
MatrixBlock mbOut,
org.apache.sysml.runtime.matrix.operators.BinaryOperator bOp,
org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator uaggOp) |
abstract void |
ColGroup.unaryAggregateOperations(org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
MatrixBlock result) |
void |
ColGroupUncompressed.unaryAggregateOperations(org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
MatrixBlock ret) |
void |
ColGroupValue.unaryAggregateOperations(org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
MatrixBlock result) |
void |
ColGroupOffset.unaryAggregateOperations(org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
MatrixBlock result,
int rl,
int ru) |
void |
ColGroupDDC.unaryAggregateOperations(org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
MatrixBlock result,
int rl,
int ru) |
abstract void |
ColGroupValue.unaryAggregateOperations(org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
MatrixBlock result,
int rl,
int ru) |
MatrixValue |
CompressedMatrixBlock.unaryOperations(org.apache.sysml.runtime.matrix.operators.UnaryOperator op,
MatrixValue result) |
void |
CompressedMatrixBlock.unaryOperationsInPlace(org.apache.sysml.runtime.matrix.operators.UnaryOperator op) |
MatrixValue |
CompressedMatrixBlock.zeroOutOperations(MatrixValue result,
org.apache.sysml.runtime.util.IndexRange range,
boolean complementary) |
Constructor and Description |
---|
ColGroupUncompressed(List<Integer> colIndicesList,
MatrixBlock rawblock)
Main constructor.
|
Modifier and Type | Method and Description |
---|---|
static List<int[]> |
PlanningCoCoder.findCocodesByPartitioning(CompressedSizeEstimator sizeEstimator,
List<Integer> cols,
CompressedSizeInfo[] colInfos,
int numRows,
int k) |
Modifier and Type | Method and Description |
---|---|
static CompressedSizeEstimator |
SizeEstimatorFactory.getSizeEstimator(MatrixBlock data,
int numRows) |
Constructor and Description |
---|
CompressedSizeEstimatorSample(MatrixBlock data,
int sampleSize) |
Modifier and Type | Method and Description |
---|---|
static int |
InstructionUtils.checkNumFields(String[] parts,
int expected) |
static int |
InstructionUtils.checkNumFields(String[] parts,
int expected1,
int expected2) |
static int |
InstructionUtils.checkNumFields(String str,
int expected) |
static int |
InstructionUtils.checkNumFields(String str,
int expected1,
int expected2) |
org.apache.sysml.runtime.controlprogram.caching.MatrixObject[] |
MRJobInstruction.extractOutputMatrices(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec)
Extracts MatrixObject references to output variables, all of which will be
of MATRIX data type, and stores them in
outputMatrices . |
static org.apache.sysml.runtime.instructions.mr.AggregateBinaryInstruction[] |
MRInstructionParser.parseAggregateBinaryInstructions(String str) |
static org.apache.sysml.runtime.instructions.mr.AggregateInstruction[] |
MRInstructionParser.parseAggregateInstructions(String str) |
static org.apache.sysml.runtime.matrix.operators.BinaryOperator |
InstructionUtils.parseBinaryOperator(String opcode) |
static org.apache.sysml.runtime.instructions.mr.CM_N_COVInstruction[] |
MRInstructionParser.parseCM_N_COVInstructions(String str) |
static org.apache.sysml.runtime.instructions.mr.MRInstruction[] |
MRInstructionParser.parseCombineInstructions(String str) |
static org.apache.sysml.runtime.instructions.mr.CSVReblockInstruction[] |
MRInstructionParser.parseCSVReblockInstructions(String str) |
static org.apache.sysml.runtime.instructions.mr.CSVWriteInstruction[] |
MRInstructionParser.parseCSVWriteInstructions(String str) |
static org.apache.sysml.runtime.instructions.mr.DataGenMRInstruction[] |
MRInstructionParser.parseDataGenInstructions(String str) |
static org.apache.sysml.runtime.matrix.operators.BinaryOperator |
InstructionUtils.parseExtendedBinaryOperator(String opcode) |
static org.apache.sysml.runtime.instructions.mr.GroupedAggregateInstruction[] |
MRInstructionParser.parseGroupedAggInstructions(String str) |
static Instruction[] |
InstructionParser.parseMixedInstructions(String str) |
static org.apache.sysml.runtime.instructions.mr.MRInstruction[] |
MRInstructionParser.parseMixedInstructions(String str) |
static org.apache.sysml.runtime.instructions.mr.ReblockInstruction[] |
MRInstructionParser.parseReblockInstructions(String str) |
static org.apache.sysml.runtime.matrix.operators.ScalarOperator |
InstructionUtils.parseScalarBinaryOperator(String opcode,
boolean arg1IsScalar)
scalar-matrix operator
|
static org.apache.sysml.runtime.matrix.operators.ScalarOperator |
InstructionUtils.parseScalarBinaryOperator(String opcode,
boolean arg1IsScalar,
double constant)
scalar-matrix operator
|
static org.apache.sysml.runtime.instructions.cp.CPInstruction |
CPInstructionParser.parseSingleInstruction(org.apache.sysml.runtime.instructions.cp.CPInstruction.CPType cptype,
String str) |
static GPUInstruction |
GPUInstructionParser.parseSingleInstruction(GPUInstruction.GPUINSTRUCTION_TYPE gputype,
String str) |
static org.apache.sysml.runtime.instructions.mr.MRInstruction |
MRInstructionParser.parseSingleInstruction(org.apache.sysml.runtime.instructions.mr.MRInstruction.MRINSTRUCTION_TYPE mrtype,
String str) |
static SPInstruction |
SPInstructionParser.parseSingleInstruction(SPInstruction.SPINSTRUCTION_TYPE sptype,
String str) |
static Instruction |
InstructionParser.parseSingleInstruction(String str) |
static org.apache.sysml.runtime.instructions.mr.MRInstruction |
MRInstructionParser.parseSingleInstruction(String str) |
static org.apache.sysml.runtime.instructions.cp.CPInstruction |
CPInstructionParser.parseSingleInstruction(String str) |
static GPUInstruction |
GPUInstructionParser.parseSingleInstruction(String str) |
static SPInstruction |
SPInstructionParser.parseSingleInstruction(String str) |
void |
Instruction.postprocessInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec)
This method should be used for any tear down after executing this instruction.
|
Instruction |
Instruction.preprocessInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec)
This method should be used for any setup before executing this instruction.
|
void |
MRJobInstruction.printCompleteMRJobInstruction(MatrixCharacteristics[] resultStats) |
abstract void |
Instruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec)
This method should be used to execute the instruction.
|
void |
MRJobInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
Instruction.updateInstructionThreadID(String pattern,
String replace)
All instructions that have thread-specific filenames or names encoded in it
should overwrite this method in order to update (1) the in-memory instruction
and (2) the instruction string
|
void |
MRJobInstruction.updateInstructionThreadID(String pattern,
String replace) |
Modifier and Type | Method and Description |
---|---|
protected org.apache.sysml.runtime.controlprogram.caching.MatrixObject |
GPUInstruction.getDenseMatrixOutputForGPUInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
String name,
long numRows,
long numCols)
Helper method to get the output block (allocated on the GPU)
Also records performance information into
Statistics |
protected org.apache.sysml.runtime.controlprogram.caching.MatrixObject |
GPUInstruction.getMatrixInputForGPUInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
String name)
Helper method to get the input block (allocated on the GPU)
Also records performance information into
Statistics |
static MatrixAppendGPUInstruction |
MatrixAppendGPUInstruction.parseInstruction(String str) |
static AggregateBinaryGPUInstruction |
AggregateBinaryGPUInstruction.parseInstruction(String str) |
static RelationalBinaryGPUInstruction |
RelationalBinaryGPUInstruction.parseInstruction(String str) |
static BuiltinUnaryGPUInstruction |
BuiltinUnaryGPUInstruction.parseInstruction(String str) |
static ReorgGPUInstruction |
ReorgGPUInstruction.parseInstruction(String str) |
static BuiltinBinaryGPUInstruction |
BuiltinBinaryGPUInstruction.parseInstruction(String str) |
static ConvolutionGPUInstruction |
ConvolutionGPUInstruction.parseInstruction(String str) |
static MatrixMatrixAxpyGPUInstruction |
MatrixMatrixAxpyGPUInstruction.parseInstruction(String str) |
static MatrixIndexingGPUInstruction |
MatrixIndexingGPUInstruction.parseInstruction(String str) |
static AggregateUnaryGPUInstruction |
AggregateUnaryGPUInstruction.parseInstruction(String str) |
static MMTSJGPUInstruction |
MMTSJGPUInstruction.parseInstruction(String str)
parse MMTSJ GPU instruction
|
static ArithmeticBinaryGPUInstruction |
ArithmeticBinaryGPUInstruction.parseInstruction(String str) |
void |
GPUInstruction.postprocessInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
Instruction |
GPUInstruction.preprocessInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
ConvolutionGPUInstruction.processBiasInstruction(String instOpcode,
org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
ConvolutionGPUInstruction.processChannelSumsInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixAppendGPUInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
abstract void |
GPUInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
AggregateBinaryGPUInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixMatrixArithmeticGPUInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
ScalarMatrixRelationalBinaryGPUInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixBuiltinGPUInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
ReorgGPUInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
ConvolutionGPUInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixMatrixAxpyGPUInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
ScalarMatrixArithmeticGPUInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixIndexingGPUInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixMatrixRelationalBinaryGPUInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
AggregateUnaryGPUInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MMTSJGPUInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec)
process MMTSJ GPU instruction
|
void |
MatrixMatrixBuiltinGPUInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
ConvolutionGPUInstruction.processReLUBackwardInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
Constructor and Description |
---|
ConvolutionGPUInstruction(org.apache.sysml.runtime.instructions.cp.CPOperand in1,
org.apache.sysml.runtime.instructions.cp.CPOperand in2,
org.apache.sysml.runtime.instructions.cp.CPOperand in3,
org.apache.sysml.runtime.instructions.cp.CPOperand out,
String opcode,
String istr,
double intermediateMemoryBudget) |
ConvolutionGPUInstruction(org.apache.sysml.runtime.instructions.cp.CPOperand in1,
org.apache.sysml.runtime.instructions.cp.CPOperand in2,
org.apache.sysml.runtime.instructions.cp.CPOperand out,
String opcode,
String istr,
double intermediateMemoryBudget) |
Modifier and Type | Method and Description |
---|---|
boolean |
GPUObject.acquireDeviceModifyDense() |
boolean |
GPUObject.acquireDeviceModifySparse() |
boolean |
GPUObject.acquireDeviceRead(String opcode) |
void |
GPUObject.addReadLock() |
void |
GPUObject.addWriteLock() |
jcuda.Pointer |
GPUContext.allocate(long size)
Convenience method for
GPUContext.allocate(String, long, int) , defaults statsCount to 1. |
jcuda.Pointer |
GPUContext.allocate(String instructionName,
long size)
Convenience method for
GPUContext.allocate(String, long, int) , defaults statsCount to 1. |
jcuda.Pointer |
GPUContext.allocate(String instructionName,
long size,
int statsCount)
Allocates temporary space on the device.
|
void |
GPUObject.allocateAndFillDense(double v)
Allocates a dense matrix of size obtained from the attached matrix metadata
and fills it up with a single value
|
static CSRPointer |
CSRPointer.allocateEmpty(GPUContext gCtx,
long nnz2,
long rows)
Factory method to allocate an empty CSR Sparse matrix on the GPU
|
static CSRPointer |
CSRPointer.allocateForDgeam(GPUContext gCtx,
jcuda.jcusparse.cusparseHandle handle,
CSRPointer A,
CSRPointer B,
int m,
int n)
Estimates the number of non zero elements from the results of a sparse cusparseDgeam operation
C = a op(A) + b op(B)
|
static CSRPointer |
CSRPointer.allocateForMatrixMultiply(GPUContext gCtx,
jcuda.jcusparse.cusparseHandle handle,
CSRPointer A,
int transA,
CSRPointer B,
int transB,
int m,
int n,
int k)
Estimates the number of non-zero elements from the result of a sparse matrix multiplication C = A * B
and returns the
CSRPointer to C with the appropriate GPU memory. |
void |
GPUObject.allocateSparseAndEmpty()
Allocates a sparse and empty
GPUObject
This is the result of operations that are both non zero matrices. |
static void |
JCudaKernels.checkResult(int cuResult) |
void |
GPUObject.clearData()
lazily clears the data associated with this
GPUObject instance |
void |
GPUObject.clearData(boolean eager)
Clears the data associated with this
GPUObject instance |
void |
GPUContext.clearMemory()
Clears all memory used by this
GPUContext . |
CSRPointer |
CSRPointer.clone(int rows) |
static CSRPointer |
GPUObject.columnMajorDenseToRowMajorSparse(GPUContext gCtx,
jcuda.jcusparse.cusparseHandle cusparseHandle,
jcuda.Pointer densePtr,
int rows,
int cols)
Convenience method to convert a CSR matrix to a dense matrix on the GPU
Since the allocated matrix is temporary, bookkeeping is not updated.
|
protected void |
GPUObject.copyFromDeviceToHost(String instName,
boolean isEviction) |
static void |
CSRPointer.copyPtrToHost(CSRPointer src,
int rows,
long nnz,
int[] rowPtr,
int[] colInd)
Static method to copy a CSR sparse matrix from Device to host
|
static void |
CSRPointer.copyToDevice(GPUContext gCtx,
CSRPointer dest,
int rows,
long nnz,
int[] rowPtr,
int[] colInd,
double[] values)
Static method to copy a CSR sparse matrix from Host to Device
|
void |
CSRPointer.deallocate()
Calls cudaFree lazily on the allocated
Pointer instances |
void |
CSRPointer.deallocate(boolean eager)
Calls cudaFree lazily or eagerly on the allocated
Pointer instances |
void |
GPUObject.denseColumnMajorToRowMajor()
Convenience method.
|
void |
GPUObject.denseRowMajorToColumnMajor()
Convenience method.
|
void |
GPUObject.denseToSparse()
Converts this GPUObject from dense to sparse format.
|
void |
GPUContext.destroy()
Destroys this GPUContext object.
|
void |
GPUContext.ensureComputeCapability()
Makes sure that GPU that SystemML is trying to use has the minimum compute capability needed.
|
protected void |
GPUContext.evict(long GPUSize)
Convenience wrapper over
GPUContext.evict(String, long) . |
protected void |
GPUContext.evict(String instructionName,
long neededSize)
Memory on the GPU is tried to be freed up until either a chunk of needed size is freed up
or it fails.
|
static void |
GPUContextPool.freeAllGPUContexts()
Unreserves all GPUContexts
|
static ExecutionConfig |
ExecutionConfig.getConfigForSimpleMatrixOperations(int rlen,
int clen)
Use this for simple vector operations and use following in the kernel
int index = blockIdx.x * blockDim.x + threadIdx.x
|
static ExecutionConfig |
ExecutionConfig.getConfigForSimpleVectorOperations(int numCells)
Use this for simple vector operations and use following in the kernel
int index = blockIdx.x * blockDim.x + threadIdx.x
|
static int |
GPUContextPool.getDeviceCount()
Number of available devices on this machine
|
jcuda.runtime.cudaDeviceProp |
GPUContext.getGPUProperties()
Gets the device properties for the active GPU (set with cudaSetDevice()).
|
int |
GPUContext.getMaxBlocks()
Gets the maximum number of blocks supported by the active cuda device.
|
long |
GPUContext.getMaxSharedMemory()
Gets the shared memory per block supported by the active cuda device.
|
int |
GPUContext.getMaxThreadsPerBlock()
Gets the maximum number of threads per block for "active" GPU.
|
protected long |
GPUObject.getSizeOnDevice() |
int |
GPUContext.getWarpSize()
Gets the warp size supported by the active cuda device.
|
static void |
GPUContextPool.initializeGPU()
Static initialization of the number of devices
Also sets behaviour for J{Cuda, Cudnn, Cublas, Cusparse} in case of error
Initializes the CUDA driver
All these need be done once, and not per GPU
|
void |
GPUContext.initializeThread()
Sets the device for the calling thread.
|
boolean |
GPUObject.isSparseAndEmpty()
If this
GPUObject is sparse and empty
Being allocated is a prerequisite to being sparse and empty. |
void |
JCudaKernels.launchKernel(String name,
ExecutionConfig config,
Object... arguments)
Setups the kernel parameters and launches the kernel using cuLaunchKernel API.
|
void |
GPUContext.printMemoryInfo(String opcode)
Print information of memory usage.
|
void |
GPUObject.releaseInput()
Releases input allocated on GPU
|
void |
GPUObject.releaseOutput()
releases output allocated on GPU
|
void |
GPUObject.releaseReadLock() |
void |
GPUObject.releaseWriteLock() |
static List<GPUContext> |
GPUContextPool.reserveAllGPUContexts()
Reserves and gets an initialized list of GPUContexts
|
void |
GPUObject.setDenseMatrixCudaPointer(jcuda.Pointer densePtr)
Convenience method to directly set the dense matrix pointer on GPU
|
void |
GPUObject.setSparseMatrixCudaPointer(CSRPointer sparseMatrixPtr)
Convenience method to directly set the sparse matrix on GPU
Needed for operations like cusparseDcsrgemm(cusparseHandle, int, int, int, int, int, cusparseMatDescr, int, Pointer, Pointer, Pointer, cusparseMatDescr, int, Pointer, Pointer, Pointer, cusparseMatDescr, Pointer, Pointer, Pointer)
|
void |
GPUObject.sparseToColumnMajorDense()
More efficient method to convert sparse to dense but returns dense in column major format
|
void |
GPUObject.sparseToDense()
Convert sparse to dense (Performs transpose, use sparseToColumnMajorDense if the kernel can deal with column major format)
|
void |
GPUObject.sparseToDense(String instructionName)
Convert sparse to dense (Performs transpose, use sparseToColumnMajorDense if the kernel can deal with column major format)
Also records per instruction invokation of sparseToDense.
|
jcuda.Pointer |
CSRPointer.toColumnMajorDenseMatrix(jcuda.jcusparse.cusparseHandle cusparseHandle,
jcuda.jcublas.cublasHandle cublasHandle,
int rows,
int cols,
String instName)
Copies this CSR matrix on the GPU to a dense column-major matrix
on the GPU.
|
static int |
CSRPointer.toIntExact(long l) |
static int |
GPUObject.toIntExact(long l) |
static jcuda.Pointer |
GPUObject.transpose(GPUContext gCtx,
jcuda.Pointer densePtr,
int m,
int n,
int lda,
int ldc)
Transposes a dense matrix on the GPU by calling the cublasDgeam operation
|
Constructor and Description |
---|
GPUContext(int deviceNum) |
Modifier and Type | Method and Description |
---|---|
protected void |
BinarySPInstruction.checkBinaryAppendInputCharacteristics(org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext sec,
boolean cbind,
boolean checkSingleBlk,
boolean checkAligned) |
protected void |
BinarySPInstruction.checkMatrixMatrixBinaryCharacteristics(org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext sec) |
static MatrixBlock |
MatrixIndexingSPInstruction.inmemoryIndexing(org.apache.spark.api.java.JavaPairRDD<MatrixIndexes,MatrixBlock> in1,
MatrixCharacteristics mcIn,
MatrixCharacteristics mcOut,
org.apache.sysml.runtime.util.IndexRange ixrange) |
protected static String |
BinarySPInstruction.parseBinaryInstruction(String instr,
org.apache.sysml.runtime.instructions.cp.CPOperand in1,
org.apache.sysml.runtime.instructions.cp.CPOperand in2,
org.apache.sysml.runtime.instructions.cp.CPOperand out) |
protected static String |
BinarySPInstruction.parseBinaryInstruction(String instr,
org.apache.sysml.runtime.instructions.cp.CPOperand in1,
org.apache.sysml.runtime.instructions.cp.CPOperand in2,
org.apache.sysml.runtime.instructions.cp.CPOperand in3,
org.apache.sysml.runtime.instructions.cp.CPOperand out) |
static BuiltinNarySPInstruction |
BuiltinNarySPInstruction.parseInstruction(String str) |
static CheckpointSPInstruction |
CheckpointSPInstruction.parseInstruction(String str) |
static BuiltinBinarySPInstruction |
BuiltinBinarySPInstruction.parseInstruction(String str) |
static MatrixReshapeSPInstruction |
MatrixReshapeSPInstruction.parseInstruction(String str) |
static BuiltinUnarySPInstruction |
BuiltinUnarySPInstruction.parseInstruction(String str) |
static CovarianceSPInstruction |
CovarianceSPInstruction.parseInstruction(String str) |
static QuantilePickSPInstruction |
QuantilePickSPInstruction.parseInstruction(String str) |
static AggregateUnarySPInstruction |
AggregateUnarySPInstruction.parseInstruction(String str) |
static TernarySPInstruction |
TernarySPInstruction.parseInstruction(String inst) |
static ConvolutionSPInstruction |
ConvolutionSPInstruction.parseInstruction(String str) |
static AppendGSPInstruction |
AppendGSPInstruction.parseInstruction(String str) |
static IndexingSPInstruction |
IndexingSPInstruction.parseInstruction(String str) |
static ArithmeticBinarySPInstruction |
ArithmeticBinarySPInstruction.parseInstruction(String str) |
static CpmmSPInstruction |
CpmmSPInstruction.parseInstruction(String str) |
static ReblockSPInstruction |
ReblockSPInstruction.parseInstruction(String str) |
static UaggOuterChainSPInstruction |
UaggOuterChainSPInstruction.parseInstruction(String str) |
static MapmmSPInstruction |
MapmmSPInstruction.parseInstruction(String str) |
static PMapmmSPInstruction |
PMapmmSPInstruction.parseInstruction(String str) |
static QuaternarySPInstruction |
QuaternarySPInstruction.parseInstruction(String str) |
static TsmmSPInstruction |
TsmmSPInstruction.parseInstruction(String str) |
static Tsmm2SPInstruction |
Tsmm2SPInstruction.parseInstruction(String str) |
static AppendGAlignedSPInstruction |
AppendGAlignedSPInstruction.parseInstruction(String str) |
static SpoofSPInstruction |
SpoofSPInstruction.parseInstruction(String str) |
static CompressionSPInstruction |
CompressionSPInstruction.parseInstruction(String str) |
static QuantileSortSPInstruction |
QuantileSortSPInstruction.parseInstruction(String str) |
static CumulativeAggregateSPInstruction |
CumulativeAggregateSPInstruction.parseInstruction(String str) |
static CastSPInstruction |
CastSPInstruction.parseInstruction(String str) |
static AggregateTernarySPInstruction |
AggregateTernarySPInstruction.parseInstruction(String str) |
static ZipmmSPInstruction |
ZipmmSPInstruction.parseInstruction(String str) |
static ParameterizedBuiltinSPInstruction |
ParameterizedBuiltinSPInstruction.parseInstruction(String str) |
static RandSPInstruction |
RandSPInstruction.parseInstruction(String str) |
static PmmSPInstruction |
PmmSPInstruction.parseInstruction(String str) |
static AppendMSPInstruction |
AppendMSPInstruction.parseInstruction(String str) |
static CentralMomentSPInstruction |
CentralMomentSPInstruction.parseInstruction(String str) |
static RelationalBinarySPInstruction |
RelationalBinarySPInstruction.parseInstruction(String str) |
static PlusMultSPInstruction |
PlusMultSPInstruction.parseInstruction(String str) |
static MapmmChainSPInstruction |
MapmmChainSPInstruction.parseInstruction(String str) |
static RmmSPInstruction |
RmmSPInstruction.parseInstruction(String str) |
static MultiReturnParameterizedBuiltinSPInstruction |
MultiReturnParameterizedBuiltinSPInstruction.parseInstruction(String str) |
static CSVReblockSPInstruction |
CSVReblockSPInstruction.parseInstruction(String str) |
static BinUaggChainSPInstruction |
BinUaggChainSPInstruction.parseInstruction(String str) |
static AppendRSPInstruction |
AppendRSPInstruction.parseInstruction(String str) |
static CumulativeOffsetSPInstruction |
CumulativeOffsetSPInstruction.parseInstruction(String str) |
static WriteSPInstruction |
WriteSPInstruction.parseInstruction(String str) |
static ReorgSPInstruction |
ReorgSPInstruction.parseInstruction(String str) |
void |
SPInstruction.postprocessInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
Instruction |
SPInstruction.preprocessInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
protected org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock> |
CSVReblockSPInstruction.processFrameCSVReblockInstruction(org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext sec,
MatrixCharacteristics mcOut,
org.apache.sysml.parser.Expression.ValueType[] schema) |
protected void |
ReblockSPInstruction.processFrameReblockInstruction(org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext sec,
InputInfo iinfo) |
protected void |
WriteSPInstruction.processFrameWriteInstruction(org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext sec,
String fname,
OutputInfo oi,
org.apache.sysml.parser.Expression.ValueType[] schema) |
void |
BuiltinNarySPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
CheckpointSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixReshapeSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
CovarianceSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixIndexingSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
QuantilePickSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixBVectorArithmeticSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixBVectorRelationalSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixBuiltinSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
AggregateUnarySPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixScalarBuiltinSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
TernarySPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
ConvolutionSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
AppendGSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
CpmmSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
FrameAppendRSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
ReblockSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
UaggOuterChainSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
FrameIndexingSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
FrameAppendMSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MapmmSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
PMapmmSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
QuaternarySPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
TsmmSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
Tsmm2SPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixMatrixBuiltinSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixAppendRSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
AppendGAlignedSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixMatrixArithmeticSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
SpoofSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
CompressionSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
QuantileSortSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
CumulativeAggregateSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
CastSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixAppendMSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
AggregateTernarySPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
ZipmmSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
abstract void |
SPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
ParameterizedBuiltinSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixScalarArithmeticSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
RandSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
PmmSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixBVectorBuiltinSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixScalarRelationalSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
CentralMomentSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
PlusMultSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MapmmChainSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
RmmSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MultiReturnParameterizedBuiltinSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
CSVReblockSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
MatrixMatrixRelationalSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
BinUaggChainSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
CumulativeOffsetSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
WriteSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
ReorgSPInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
protected void |
BinarySPInstruction.processMatrixBVectorBinaryInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
org.apache.sysml.lops.BinaryM.VectorType vtype) |
protected org.apache.spark.api.java.JavaPairRDD<MatrixIndexes,MatrixBlock> |
CSVReblockSPInstruction.processMatrixCSVReblockInstruction(org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext sec,
MatrixCharacteristics mcOut) |
protected void |
BinarySPInstruction.processMatrixMatrixBinaryInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec)
Common binary matrix-matrix process instruction
|
protected void |
ReblockSPInstruction.processMatrixReblockInstruction(org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext sec,
InputInfo iinfo) |
protected void |
BinarySPInstruction.processMatrixScalarBinaryInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
protected void |
WriteSPInstruction.processMatrixWriteInstruction(org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext sec,
String fname,
OutputInfo oi) |
void |
ParameterizedBuiltinSPInstruction.setOutputCharacteristicsForGroupedAgg(MatrixCharacteristics mc1,
MatrixCharacteristics mcOut,
org.apache.spark.api.java.JavaPairRDD<MatrixIndexes,MatrixCell> out) |
protected void |
BinarySPInstruction.updateBinaryAppendOutputMatrixCharacteristics(org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext sec,
boolean cbind) |
protected MatrixCharacteristics |
BinarySPInstruction.updateBinaryMMOutputMatrixCharacteristics(org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext sec,
boolean checkCommonDim) |
protected void |
ComputationSPInstruction.updateBinaryOutputMatrixCharacteristics(org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext sec) |
protected void |
UaggOuterChainSPInstruction.updateUnaryAggOutputMatrixCharacteristics(org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext sec) |
protected void |
ComputationSPInstruction.updateUnaryAggOutputMatrixCharacteristics(org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext sec,
org.apache.sysml.runtime.functionobjects.IndexFunction ixFn) |
protected void |
ComputationSPInstruction.updateUnaryOutputMatrixCharacteristics(org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext sec) |
protected void |
ComputationSPInstruction.updateUnaryOutputMatrixCharacteristics(org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext sec,
String nameIn,
String nameOut) |
Constructor and Description |
---|
MatrixBVectorArithmeticSPInstruction(org.apache.sysml.runtime.matrix.operators.Operator op,
org.apache.sysml.runtime.instructions.cp.CPOperand in1,
org.apache.sysml.runtime.instructions.cp.CPOperand in2,
org.apache.sysml.runtime.instructions.cp.CPOperand out,
org.apache.sysml.lops.BinaryM.VectorType vtype,
String opcode,
String istr) |
MatrixBVectorBuiltinSPInstruction(org.apache.sysml.runtime.matrix.operators.Operator op,
org.apache.sysml.runtime.instructions.cp.CPOperand in1,
org.apache.sysml.runtime.instructions.cp.CPOperand in2,
org.apache.sysml.runtime.instructions.cp.CPOperand out,
org.apache.sysml.lops.BinaryM.VectorType vtype,
String opcode,
String istr) |
MatrixBVectorRelationalSPInstruction(org.apache.sysml.runtime.matrix.operators.Operator op,
org.apache.sysml.runtime.instructions.cp.CPOperand in1,
org.apache.sysml.runtime.instructions.cp.CPOperand in2,
org.apache.sysml.runtime.instructions.cp.CPOperand out,
org.apache.sysml.lops.BinaryM.VectorType vtype,
String opcode,
String istr) |
MatrixMatrixArithmeticSPInstruction(org.apache.sysml.runtime.matrix.operators.Operator op,
org.apache.sysml.runtime.instructions.cp.CPOperand in1,
org.apache.sysml.runtime.instructions.cp.CPOperand in2,
org.apache.sysml.runtime.instructions.cp.CPOperand out,
String opcode,
String istr) |
MatrixMatrixRelationalSPInstruction(org.apache.sysml.runtime.matrix.operators.Operator op,
org.apache.sysml.runtime.instructions.cp.CPOperand in1,
org.apache.sysml.runtime.instructions.cp.CPOperand in2,
org.apache.sysml.runtime.instructions.cp.CPOperand out,
String opcode,
String istr) |
Modifier and Type | Method and Description |
---|---|
static MatrixBlock |
RDDConverterUtilsExt.allocateDenseOrSparse(long rlen,
long clen,
boolean isSparse) |
static org.apache.spark.api.java.JavaRDD<String> |
FrameRDDConverterUtils.binaryBlockToTextCell(org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock> input,
MatrixCharacteristics mcIn) |
static org.apache.spark.api.java.JavaPairRDD<MatrixIndexes,MatrixBlock> |
RDDConverterUtils.binaryCellToBinaryBlock(org.apache.spark.api.java.JavaSparkContext sc,
org.apache.spark.api.java.JavaPairRDD<MatrixIndexes,MatrixCell> input,
MatrixCharacteristics mcOut,
boolean outputEmptyBlocks) |
static byte[] |
RDDConverterUtilsExt.convertMBtoPy4JDenseArr(MatrixBlock mb) |
static MatrixBlock |
RDDConverterUtilsExt.convertPy4JArrayToMB(byte[] data,
int rlen,
int clen) |
static MatrixBlock |
RDDConverterUtilsExt.convertPy4JArrayToMB(byte[] data,
int rlen,
int clen,
boolean isSparse) |
static MatrixBlock |
RDDConverterUtilsExt.convertPy4JArrayToMB(byte[] data,
long rlen,
long clen) |
static MatrixBlock |
RDDConverterUtilsExt.convertPy4JArrayToMB(byte[] data,
long rlen,
long clen,
boolean isSparse) |
static MatrixBlock |
RDDConverterUtilsExt.convertSciPyCOOToMB(byte[] data,
byte[] row,
byte[] col,
int rlen,
int clen,
int nnz) |
static MatrixBlock |
RDDConverterUtilsExt.convertSciPyCOOToMB(byte[] data,
byte[] row,
byte[] col,
long rlen,
long clen,
long nnz) |
static org.apache.spark.api.java.JavaPairRDD<MatrixIndexes,MatrixBlock> |
RDDConverterUtilsExt.coordinateMatrixToBinaryBlock(org.apache.spark.api.java.JavaSparkContext sc,
org.apache.spark.mllib.linalg.distributed.CoordinateMatrix input,
MatrixCharacteristics mcIn,
boolean outputEmptyBlocks)
Example usage:
|
static org.apache.spark.api.java.JavaPairRDD<MatrixIndexes,MatrixBlock> |
RDDConverterUtilsExt.coordinateMatrixToBinaryBlock(org.apache.spark.SparkContext sc,
org.apache.spark.mllib.linalg.distributed.CoordinateMatrix input,
MatrixCharacteristics mcIn,
boolean outputEmptyBlocks) |
static void |
RDDConverterUtilsExt.copyRowBlocks(MatrixBlock mb,
int rowIndex,
MatrixBlock ret,
int numRowsPerBlock,
int rlen,
int clen) |
static void |
RDDConverterUtilsExt.copyRowBlocks(MatrixBlock mb,
int rowIndex,
MatrixBlock ret,
long numRowsPerBlock,
long rlen,
long clen) |
static void |
RDDConverterUtilsExt.copyRowBlocks(MatrixBlock mb,
long rowIndex,
MatrixBlock ret,
int numRowsPerBlock,
int rlen,
int clen) |
static void |
RDDConverterUtilsExt.copyRowBlocks(MatrixBlock mb,
long rowIndex,
MatrixBlock ret,
long numRowsPerBlock,
long rlen,
long clen) |
static org.apache.spark.api.java.JavaPairRDD<MatrixIndexes,MatrixBlock> |
RDDConverterUtils.csvToBinaryBlock(org.apache.spark.api.java.JavaSparkContext sc,
org.apache.spark.api.java.JavaPairRDD<org.apache.hadoop.io.LongWritable,org.apache.hadoop.io.Text> input,
MatrixCharacteristics mc,
boolean hasHeader,
String delim,
boolean fill,
double fillValue) |
static org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock> |
FrameRDDConverterUtils.csvToBinaryBlock(org.apache.spark.api.java.JavaSparkContext sc,
org.apache.spark.api.java.JavaPairRDD<org.apache.hadoop.io.LongWritable,org.apache.hadoop.io.Text> input,
MatrixCharacteristics mc,
org.apache.sysml.parser.Expression.ValueType[] schema,
boolean hasHeader,
String delim,
boolean fill,
double fillValue) |
static org.apache.spark.api.java.JavaPairRDD<MatrixIndexes,MatrixBlock> |
RDDConverterUtils.csvToBinaryBlock(org.apache.spark.api.java.JavaSparkContext sc,
org.apache.spark.api.java.JavaRDD<String> input,
MatrixCharacteristics mcOut,
boolean hasHeader,
String delim,
boolean fill,
double fillValue)
Example usage:
|
static org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock> |
FrameRDDConverterUtils.csvToBinaryBlock(org.apache.spark.api.java.JavaSparkContext sc,
org.apache.spark.api.java.JavaRDD<String> input,
MatrixCharacteristics mcOut,
org.apache.sysml.parser.Expression.ValueType[] schema,
boolean hasHeader,
String delim,
boolean fill,
double fillValue) |
static org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock> |
FrameRDDConverterUtils.dataFrameToBinaryBlock(org.apache.spark.api.java.JavaSparkContext sc,
org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> df,
MatrixCharacteristics mc,
boolean containsID) |
static org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock> |
FrameRDDConverterUtils.dataFrameToBinaryBlock(org.apache.spark.api.java.JavaSparkContext sc,
org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> df,
MatrixCharacteristics mc,
boolean containsID,
Pair<String[],org.apache.sysml.parser.Expression.ValueType[]> out) |
static String |
SparkUtils.getStartLineFromSparkDebugInfo(String line) |
static void |
RDDConverterUtils.libsvmToBinaryBlock(org.apache.spark.api.java.JavaSparkContext sc,
String pathIn,
String pathX,
String pathY,
MatrixCharacteristics mcOutX)
Converts a libsvm text input file into two binary block matrices for features
and labels, and saves these to the specified output files.
|
static org.apache.spark.api.java.JavaPairRDD<org.apache.hadoop.io.LongWritable,FrameBlock> |
FrameRDDConverterUtils.matrixBlockToBinaryBlock(org.apache.spark.api.java.JavaSparkContext sc,
org.apache.spark.api.java.JavaPairRDD<MatrixIndexes,MatrixBlock> input,
MatrixCharacteristics mcIn) |
static org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock> |
FrameRDDConverterUtils.matrixBlockToBinaryBlockLongIndex(org.apache.spark.api.java.JavaSparkContext sc,
org.apache.spark.api.java.JavaPairRDD<MatrixIndexes,MatrixBlock> input,
MatrixCharacteristics mcIn) |
static void |
RDDConverterUtilsExt.postProcessAfterCopying(MatrixBlock ret) |
static org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> |
RDDConverterUtilsExt.projectColumns(org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> df,
ArrayList<String> columns) |
static org.apache.spark.api.java.JavaPairRDD<MatrixIndexes,MatrixBlock> |
RDDSortUtils.sortDataByValMemSort(org.apache.spark.api.java.JavaPairRDD<MatrixIndexes,MatrixBlock> val,
org.apache.spark.api.java.JavaPairRDD<MatrixIndexes,MatrixBlock> data,
boolean asc,
long rlen,
long clen,
int brlen,
int bclen,
org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext sec,
org.apache.sysml.runtime.matrix.operators.ReorgOperator r_op)
This function collects and sorts value column in memory and then broadcasts it.
|
static org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> |
RDDConverterUtilsExt.stringDataFrameToVectorDataFrame(org.apache.spark.sql.SparkSession sparkSession,
org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> inputDF)
Convert a dataframe of comma-separated string rows to a dataframe of
ml.linalg.Vector rows.
|
static org.apache.spark.api.java.JavaPairRDD<MatrixIndexes,MatrixBlock> |
RDDConverterUtils.textCellToBinaryBlock(org.apache.spark.api.java.JavaSparkContext sc,
org.apache.spark.api.java.JavaPairRDD<org.apache.hadoop.io.LongWritable,org.apache.hadoop.io.Text> input,
MatrixCharacteristics mcOut,
boolean outputEmptyBlocks) |
static org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock> |
FrameRDDConverterUtils.textCellToBinaryBlock(org.apache.spark.api.java.JavaSparkContext sc,
org.apache.spark.api.java.JavaPairRDD<org.apache.hadoop.io.LongWritable,org.apache.hadoop.io.Text> in,
MatrixCharacteristics mcOut,
org.apache.sysml.parser.Expression.ValueType[] schema) |
static org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock> |
FrameRDDConverterUtils.textCellToBinaryBlockLongIndex(org.apache.spark.api.java.JavaSparkContext sc,
org.apache.spark.api.java.JavaPairRDD<Long,org.apache.hadoop.io.Text> input,
MatrixCharacteristics mc,
org.apache.sysml.parser.Expression.ValueType[] schema) |
Modifier and Type | Method and Description |
---|---|
static void |
MatrixCharacteristics.aggregateUnary(MatrixCharacteristics dim,
org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
MatrixCharacteristics dimOut) |
boolean |
JobReturn.checkReturnStatus() |
static void |
MatrixCharacteristics.computeDimension(HashMap<Byte,MatrixCharacteristics> dims,
org.apache.sysml.runtime.instructions.mr.MRInstruction ins) |
static org.apache.sysml.runtime.instructions.mr.MRInstruction |
SortMR.parseSortInstruction(String str) |
static void |
MatrixCharacteristics.reorg(MatrixCharacteristics dim,
org.apache.sysml.runtime.matrix.operators.ReorgOperator op,
MatrixCharacteristics dimOut) |
static JobReturn |
DataPartitionMR.runJob(MRJobInstruction jobinst,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject[] inputMatrices,
String shuffleInst,
byte[] resultIndices,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject[] outputMatrices,
int numReducers,
int replication) |
Constructor and Description |
---|
JobReturn(MatrixCharacteristics[] sts,
OutputInfo[] infos,
boolean success) |
JobReturn(MatrixCharacteristics sts,
OutputInfo info,
boolean success) |
Modifier and Type | Method and Description |
---|---|
static void |
LibMatrixCUDA.abs(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "abs" operation on a matrix on the GPU
|
static void |
LibMatrixCUDA.acos(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "acos" operation on a matrix on the GPU
|
static void |
LibMatrixAgg.aggregateBinaryMatrix(MatrixBlock in,
MatrixBlock aggVal,
org.apache.sysml.runtime.matrix.operators.AggregateOperator aop)
Core incremental matrix aggregate (ak+) as used for uack+ and acrk+.
|
static void |
LibMatrixAgg.aggregateBinaryMatrix(MatrixBlock in,
MatrixBlock aggVal,
MatrixBlock aggCorr)
Core incremental matrix aggregate (ak+) as used in mapmult, tsmm,
cpmm, etc.
|
MatrixValue |
MatrixBlock.aggregateBinaryOperations(MatrixIndexes m1Index,
MatrixValue m1Value,
MatrixIndexes m2Index,
MatrixValue m2Value,
MatrixValue result,
org.apache.sysml.runtime.matrix.operators.AggregateBinaryOperator op) |
abstract MatrixValue |
MatrixValue.aggregateBinaryOperations(MatrixIndexes m1Index,
MatrixValue m1Value,
MatrixIndexes m2Index,
MatrixValue m2Value,
MatrixValue result,
org.apache.sysml.runtime.matrix.operators.AggregateBinaryOperator op) |
MatrixValue |
MatrixCell.aggregateBinaryOperations(MatrixIndexes m1Index,
MatrixValue m1Value,
MatrixIndexes m2Index,
MatrixValue m2Value,
MatrixValue result,
org.apache.sysml.runtime.matrix.operators.AggregateBinaryOperator op) |
MatrixValue |
CM_N_COVCell.aggregateBinaryOperations(MatrixIndexes m1Index,
MatrixValue m1Value,
MatrixIndexes m2Index,
MatrixValue m2Value,
MatrixValue result,
org.apache.sysml.runtime.matrix.operators.AggregateBinaryOperator op) |
MatrixValue |
MatrixBlock.aggregateBinaryOperations(MatrixValue m1Value,
MatrixValue m2Value,
MatrixValue result,
org.apache.sysml.runtime.matrix.operators.AggregateBinaryOperator op) |
abstract MatrixValue |
MatrixValue.aggregateBinaryOperations(MatrixValue m1Value,
MatrixValue m2Value,
MatrixValue result,
org.apache.sysml.runtime.matrix.operators.AggregateBinaryOperator op) |
MatrixValue |
MatrixCell.aggregateBinaryOperations(MatrixValue value1,
MatrixValue value2,
MatrixValue result,
org.apache.sysml.runtime.matrix.operators.AggregateBinaryOperator op) |
MatrixValue |
CM_N_COVCell.aggregateBinaryOperations(MatrixValue m1Value,
MatrixValue m2Value,
MatrixValue result,
org.apache.sysml.runtime.matrix.operators.AggregateBinaryOperator op) |
static void |
LibMatrixOuterAgg.aggregateMatrix(MatrixBlock in1Val,
MatrixBlock outVal,
double[] bv,
int[] bvi,
org.apache.sysml.runtime.matrix.operators.BinaryOperator bOp,
org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator uaggOp) |
static MatrixBlock |
LibMatrixAgg.aggregateTernary(MatrixBlock in1,
MatrixBlock in2,
MatrixBlock in3,
MatrixBlock ret,
org.apache.sysml.runtime.matrix.operators.AggregateTernaryOperator op) |
static MatrixBlock |
LibMatrixAgg.aggregateTernary(MatrixBlock in1,
MatrixBlock in2,
MatrixBlock in3,
MatrixBlock ret,
org.apache.sysml.runtime.matrix.operators.AggregateTernaryOperator op,
int k) |
MatrixBlock |
MatrixBlock.aggregateTernaryOperations(MatrixBlock m1,
MatrixBlock m2,
MatrixBlock m3,
MatrixBlock ret,
org.apache.sysml.runtime.matrix.operators.AggregateTernaryOperator op,
boolean inCP) |
static void |
LibMatrixAgg.aggregateUnaryMatrix(MatrixBlock in,
MatrixBlock out,
org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator uaop) |
static void |
LibMatrixAgg.aggregateUnaryMatrix(MatrixBlock in,
MatrixBlock out,
org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator uaop,
int k) |
MatrixValue |
MatrixBlock.aggregateUnaryOperations(org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
MatrixValue result,
int blockingFactorRow,
int blockingFactorCol,
MatrixIndexes indexesIn) |
MatrixValue |
WeightedCell.aggregateUnaryOperations(org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
MatrixValue result,
int brlen,
int bclen,
MatrixIndexes indexesIn) |
abstract MatrixValue |
MatrixValue.aggregateUnaryOperations(org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
MatrixValue result,
int brlen,
int bclen,
MatrixIndexes indexesIn) |
MatrixValue |
MatrixCell.aggregateUnaryOperations(org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
MatrixValue result,
int brlen,
int bclen,
MatrixIndexes indexesIn) |
MatrixValue |
CM_N_COVCell.aggregateUnaryOperations(org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
MatrixValue result,
int brlen,
int bclen,
MatrixIndexes indexesIn) |
MatrixValue |
MatrixBlock.aggregateUnaryOperations(org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
MatrixValue result,
int blockingFactorRow,
int blockingFactorCol,
MatrixIndexes indexesIn,
boolean inCP) |
abstract MatrixValue |
MatrixValue.aggregateUnaryOperations(org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
MatrixValue result,
int blockingFactorRow,
int blockingFactorCol,
MatrixIndexes indexesIn,
boolean inCP) |
MatrixValue |
MatrixCell.aggregateUnaryOperations(org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
MatrixValue result,
int blockingFactorRow,
int blockingFactorCol,
MatrixIndexes indexesIn,
boolean inCP) |
MatrixValue |
CM_N_COVCell.aggregateUnaryOperations(org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
MatrixValue result,
int blockingFactorRow,
int blockingFactorCol,
MatrixIndexes indexesIn,
boolean inCP) |
void |
MatrixBlock.allocateDenseBlockUnsafe(int rl,
int cl)
This should be called only in the read and write functions for CP
This function should be called before calling any setValueDenseUnsafe()
|
FrameBlock |
FrameBlock.appendOperations(FrameBlock that,
FrameBlock ret,
boolean cbind)
Appends the given argument frameblock 'that' to this frameblock by
creating a deep copy to prevent side effects.
|
MatrixBlock |
MatrixBlock.appendOperations(MatrixBlock[] that,
MatrixBlock ret,
boolean cbind) |
MatrixBlock |
MatrixBlock.appendOperations(MatrixBlock that,
MatrixBlock ret) |
MatrixBlock |
MatrixBlock.appendOperations(MatrixBlock that,
MatrixBlock ret,
boolean cbind) |
void |
MatrixBlock.appendOperations(MatrixValue v2,
ArrayList<org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue> outlist,
int blockRowFactor,
int blockColFactor,
boolean cbind,
boolean m2IsLast,
int nextNCol) |
abstract void |
MatrixValue.appendOperations(MatrixValue valueIn2,
ArrayList<org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue> outlist,
int blockRowFactor,
int blockColFactor,
boolean cbind,
boolean m2IsLast,
int nextNCol) |
void |
MatrixCell.appendOperations(MatrixValue valueIn2,
ArrayList<org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue> outlist,
int blockRowFactor,
int blockColFactor,
boolean cbind,
boolean m2IsLast,
int nextNCol) |
void |
CM_N_COVCell.appendOperations(MatrixValue valueIn2,
ArrayList<org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue> outlist,
int blockRowFactor,
int blockColFactor,
boolean cbind,
boolean m2IsLast,
int nextNCol) |
static void |
LibMatrixCUDA.asin(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "asin" operation on a matrix on the GPU
|
static void |
LibMatrixCUDA.atan(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "atan" operation on a matrix on the GPU
|
static void |
LibMatrixCUDA.axpy(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in2,
String outputName,
double constant)
Performs daxpy operation
|
static void |
LibMatrixCUDA.biasAdd(GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject input,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject bias,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject outputBlock)
Performs the operation corresponding to the DML script:
ones = matrix(1, rows=1, cols=Hout*Wout)
output = input + matrix(bias %*% ones, rows=1, cols=F*Hout*Wout)
This operation is often followed by conv2d and hence we have introduced bias_add(input, bias) built-in function
|
static void |
LibMatrixDNN.biasAdd(MatrixBlock input,
MatrixBlock bias,
MatrixBlock outputBlock,
int numThreads)
Performs the operation corresponding to the DML script:
ones = matrix(1, rows=1, cols=Hout*Wout)
output = input + matrix(bias %*% ones, rows=1, cols=F*Hout*Wout)
This operation is often followed by conv2d and hence we have introduced bias_add(input, bias) built-in function
|
static void |
LibMatrixCUDA.biasMultiply(GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject input,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject bias,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject outputBlock)
Performs the operation corresponding to the DML script:
ones = matrix(1, rows=1, cols=Hout*Wout)
output = input * matrix(bias %*% ones, rows=1, cols=F*Hout*Wout)
This operation is often followed by conv2d and hence we have introduced bias_add(input, bias) built-in function
|
static void |
LibMatrixDNN.biasMultiply(MatrixBlock input,
MatrixBlock bias,
MatrixBlock outputBlock,
int numThreads)
Performs the operation corresponding to the DML script:
ones = matrix(1, rows=1, cols=Hout*Wout)
output = input * matrix(bias %*% ones, rows=1, cols=F*Hout*Wout)
This operation is often followed by conv2d and hence we have introduced bias_multiply(input, bias) built-in function
|
MatrixValue |
MatrixBlock.binaryOperations(org.apache.sysml.runtime.matrix.operators.BinaryOperator op,
MatrixValue thatValue,
MatrixValue result) |
abstract MatrixValue |
MatrixValue.binaryOperations(org.apache.sysml.runtime.matrix.operators.BinaryOperator op,
MatrixValue thatValue,
MatrixValue result) |
MatrixValue |
MatrixCell.binaryOperations(org.apache.sysml.runtime.matrix.operators.BinaryOperator op,
MatrixValue thatValue,
MatrixValue result) |
MatrixValue |
CM_N_COVCell.binaryOperations(org.apache.sysml.runtime.matrix.operators.BinaryOperator op,
MatrixValue thatValue,
MatrixValue result) |
void |
MatrixBlock.binaryOperationsInPlace(org.apache.sysml.runtime.matrix.operators.BinaryOperator op,
MatrixValue thatValue) |
abstract void |
MatrixValue.binaryOperationsInPlace(org.apache.sysml.runtime.matrix.operators.BinaryOperator op,
MatrixValue thatValue) |
void |
MatrixCell.binaryOperationsInPlace(org.apache.sysml.runtime.matrix.operators.BinaryOperator op,
MatrixValue thatValue) |
void |
CM_N_COVCell.binaryOperationsInPlace(org.apache.sysml.runtime.matrix.operators.BinaryOperator op,
MatrixValue thatValue) |
static void |
LibMatrixBincell.bincellOp(MatrixBlock m1,
MatrixBlock m2,
MatrixBlock ret,
org.apache.sysml.runtime.matrix.operators.BinaryOperator op)
matrix-matrix binary operations, MM, MV
|
static void |
LibMatrixBincell.bincellOp(MatrixBlock m1,
MatrixBlock ret,
org.apache.sysml.runtime.matrix.operators.ScalarOperator op)
matrix-scalar, scalar-matrix binary operations.
|
static void |
LibMatrixBincell.bincellOpInPlace(MatrixBlock m1ret,
MatrixBlock m2,
org.apache.sysml.runtime.matrix.operators.BinaryOperator op)
NOTE: operations in place always require m1 and m2 to be of equal dimensions
|
static void |
LibMatrixCUDA.cbind(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in2,
String outputName) |
static void |
LibMatrixCUDA.ceil(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "ceil" operation on a matrix on the GPU
|
MatrixBlock |
MatrixBlock.chainMatrixMultOperations(MatrixBlock v,
MatrixBlock w,
MatrixBlock out,
org.apache.sysml.lops.MapMultChain.ChainType ctype) |
MatrixBlock |
MatrixBlock.chainMatrixMultOperations(MatrixBlock v,
MatrixBlock w,
MatrixBlock out,
org.apache.sysml.lops.MapMultChain.ChainType ctype,
int k) |
static void |
LibMatrixCUDA.channelSums(GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject input,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject outputBlock,
long C,
long HW)
Perform channel_sums operations: out = rowSums(matrix(colSums(A), rows=C, cols=HW))
|
protected static void |
LibMatrixCuDNN.checkStatus(int status)
Convenience method for checking the status of CuDNN kernel.
|
static MatrixPackedCell |
MatrixPackedCell.checkType(MatrixValue cell) |
org.apache.sysml.runtime.instructions.cp.CM_COV_Object |
MatrixBlock.cmOperations(org.apache.sysml.runtime.matrix.operators.CMOperator op) |
org.apache.sysml.runtime.instructions.cp.CM_COV_Object |
MatrixBlock.cmOperations(org.apache.sysml.runtime.matrix.operators.CMOperator op,
MatrixBlock weights) |
static LongStream |
LibMatrixDatagen.computeNNZperBlock(long nrow,
long ncol,
int brlen,
int bclen,
double sparsity) |
static void |
LibMatrixCuDNN.conv2d(GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject image,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject filter,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject outputBlock,
int N,
int C,
int H,
int W,
int K,
int R,
int S,
int pad_h,
int pad_w,
int stride_h,
int stride_w,
int P,
int Q,
double intermediateMemoryBudget)
Performs a 2D convolution
|
static void |
LibMatrixDNN.conv2d(MatrixBlock input,
MatrixBlock filter,
MatrixBlock outputBlock,
ConvolutionParameters params)
This method performs convolution (i.e.
|
static void |
LibMatrixNative.conv2d(MatrixBlock input,
MatrixBlock filter,
MatrixBlock outputBlock,
ConvolutionParameters params)
This method performs convolution (i.e.
|
static void |
LibMatrixCuDNN.conv2dBackwardData(GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject filter,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject dout,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject output,
int N,
int C,
int H,
int W,
int K,
int R,
int S,
int pad_h,
int pad_w,
int stride_h,
int stride_w,
int P,
int Q,
double intermediateMemoryBudget)
This method computes the backpropogation errors for previous layer of convolution operation
|
static void |
LibMatrixDNN.conv2dBackwardData(MatrixBlock filter,
MatrixBlock dout,
MatrixBlock outputBlock,
ConvolutionParameters params)
This method computes the backpropogation errors for previous layer of convolution operation
|
static void |
LibMatrixNative.conv2dBackwardData(MatrixBlock filter,
MatrixBlock dout,
MatrixBlock outputBlock,
ConvolutionParameters params)
This method computes the backpropogation errors for previous layer of convolution operation
|
static void |
LibMatrixCuDNN.conv2dBackwardFilter(GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject image,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject dout,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject outputBlock,
int N,
int C,
int H,
int W,
int K,
int R,
int S,
int pad_h,
int pad_w,
int stride_h,
int stride_w,
int P,
int Q,
double intermediateMemoryBudget)
This method computes the backpropogation errors for filter of convolution operation
|
static void |
LibMatrixDNN.conv2dBackwardFilter(MatrixBlock input,
MatrixBlock dout,
MatrixBlock outputBlock,
ConvolutionParameters params)
This method computes the backpropogation errors for filter of convolution operation
|
static void |
LibMatrixNative.conv2dBackwardFilter(MatrixBlock input,
MatrixBlock dout,
MatrixBlock outputBlock,
ConvolutionParameters params)
This method computes the backpropogation errors for filter of convolution operation
|
static void |
LibMatrixCuDNN.conv2dBiasAdd(GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject image,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject bias,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject filter,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject output,
int N,
int C,
int H,
int W,
int K,
int R,
int S,
int pad_h,
int pad_w,
int stride_h,
int stride_w,
int P,
int Q,
double intermediateMemoryBudget)
Does a 2D convolution followed by a bias_add
|
void |
MatrixBlock.copy(int rl,
int ru,
int cl,
int cu,
MatrixBlock src,
boolean awareDestNZ)
In-place copy of matrix src into the index range of the existing current matrix.
|
static void |
LibMatrixCUDA.cos(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "cos" operation on a matrix on the GPU
|
static void |
LibMatrixCUDA.cosh(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "cosh" operation on a matrix on the GPU
|
org.apache.sysml.runtime.instructions.cp.CM_COV_Object |
MatrixBlock.covOperations(org.apache.sysml.runtime.matrix.operators.COVOperator op,
MatrixBlock that) |
org.apache.sysml.runtime.instructions.cp.CM_COV_Object |
MatrixBlock.covOperations(org.apache.sysml.runtime.matrix.operators.COVOperator op,
MatrixBlock that,
MatrixBlock weights) |
static RandomMatrixGenerator |
LibMatrixDatagen.createRandomMatrixGenerator(String pdfStr,
int r,
int c,
int rpb,
int cpb,
double sp,
double min,
double max,
String distParams) |
static LibMatrixCuDNNConvolutionAlgorithm |
LibMatrixCuDNNConvolutionAlgorithm.cudnnGetConvolutionBackwardDataAlgorithm(GPUContext gCtx,
String instName,
int N,
int C,
int H,
int W,
int K,
int R,
int S,
int pad_h,
int pad_w,
int stride_h,
int stride_w,
int P,
int Q,
long workspaceLimit)
Factory method to get the algorithm wrapper for convolution backward data
|
static LibMatrixCuDNNConvolutionAlgorithm |
LibMatrixCuDNNConvolutionAlgorithm.cudnnGetConvolutionBackwardFilterAlgorithm(GPUContext gCtx,
String instName,
int N,
int C,
int H,
int W,
int K,
int R,
int S,
int pad_h,
int pad_w,
int stride_h,
int stride_w,
int P,
int Q,
long workspaceLimit)
Factory method to get the algorithm wrapper for convolution backward filter
|
static LibMatrixCuDNNConvolutionAlgorithm |
LibMatrixCuDNNConvolutionAlgorithm.cudnnGetConvolutionForwardAlgorithm(GPUContext gCtx,
String instName,
int N,
int C,
int H,
int W,
int K,
int R,
int S,
int pad_h,
int pad_w,
int stride_h,
int stride_w,
int P,
int Q,
long workspaceLimit)
Factory method to get the algorithm wrapper for convolution forward
|
static LibMatrixCuDNNPoolingDescriptors |
LibMatrixCuDNNPoolingDescriptors.cudnnMaxpoolingBackwardDescriptors(GPUContext gCtx,
String instName,
int N,
int C,
int H,
int W,
int K,
int R,
int S,
int pad_h,
int pad_w,
int stride_h,
int stride_w,
int P,
int Q)
Get descriptors for maxpooling backward operation
|
static LibMatrixCuDNNPoolingDescriptors |
LibMatrixCuDNNPoolingDescriptors.cudnnMaxpoolingDescriptors(GPUContext gCtx,
String instName,
int N,
int C,
int H,
int W,
int K,
int R,
int S,
int pad_h,
int pad_w,
int stride_h,
int stride_w,
int P,
int Q)
Get descriptors for maxpooling operation
|
static MatrixBlock |
LibMatrixAgg.cumaggregateUnaryMatrix(MatrixBlock in,
MatrixBlock out,
org.apache.sysml.runtime.matrix.operators.UnaryOperator uop) |
static MatrixBlock |
LibMatrixAgg.cumaggregateUnaryMatrix(MatrixBlock in,
MatrixBlock out,
org.apache.sysml.runtime.matrix.operators.UnaryOperator uop,
int k) |
void |
WeightedCell.denseScalarOperationsInPlace(org.apache.sysml.runtime.matrix.operators.ScalarOperator op) |
void |
MatrixCell.denseScalarOperationsInPlace(org.apache.sysml.runtime.matrix.operators.ScalarOperator op) |
void |
SinglePrecisionCudaSupportFunctions.deviceToHost(GPUContext gCtx,
jcuda.Pointer src,
double[] dest,
String instName,
boolean isEviction) |
void |
DoublePrecisionCudaSupportFunctions.deviceToHost(GPUContext gCtx,
jcuda.Pointer src,
double[] dest,
String instName,
boolean isEviction) |
void |
CudaSupportFunctions.deviceToHost(GPUContext gCtx,
jcuda.Pointer src,
double[] dest,
String instName,
boolean isEviction) |
static MatrixBlock |
LibMatrixReorg.diag(MatrixBlock in,
MatrixBlock out) |
static jcuda.Pointer |
LibMatrixCUDA.double2float(GPUContext gCtx,
jcuda.Pointer A,
jcuda.Pointer ret,
int numElems) |
void |
MatrixBlock.examSparsity() |
void |
MatrixBlock.examSparsity(String opcode)
Evaluates if this matrix block should be in sparse format in
memory.
|
static void |
LibMatrixCUDA.exp(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "exp" operation on a matrix on the GPU
|
static jcuda.Pointer |
LibMatrixCUDA.float2double(GPUContext gCtx,
jcuda.Pointer A,
jcuda.Pointer ret,
int numElems) |
static void |
LibMatrixCUDA.floor(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "floor" operation on a matrix on the GPU
|
static void |
LibMatrixDatagen.generateRandomMatrix(MatrixBlock out,
RandomMatrixGenerator rgen,
LongStream nnzInBlocks,
org.apache.commons.math3.random.Well1024a bigrand,
long bSeed)
Function to generate a matrix of random numbers.
|
static void |
LibMatrixDatagen.generateRandomMatrix(MatrixBlock out,
RandomMatrixGenerator rgen,
LongStream nnzInBlocks,
org.apache.commons.math3.random.Well1024a bigrand,
long bSeed,
int k)
Function to generate a matrix of random numbers.
|
static void |
LibMatrixDatagen.generateSample(MatrixBlock out,
long range,
int size,
boolean replace,
long seed)
Generates a sample of size
size from a range of values [1,range]. |
static void |
LibMatrixDatagen.generateSequence(MatrixBlock out,
double from,
double to,
double incr)
Method to generate a sequence according to the given parameters.
|
static ArrayList<Callable<Long>> |
LibMatrixDNNHelper.getConv2dBackwardDataWorkers(ConvolutionParameters params)
Factory method that returns list of callable tasks for performing conv2d backward data
|
static ArrayList<Callable<Long>> |
LibMatrixDNNHelper.getConv2dBackwardFilterWorkers(ConvolutionParameters params)
Factory method that returns list of callable tasks for performing conv2d backward filter
|
static ArrayList<Callable<Long>> |
LibMatrixDNNHelper.getConv2dWorkers(ConvolutionParameters params)
Factory method that returns list of callable tasks for performing conv2d
|
protected static jcuda.jcublas.cublasHandle |
LibMatrixCUDA.getCublasHandle(GPUContext gCtx) |
protected static JCudaKernels |
LibMatrixCUDA.getCudaKernels(GPUContext gCtx) |
protected static jcuda.jcudnn.cudnnHandle |
LibMatrixCuDNN.getCudnnHandle(GPUContext gCtx) |
protected static jcuda.jcusparse.cusparseHandle |
LibMatrixCUDA.getCusparseHandle(GPUContext gCtx) |
protected static org.apache.sysml.runtime.controlprogram.caching.MatrixObject |
LibMatrixCUDA.getDenseMatrixOutputForGPUInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
String instName,
String name,
long numRows,
long numCols)
Helper method to get the output block (allocated on the GPU)
Also records performance information into
Statistics |
protected static jcuda.Pointer |
LibMatrixCUDA.getDensePointer(GPUContext gCtx,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject input,
String instName)
Convenience method to get jcudaDenseMatrixPtr.
|
protected static jcuda.Pointer |
LibMatrixCuDNN.getDensePointerForCuDNN(GPUContext gCtx,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject image,
String instName)
Convenience method to get jcudaDenseMatrixPtr.
|
static InputInfo |
OutputInfo.getMatchingInputInfo(OutputInfo oi) |
static OutputInfo |
InputInfo.getMatchingOutputInfo(InputInfo ii) |
static ArrayList<Callable<Long>> |
LibMatrixDNNHelper.getMaxPoolingBackwardWorkers(ConvolutionParameters params,
boolean performReluBackward)
Factory method that returns list of callable tasks for performing maxpooling backward operation
|
static ArrayList<Callable<Long>> |
LibMatrixDNNHelper.getMaxPoolingWorkers(ConvolutionParameters params)
Factory method that returns list of callable tasks for performing maxpooling operation
|
jcuda.Pointer |
LibMatrixCuDNNInputRowFetcher.getNthRow(int n)
Copy the nth row and return the dense pointer
|
static ArrayList<Callable<Long>> |
LibMatrixDNNHelper.getReluBackwardWorkers(ConvolutionParameters params)
Factory method that returns list of callable tasks for performing relu backward operation
|
protected static CSRPointer |
LibMatrixCUDA.getSparsePointer(GPUContext gCtx,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject input,
String instName)
Convenience method to get the sparse matrix pointer from a
MatrixObject . |
MatrixBlock |
MatrixBlock.groupedAggOperations(MatrixValue tgt,
MatrixValue wghts,
MatrixValue ret,
int ngroups,
org.apache.sysml.runtime.matrix.operators.Operator op)
Invocation from CP instructions.
|
MatrixBlock |
MatrixBlock.groupedAggOperations(MatrixValue tgt,
MatrixValue wghts,
MatrixValue ret,
int ngroups,
org.apache.sysml.runtime.matrix.operators.Operator op,
int k) |
static void |
LibMatrixAgg.groupedAggregate(MatrixBlock groups,
MatrixBlock target,
MatrixBlock weights,
MatrixBlock result,
int numGroups,
org.apache.sysml.runtime.matrix.operators.Operator op) |
static void |
LibMatrixAgg.groupedAggregate(MatrixBlock groups,
MatrixBlock target,
MatrixBlock weights,
MatrixBlock result,
int numGroups,
org.apache.sysml.runtime.matrix.operators.Operator op,
int k) |
void |
SinglePrecisionCudaSupportFunctions.hostToDevice(GPUContext gCtx,
double[] src,
jcuda.Pointer dest,
String instName) |
void |
DoublePrecisionCudaSupportFunctions.hostToDevice(GPUContext gCtx,
double[] src,
jcuda.Pointer dest,
String instName) |
void |
CudaSupportFunctions.hostToDevice(GPUContext gCtx,
double[] src,
jcuda.Pointer dest,
String instName) |
void |
MatrixPackedCell.incrementalAggregate(org.apache.sysml.runtime.matrix.operators.AggregateOperator aggOp,
MatrixValue newWithCorrection) |
void |
MatrixBlock.incrementalAggregate(org.apache.sysml.runtime.matrix.operators.AggregateOperator aggOp,
MatrixValue newWithCorrection) |
abstract void |
MatrixValue.incrementalAggregate(org.apache.sysml.runtime.matrix.operators.AggregateOperator aggOp,
MatrixValue newWithCorrection) |
void |
MatrixCell.incrementalAggregate(org.apache.sysml.runtime.matrix.operators.AggregateOperator aggOp,
MatrixValue newWithCorrection) |
void |
CM_N_COVCell.incrementalAggregate(org.apache.sysml.runtime.matrix.operators.AggregateOperator aggOp,
MatrixValue newWithCorrection) |
void |
MatrixPackedCell.incrementalAggregate(org.apache.sysml.runtime.matrix.operators.AggregateOperator aggOp,
MatrixValue correction,
MatrixValue newWithCorrection) |
void |
MatrixBlock.incrementalAggregate(org.apache.sysml.runtime.matrix.operators.AggregateOperator aggOp,
MatrixValue correction,
MatrixValue newWithCorrection) |
abstract void |
MatrixValue.incrementalAggregate(org.apache.sysml.runtime.matrix.operators.AggregateOperator aggOp,
MatrixValue correction,
MatrixValue newWithCorrection) |
void |
MatrixCell.incrementalAggregate(org.apache.sysml.runtime.matrix.operators.AggregateOperator aggOp,
MatrixValue correction,
MatrixValue newWithCorrection) |
void |
CM_N_COVCell.incrementalAggregate(org.apache.sysml.runtime.matrix.operators.AggregateOperator aggOp,
MatrixValue correction,
MatrixValue newWithCorrection) |
static void |
OperationsOnMatrixValues.incrementalAggregation(MatrixValue valueAgg,
MatrixValue correction,
MatrixValue valueAdd,
org.apache.sysml.runtime.matrix.operators.AggregateOperator op,
boolean imbededCorrection) |
void |
MatrixBlock.init(double[][] arr,
int r,
int c)
NOTE: This method is designed only for dense representation.
|
void |
MatrixBlock.init(double[] arr,
int r,
int c)
NOTE: This method is designed only for dense representation.
|
void |
RandomMatrixGenerator.init(org.apache.sysml.runtime.matrix.data.RandomMatrixGenerator.PDF pdf,
int r,
int c,
int rpb,
int cpb,
double sp,
double min,
double max)
Initializes internal data structures.
|
void |
RandomMatrixGenerator.init(org.apache.sysml.runtime.matrix.data.RandomMatrixGenerator.PDF pdf,
int r,
int c,
int rpb,
int cpb,
double sp,
double min,
double max,
double mean)
Instantiates a Random number generator with a specific poisson mean
|
static String |
InputInfo.inputInfoToString(InputInfo ii) |
double |
MatrixBlock.interQuartileMean() |
FrameBlock |
FrameBlock.leftIndexingOperations(FrameBlock rhsFrame,
org.apache.sysml.runtime.util.IndexRange ixrange,
FrameBlock ret) |
FrameBlock |
FrameBlock.leftIndexingOperations(FrameBlock rhsFrame,
int rl,
int ru,
int cl,
int cu,
FrameBlock ret) |
MatrixBlock |
MatrixBlock.leftIndexingOperations(MatrixBlock rhsMatrix,
org.apache.sysml.runtime.util.IndexRange ixrange,
MatrixBlock ret,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject.UpdateType update) |
MatrixBlock |
MatrixBlock.leftIndexingOperations(MatrixBlock rhsMatrix,
org.apache.sysml.runtime.util.IndexRange ixrange,
MatrixBlock ret,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject.UpdateType update,
String opcode) |
MatrixBlock |
MatrixBlock.leftIndexingOperations(MatrixBlock rhsMatrix,
int rl,
int ru,
int cl,
int cu,
MatrixBlock ret,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject.UpdateType update) |
MatrixBlock |
MatrixBlock.leftIndexingOperations(MatrixBlock rhsMatrix,
int rl,
int ru,
int cl,
int cu,
MatrixBlock ret,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject.UpdateType update,
String opcode) |
MatrixBlock |
MatrixBlock.leftIndexingOperations(org.apache.sysml.runtime.instructions.cp.ScalarObject scalar,
int rl,
int cl,
MatrixBlock ret,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject.UpdateType update)
Explicitly allow left indexing for scalars.
|
static void |
LibMatrixCUDA.log(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "log" operation on a matrix on the GPU
|
static org.apache.sysml.runtime.controlprogram.caching.MatrixObject |
LibMatrixCuMatMult.matmult(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject left,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject right,
String outputName,
boolean isLeftTransposed,
boolean isRightTransposed)
Matrix multiply on GPU Examines sparsity and shapes and routes call to
appropriate method from cuBLAS or cuSparse C = op(A) x op(B)
The user is expected to call
ec.releaseMatrixOutputForGPUInstruction(outputName);
|
static void |
LibMatrixCUDA.matmultTSMM(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject left,
String outputName,
boolean isLeftTransposed)
Performs tsmm, A %*% A' or A' %*% A, on GPU by exploiting cublasDsyrk(...)
|
static void |
LibMatrixCUDA.matrixMatrixArithmetic(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in2,
String outputName,
boolean isLeftTransposed,
boolean isRightTransposed,
org.apache.sysml.runtime.matrix.operators.BinaryOperator op)
Performs elementwise arithmetic operation specified by op of two input matrices in1 and in2
|
static MatrixBlock |
LibCommonsMath.matrixMatrixOperations(org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in2,
String opcode) |
static void |
LibMatrixCUDA.matrixMatrixRelational(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in2,
String outputName,
org.apache.sysml.runtime.matrix.operators.BinaryOperator op)
Performs elementwise operation relational specified by op of two input matrices in1 and in2
|
static void |
LibMatrixMult.matrixMult(MatrixBlock m1,
MatrixBlock m2,
MatrixBlock ret)
Performs a matrix multiplication and stores the result in the output matrix.
|
static void |
LibMatrixMult.matrixMult(MatrixBlock m1,
MatrixBlock m2,
MatrixBlock ret,
boolean maintainNnz)
This method allows one to disabling exam sparsity.
|
static void |
LibMatrixMult.matrixMult(MatrixBlock m1,
MatrixBlock m2,
MatrixBlock ret,
int k)
Performs a multi-threaded matrix multiplication and stores the result in the output matrix.
|
static void |
LibMatrixNative.matrixMult(MatrixBlock m1,
MatrixBlock m2,
MatrixBlock ret,
int k)
Performs matrix multiplication using native library if BLAS is available or else falls back to
Java BLAS.
|
static void |
LibMatrixNative.matrixMult(MatrixBlock m1,
MatrixBlock m2,
MatrixBlock ret,
int k,
boolean examSparsity) |
static void |
LibMatrixMult.matrixMult(MatrixBlock m1,
MatrixBlock m2,
MatrixBlock ret,
int rl,
int ru) |
static void |
LibMatrixMult.matrixMult(MatrixBlock m1,
MatrixBlock m2,
MatrixBlock ret,
int rl,
int ru,
boolean maintainNnz) |
static void |
LibMatrixMult.matrixMultChain(MatrixBlock mX,
MatrixBlock mV,
MatrixBlock mW,
MatrixBlock ret,
org.apache.sysml.lops.MapMultChain.ChainType ct)
Performs a matrix multiplication chain operation of type t(X)%*%(X%*%v) or t(X)%*%(w*(X%*%v)).
|
static void |
LibMatrixMult.matrixMultChain(MatrixBlock mX,
MatrixBlock mV,
MatrixBlock mW,
MatrixBlock ret,
org.apache.sysml.lops.MapMultChain.ChainType ct,
int k)
Performs a parallel matrix multiplication chain operation of type t(X)%*%(X%*%v) or t(X)%*%(w*(X%*%v)).
|
static void |
LibMatrixMult.matrixMultPermute(MatrixBlock pm1,
MatrixBlock m2,
MatrixBlock ret1,
MatrixBlock ret2) |
static void |
LibMatrixMult.matrixMultPermute(MatrixBlock pm1,
MatrixBlock m2,
MatrixBlock ret1,
MatrixBlock ret2,
int k) |
static void |
LibMatrixMult.matrixMultTransposeSelf(MatrixBlock m1,
MatrixBlock ret,
boolean leftTranspose) |
static void |
LibMatrixMult.matrixMultTransposeSelf(MatrixBlock m1,
MatrixBlock ret,
boolean leftTranspose,
int k) |
static void |
LibMatrixMult.matrixMultWCeMM(MatrixBlock mW,
MatrixBlock mU,
MatrixBlock mV,
double eps,
MatrixBlock ret,
org.apache.sysml.lops.WeightedCrossEntropy.WCeMMType wt) |
static void |
LibMatrixMult.matrixMultWCeMM(MatrixBlock mW,
MatrixBlock mU,
MatrixBlock mV,
double eps,
MatrixBlock ret,
org.apache.sysml.lops.WeightedCrossEntropy.WCeMMType wt,
int k) |
static void |
LibMatrixMult.matrixMultWDivMM(MatrixBlock mW,
MatrixBlock mU,
MatrixBlock mV,
MatrixBlock mX,
MatrixBlock ret,
org.apache.sysml.lops.WeightedDivMM.WDivMMType wt)
NOTE: This operation has limited NaN support, which is acceptable because all our sparse-safe operations
have only limited NaN support.
|
static void |
LibMatrixMult.matrixMultWDivMM(MatrixBlock mW,
MatrixBlock mU,
MatrixBlock mV,
MatrixBlock mX,
MatrixBlock ret,
org.apache.sysml.lops.WeightedDivMM.WDivMMType wt,
int k)
NOTE: This operation has limited NaN support, which is acceptable because all our sparse-safe operations
have only limited NaN support.
|
static void |
LibMatrixMult.matrixMultWSigmoid(MatrixBlock mW,
MatrixBlock mU,
MatrixBlock mV,
MatrixBlock ret,
org.apache.sysml.lops.WeightedSigmoid.WSigmoidType wt) |
static void |
LibMatrixMult.matrixMultWSigmoid(MatrixBlock mW,
MatrixBlock mU,
MatrixBlock mV,
MatrixBlock ret,
org.apache.sysml.lops.WeightedSigmoid.WSigmoidType wt,
int k) |
static void |
LibMatrixMult.matrixMultWSLoss(MatrixBlock mX,
MatrixBlock mU,
MatrixBlock mV,
MatrixBlock mW,
MatrixBlock ret,
org.apache.sysml.lops.WeightedSquaredLoss.WeightsType wt) |
static void |
LibMatrixMult.matrixMultWSLoss(MatrixBlock mX,
MatrixBlock mU,
MatrixBlock mV,
MatrixBlock mW,
MatrixBlock ret,
org.apache.sysml.lops.WeightedSquaredLoss.WeightsType wt,
int k) |
static void |
LibMatrixMult.matrixMultWuMM(MatrixBlock mW,
MatrixBlock mU,
MatrixBlock mV,
MatrixBlock ret,
org.apache.sysml.lops.WeightedUnaryMM.WUMMType wt,
org.apache.sysml.runtime.functionobjects.ValueFunction fn) |
static void |
LibMatrixMult.matrixMultWuMM(MatrixBlock mW,
MatrixBlock mU,
MatrixBlock mV,
MatrixBlock ret,
org.apache.sysml.lops.WeightedUnaryMM.WUMMType wt,
org.apache.sysml.runtime.functionobjects.ValueFunction fn,
int k) |
static void |
LibMatrixCUDA.matrixScalarArithmetic(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in,
String outputName,
boolean isInputTransposed,
org.apache.sysml.runtime.matrix.operators.ScalarOperator op)
Entry point to perform elementwise matrix-scalar arithmetic operation specified by op
|
static void |
LibMatrixCUDA.matrixScalarRelational(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in,
String outputName,
org.apache.sysml.runtime.matrix.operators.ScalarOperator op)
Entry point to perform elementwise matrix-scalar relational operation specified by op
|
double |
MatrixBlock.max()
Wrapper method for reduceall-max of a matrix.
|
static void |
LibMatrixCuDNN.maxpooling(GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject image,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject outputBlock,
int N,
int C,
int H,
int W,
int K,
int R,
int S,
int pad_h,
int pad_w,
int stride_h,
int stride_w,
int P,
int Q,
double intermediateMemoryBudget)
performs maxpooling on GPU by exploiting cudnnPoolingForward(...)
|
static void |
LibMatrixDNN.maxpooling(MatrixBlock input,
MatrixBlock output,
ConvolutionParameters params) |
static void |
LibMatrixCuDNN.maxpoolingBackward(GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject image,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject dout,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject maxpoolOutput,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject outputBlock,
int N,
int C,
int H,
int W,
int K,
int R,
int S,
int pad_h,
int pad_w,
int stride_h,
int stride_w,
int P,
int Q,
double intermediateMemoryBudget)
Performs maxpoolingBackward on GPU by exploiting cudnnPoolingBackward(...)
This method computes the backpropogation errors for previous layer of maxpooling operation
|
static void |
LibMatrixDNN.maxpoolingBackward(MatrixBlock input,
MatrixBlock dout,
MatrixBlock outputBlock,
ConvolutionParameters params,
boolean performReluBackward)
This method computes the backpropogation errors for previous layer of maxpooling operation
|
double |
MatrixBlock.median() |
void |
FrameBlock.merge(org.apache.sysml.runtime.controlprogram.caching.CacheBlock that,
boolean bDummy) |
void |
MatrixBlock.merge(org.apache.sysml.runtime.controlprogram.caching.CacheBlock that,
boolean appendOnly) |
void |
FrameBlock.merge(FrameBlock that) |
void |
MatrixBlock.merge(MatrixBlock that,
boolean appendOnly)
Merge disjoint: merges all non-zero values of the given input into the current
matrix block.
|
double |
MatrixBlock.min()
Wrapper method for reduceall-min of a matrix.
|
double |
MatrixBlock.minNonZero()
Utility function for computing the min non-zero value.
|
static MatrixBlock[] |
LibCommonsMath.multiReturnOperations(org.apache.sysml.runtime.controlprogram.caching.MatrixObject in,
String opcode) |
static String |
OutputInfo.outputInfoToString(OutputInfo oi) |
static void |
OperationsOnMatrixValues.performAggregateBinary(MatrixIndexes indexes1,
MatrixValue value1,
MatrixIndexes indexes2,
MatrixValue value2,
MatrixIndexes indexesOut,
MatrixValue valueOut,
org.apache.sysml.runtime.matrix.operators.AggregateBinaryOperator op) |
static MatrixValue |
OperationsOnMatrixValues.performAggregateBinaryIgnoreIndexes(MatrixValue value1,
MatrixValue value2,
MatrixValue valueOut,
org.apache.sysml.runtime.matrix.operators.AggregateBinaryOperator op) |
static void |
OperationsOnMatrixValues.performAggregateUnary(MatrixIndexes indexesIn,
MatrixValue valueIn,
MatrixIndexes indexesOut,
MatrixValue valueOut,
org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op,
int brlen,
int bclen) |
static void |
OperationsOnMatrixValues.performAppend(MatrixValue valueIn1,
MatrixValue valueIn2,
ArrayList<org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue> outlist,
int blockRowFactor,
int blockColFactor,
boolean cbind,
boolean m2IsLast,
int nextNCol) |
static void |
OperationsOnMatrixValues.performBinaryIgnoreIndexes(MatrixValue value1,
MatrixValue value2,
MatrixValue valueOut,
org.apache.sysml.runtime.matrix.operators.BinaryOperator op) |
static void |
OperationsOnMatrixValues.performMapGroupedAggregate(org.apache.sysml.runtime.matrix.operators.Operator op,
org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue inTarget,
MatrixBlock groups,
int ngroups,
int brlen,
int bclen,
ArrayList<org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue> outlist) |
static void |
OperationsOnMatrixValues.performReorg(MatrixIndexes indexesIn,
MatrixValue valueIn,
MatrixIndexes indexesOut,
MatrixValue valueOut,
org.apache.sysml.runtime.matrix.operators.ReorgOperator op,
int startRow,
int startColumn,
int length) |
static void |
OperationsOnMatrixValues.performScalarIgnoreIndexes(MatrixValue valueIn,
MatrixValue valueOut,
org.apache.sysml.runtime.matrix.operators.ScalarOperator op) |
static void |
OperationsOnMatrixValues.performShift(org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue in,
org.apache.sysml.runtime.util.IndexRange ixrange,
int brlen,
int bclen,
long rlen,
long clen,
ArrayList<org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue> outlist) |
static void |
OperationsOnMatrixValues.performShift(Pair<Long,FrameBlock> in,
org.apache.sysml.runtime.util.IndexRange ixrange,
int brlenLeft,
int clenLeft,
long rlen,
long clen,
ArrayList<Pair<Long,FrameBlock>> outlist) |
static void |
OperationsOnMatrixValues.performSlice(org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue in,
org.apache.sysml.runtime.util.IndexRange ixrange,
int brlen,
int bclen,
ArrayList<org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue> outlist) |
static ArrayList |
OperationsOnMatrixValues.performSlice(org.apache.sysml.runtime.util.IndexRange ixrange,
int brlen,
int bclen,
int iix,
int jix,
org.apache.sysml.runtime.controlprogram.caching.CacheBlock in) |
static ArrayList |
OperationsOnMatrixValues.performSlice(org.apache.sysml.runtime.util.IndexRange ixrange,
int brlen,
int bclen,
int iix,
int jix,
FrameBlock in) |
static ArrayList |
OperationsOnMatrixValues.performSlice(org.apache.sysml.runtime.util.IndexRange ixrange,
int brlen,
int bclen,
int iix,
int jix,
MatrixBlock in) |
static void |
OperationsOnMatrixValues.performSlice(Pair<Long,FrameBlock> in,
org.apache.sysml.runtime.util.IndexRange ixrange,
int brlen,
int bclen,
ArrayList<Pair<Long,FrameBlock>> outlist)
This function will get slice of the input frame block overlapping in overall slice(Range), slice has requested for.
|
static void |
OperationsOnMatrixValues.performTernary(MatrixIndexes indexesIn1,
MatrixValue valueIn1,
double scalarIn2,
boolean left,
int brlen,
CTableMap resultMap,
MatrixBlock resultBlock,
org.apache.sysml.runtime.matrix.operators.Operator op) |
static void |
OperationsOnMatrixValues.performTernary(MatrixIndexes indexesIn1,
MatrixValue valueIn1,
double scalarIn2,
double scalarIn3,
CTableMap resultMap,
MatrixBlock resultBlock,
org.apache.sysml.runtime.matrix.operators.Operator op) |
static void |
OperationsOnMatrixValues.performTernary(MatrixIndexes indexesIn1,
MatrixValue valueIn1,
double scalarIn2,
MatrixIndexes indexesIn3,
MatrixValue valueIn3,
CTableMap resultMap,
MatrixBlock resultBlock,
org.apache.sysml.runtime.matrix.operators.Operator op) |
static void |
OperationsOnMatrixValues.performTernary(MatrixIndexes indexesIn1,
MatrixValue valueIn1,
MatrixIndexes indexesIn2,
MatrixValue valueIn2,
double scalarIn3,
CTableMap resultMap,
MatrixBlock resultBlock,
org.apache.sysml.runtime.matrix.operators.Operator op) |
static void |
OperationsOnMatrixValues.performTernary(MatrixIndexes indexesIn1,
MatrixValue valueIn1,
MatrixIndexes indexesIn2,
MatrixValue valueIn2,
MatrixIndexes indexesIn3,
MatrixValue valueIn3,
CTableMap resultMap,
MatrixBlock resultBlock,
org.apache.sysml.runtime.matrix.operators.Operator op) |
static void |
OperationsOnMatrixValues.performUnaryIgnoreIndexes(MatrixValue valueIn,
MatrixValue valueOut,
org.apache.sysml.runtime.matrix.operators.UnaryOperator op) |
static void |
OperationsOnMatrixValues.performZeroOut(MatrixIndexes indexesIn,
MatrixValue valueIn,
MatrixIndexes indexesOut,
MatrixValue valueOut,
org.apache.sysml.runtime.util.IndexRange range,
boolean complementary) |
void |
MatrixBlock.permutationMatrixMultOperations(MatrixValue m2Val,
MatrixValue out1Val,
MatrixValue out2Val) |
void |
MatrixBlock.permutationMatrixMultOperations(MatrixValue m2Val,
MatrixValue out1Val,
MatrixValue out2Val,
int k) |
double |
MatrixBlock.pickValue(double quantile) |
double |
MatrixBlock.pickValue(double quantile,
boolean average) |
MatrixValue |
MatrixBlock.pickValues(MatrixValue quantiles,
MatrixValue ret) |
static int[] |
LibMatrixOuterAgg.prepareRowIndices(int iCols,
double[] vmb,
org.apache.sysml.runtime.matrix.operators.BinaryOperator bOp,
org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator uaggOp) |
static int[] |
LibMatrixOuterAgg.prepareRowIndicesMax(int iCols,
double[] vmb,
org.apache.sysml.runtime.matrix.operators.BinaryOperator bOp)
This function will return max indices, based on column vector data.
|
static int[] |
LibMatrixOuterAgg.prepareRowIndicesMin(int iCols,
double[] vmb,
org.apache.sysml.runtime.matrix.operators.BinaryOperator bOp)
This function will return min indices, based on column vector data.
|
MatrixValue |
MatrixBlock.quaternaryOperations(org.apache.sysml.runtime.matrix.operators.QuaternaryOperator qop,
MatrixValue um,
MatrixValue vm,
MatrixValue wm,
MatrixValue out) |
abstract MatrixValue |
MatrixValue.quaternaryOperations(org.apache.sysml.runtime.matrix.operators.QuaternaryOperator qop,
MatrixValue um,
MatrixValue vm,
MatrixValue wm,
MatrixValue out) |
MatrixValue |
MatrixCell.quaternaryOperations(org.apache.sysml.runtime.matrix.operators.QuaternaryOperator qop,
MatrixValue um,
MatrixValue vm,
MatrixValue wm,
MatrixValue out) |
MatrixValue |
CM_N_COVCell.quaternaryOperations(org.apache.sysml.runtime.matrix.operators.QuaternaryOperator qop,
MatrixValue um,
MatrixValue vm,
MatrixValue wm,
MatrixValue out) |
MatrixValue |
MatrixBlock.quaternaryOperations(org.apache.sysml.runtime.matrix.operators.QuaternaryOperator qop,
MatrixValue um,
MatrixValue vm,
MatrixValue wm,
MatrixValue out,
int k) |
static MatrixBlock |
MatrixBlock.randOperations(int rows,
int cols,
double sparsity,
double min,
double max,
String pdf,
long seed)
Function to generate the random matrix with specified dimensions (block sizes are not specified).
|
static MatrixBlock |
MatrixBlock.randOperations(int rows,
int cols,
double sparsity,
double min,
double max,
String pdf,
long seed,
int k)
Function to generate the random matrix with specified dimensions (block sizes are not specified).
|
static MatrixBlock |
MatrixBlock.randOperations(RandomMatrixGenerator rgen,
long seed)
Function to generate the random matrix with specified dimensions and block dimensions.
|
static MatrixBlock |
MatrixBlock.randOperations(RandomMatrixGenerator rgen,
long seed,
int k)
Function to generate the random matrix with specified dimensions and block dimensions.
|
MatrixBlock |
MatrixBlock.randOperationsInPlace(RandomMatrixGenerator rgen,
LongStream nnzInBlock,
org.apache.commons.math3.random.Well1024a bigrand,
long bSeed)
Function to generate a matrix of random numbers.
|
MatrixBlock |
MatrixBlock.randOperationsInPlace(RandomMatrixGenerator rgen,
LongStream nnzInBlock,
org.apache.commons.math3.random.Well1024a bigrand,
long bSeed,
int k)
Function to generate a matrix of random numbers.
|
static void |
LibMatrixCUDA.rbind(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in2,
String outputName) |
static void |
LibMatrixCuDNN.relu(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in,
String outputName)
Performs the relu operation on the GPU.
|
static void |
LibMatrixCUDA.reluBackward(GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject input,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject dout,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject outputBlock)
This method computes the backpropagation errors for previous layer of relu operation
|
static void |
LibMatrixDNN.reluBackward(MatrixBlock input,
MatrixBlock dout,
MatrixBlock outputBlock,
int numThreads)
This method computes the backpropagation errors for previous layer of relu operation
|
MatrixBlock |
MatrixBlock.removeEmptyOperations(MatrixBlock ret,
boolean rows) |
MatrixBlock |
MatrixBlock.removeEmptyOperations(MatrixBlock ret,
boolean rows,
MatrixBlock select) |
static MatrixBlock |
LibMatrixReorg.reorg(MatrixBlock in,
MatrixBlock out,
org.apache.sysml.runtime.matrix.operators.ReorgOperator op) |
MatrixValue |
MatrixBlock.reorgOperations(org.apache.sysml.runtime.matrix.operators.ReorgOperator op,
MatrixValue ret,
int startRow,
int startColumn,
int length) |
MatrixValue |
WeightedCell.reorgOperations(org.apache.sysml.runtime.matrix.operators.ReorgOperator op,
MatrixValue result,
int startRow,
int startColumn,
int length) |
abstract MatrixValue |
MatrixValue.reorgOperations(org.apache.sysml.runtime.matrix.operators.ReorgOperator op,
MatrixValue result,
int startRow,
int startColumn,
int length) |
MatrixValue |
MatrixCell.reorgOperations(org.apache.sysml.runtime.matrix.operators.ReorgOperator op,
MatrixValue result,
int startRow,
int startColumn,
int length) |
MatrixValue |
CM_N_COVCell.reorgOperations(org.apache.sysml.runtime.matrix.operators.ReorgOperator op,
MatrixValue result,
int startRow,
int startColumn,
int length) |
MatrixValue |
MatrixBlock.replaceOperations(MatrixValue result,
double pattern,
double replacement) |
abstract MatrixValue |
MatrixValue.replaceOperations(MatrixValue result,
double pattern,
double replacement) |
MatrixValue |
MatrixCell.replaceOperations(MatrixValue result,
double pattern,
double replacement) |
MatrixValue |
CM_N_COVCell.replaceOperations(MatrixValue result,
double pattern,
double replacement) |
abstract void |
MatrixValue.reset(int rl,
int cl,
double v) |
static void |
LibMatrixCUDA.resetFloatingPointPrecision()
Sets the internal state based on the DMLScript.DATA_TYPE
|
static ArrayList<org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue> |
LibMatrixReorg.reshape(org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue in,
MatrixCharacteristics mcIn,
ArrayList<org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue> out,
MatrixCharacteristics mcOut,
boolean rowwise)
MR/SPARK reshape interface - for reshape we cannot view blocks independently, and hence,
there are different CP and MR interfaces.
|
static MatrixBlock |
LibMatrixReorg.reshape(MatrixBlock in,
MatrixBlock out,
int rows,
int cols,
boolean rowwise)
CP reshape operation (single input, single output matrix)
|
static void |
LibMatrixReorg.rev(org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue in,
long rlen,
int brlen,
ArrayList<org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue> out) |
static MatrixBlock |
LibMatrixReorg.rev(MatrixBlock in,
MatrixBlock out) |
static void |
LibMatrixReorg.rexpand(org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue data,
double max,
boolean rows,
boolean cast,
boolean ignore,
long brlen,
long bclen,
ArrayList<org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue> outList)
MR/Spark rexpand operation (single input, multiple outputs incl empty blocks)
|
static MatrixBlock |
LibMatrixReorg.rexpand(MatrixBlock in,
MatrixBlock ret,
double max,
boolean rows,
boolean cast,
boolean ignore,
int k)
CP rexpand operation (single input, single output)
|
MatrixBlock |
MatrixBlock.rexpandOperations(MatrixBlock ret,
double max,
boolean rows,
boolean cast,
boolean ignore,
int k) |
static void |
LibMatrixReorg.rmempty(org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue data,
org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue offset,
boolean rmRows,
long len,
long brlen,
long bclen,
ArrayList<org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue> outList)
MR rmempty interface - for rmempty we cannot view blocks independently, and hence,
there are different CP and MR interfaces.
|
static MatrixBlock |
LibMatrixReorg.rmempty(MatrixBlock in,
MatrixBlock ret,
boolean rows,
MatrixBlock select)
CP rmempty operation (single input, single output matrix)
|
static void |
LibMatrixCUDA.round(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "round" operation on a matrix on the GPU
|
static MatrixBlock |
MatrixBlock.sampleOperations(long range,
int size,
boolean replace,
long seed) |
MatrixValue |
MatrixBlock.scalarOperations(org.apache.sysml.runtime.matrix.operators.ScalarOperator op,
MatrixValue result) |
MatrixValue |
WeightedCell.scalarOperations(org.apache.sysml.runtime.matrix.operators.ScalarOperator op,
MatrixValue result) |
abstract MatrixValue |
MatrixValue.scalarOperations(org.apache.sysml.runtime.matrix.operators.ScalarOperator op,
MatrixValue result) |
MatrixValue |
MatrixCell.scalarOperations(org.apache.sysml.runtime.matrix.operators.ScalarOperator op,
MatrixValue result) |
MatrixValue |
CM_N_COVCell.scalarOperations(org.apache.sysml.runtime.matrix.operators.ScalarOperator op,
MatrixValue result) |
static MatrixBlock |
MatrixBlock.seqOperations(double from,
double to,
double incr)
Method to generate a sequence according to the given parameters.
|
MatrixBlock |
MatrixBlock.seqOperationsInPlace(double from,
double to,
double incr) |
void |
ConvolutionParameters.setIfUnknown(org.apache.sysml.hops.Hop N,
org.apache.sysml.hops.Hop C,
org.apache.sysml.hops.Hop H,
org.apache.sysml.hops.Hop W,
org.apache.sysml.hops.Hop K,
org.apache.sysml.hops.Hop R,
org.apache.sysml.hops.Hop S,
org.apache.sysml.hops.Hop stride_h,
org.apache.sysml.hops.Hop stride_w,
org.apache.sysml.hops.Hop pad_h,
org.apache.sysml.hops.Hop pad_w,
int numThreads) |
protected void |
RandomMatrixGenerator.setupValuePRNG() |
static void |
LibMatrixCUDA.sigmoid(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "sigmoid" operation on a matrix on the GPU
|
static void |
LibMatrixCUDA.sign(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "sign" operation on a matrix on the GPU
|
static void |
LibMatrixCUDA.sin(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "sin" operation on a matrix on the GPU
|
static void |
LibMatrixCUDA.sinh(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "sinh" operation on a matrix on the GPU
|
protected static void |
LibMatrixCUDA.sliceDenseDense(GPUContext gCtx,
String instName,
jcuda.Pointer inPointer,
jcuda.Pointer outPointer,
int rl,
int ru,
int cl,
int cu,
int inClen)
Perform slice operation on dense input and output it in dense format
|
abstract void |
MatrixValue.sliceOperations(ArrayList<org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue> outlist,
org.apache.sysml.runtime.util.IndexRange range,
int rowCut,
int colCut,
int blockRowFactor,
int blockColFactor,
int boundaryRlen,
int boundaryClen) |
void |
MatrixCell.sliceOperations(ArrayList<org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue> outlist,
org.apache.sysml.runtime.util.IndexRange range,
int rowCut,
int colCut,
int blockRowFactor,
int blockColFactor,
int boundaryRlen,
int boundaryClen) |
void |
CM_N_COVCell.sliceOperations(ArrayList<org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue> outlist,
org.apache.sysml.runtime.util.IndexRange range,
int rowCut,
int colCut,
int blockRowFactor,
int blockColFactor,
int boundaryRlen,
int boundaryClen) |
static void |
LibMatrixCUDA.sliceOperations(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
org.apache.sysml.runtime.util.IndexRange ixrange,
String outputName)
Method to perform rightIndex operation for a given lower and upper bounds in row and column dimensions.
|
FrameBlock |
FrameBlock.sliceOperations(org.apache.sysml.runtime.util.IndexRange ixrange,
FrameBlock ret) |
MatrixBlock |
MatrixBlock.sliceOperations(org.apache.sysml.runtime.util.IndexRange ixrange,
MatrixBlock ret) |
MatrixBlock |
MatrixBlock.sliceOperations(int rl,
int ru,
int cl,
int cu,
boolean deep,
org.apache.sysml.runtime.controlprogram.caching.CacheBlock ret)
Method to perform rightIndex operation for a given lower and upper bounds in row and column dimensions.
|
FrameBlock |
FrameBlock.sliceOperations(int rl,
int ru,
int cl,
int cu,
org.apache.sysml.runtime.controlprogram.caching.CacheBlock retCache)
Right indexing operations to slice a subframe out of this frame block.
|
MatrixBlock |
MatrixBlock.sliceOperations(int rl,
int ru,
int cl,
int cu,
org.apache.sysml.runtime.controlprogram.caching.CacheBlock ret) |
protected static void |
LibMatrixCUDA.sliceSparseDense(GPUContext gCtx,
String instName,
CSRPointer inPointer,
jcuda.Pointer outPointer,
int rl,
int ru,
int cl,
int cu,
int inClen)
Perform slice operation on sparse input and output it in dense format
|
static void |
LibMatrixCuDNN.softmax(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "softmax" operation on a matrix on the GPU
|
static void |
LibMatrixCUDA.solve(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in2,
String outputName)
Implements the "solve" function for systemml Ax = B (A is of size m*n, B is of size m*1, x is of size n*1)
|
static MatrixBlock |
LibMatrixReorg.sort(MatrixBlock in,
MatrixBlock out,
int[] by,
boolean desc,
boolean ixret) |
MatrixValue |
MatrixBlock.sortOperations(MatrixValue weights,
MatrixValue result) |
void |
WeightedCell.sparseScalarOperationsInPlace(org.apache.sysml.runtime.matrix.operators.ScalarOperator op) |
void |
MatrixCell.sparseScalarOperationsInPlace(org.apache.sysml.runtime.matrix.operators.ScalarOperator op) |
void |
MatrixBlock.sparseToDense() |
void |
WeightedCell.sparseUnaryOperationsInPlace(org.apache.sysml.runtime.matrix.operators.UnaryOperator op) |
void |
MatrixCell.sparseUnaryOperationsInPlace(org.apache.sysml.runtime.matrix.operators.UnaryOperator op) |
static void |
LibMatrixCUDA.sqrt(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "sqrt" operation on a matrix on the GPU
|
static void |
OperationsOnMatrixValues.startAggregation(MatrixValue valueOut,
MatrixValue correction,
org.apache.sysml.runtime.matrix.operators.AggregateOperator op,
int rlen,
int clen,
boolean sparseHint,
boolean imbededCorrection) |
double |
MatrixBlock.sum()
Wrapper method for reduceall-sum of a matrix.
|
double |
MatrixBlock.sumSq()
Wrapper method for reduceall-sumSq of a matrix.
|
double |
MatrixBlock.sumWeightForQuantile()
In a given two column matrix, the second column denotes weights.
|
static void |
LibMatrixCUDA.tan(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "tan" operation on a matrix on the GPU
|
static void |
LibMatrixCUDA.tanh(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String outputName)
Performs an "tanh" operation on a matrix on the GPU
|
void |
MatrixBlock.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
double scalarThat,
double scalarThat2,
CTableMap resultMap,
MatrixBlock resultBlock)
D = ctable(A,v2,w)
this <- A; scalar_that <- v2; scalar_that2 <- w; result <- D
(i1,j1,v1) from input1 (this)
(v2) from sclar_input2 (scalarThat)
(w) from scalar_input3 (scalarThat2)
|
abstract void |
MatrixValue.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
double scalar_that,
double scalar_that2,
CTableMap resultMap,
MatrixBlock resultBlock) |
void |
MatrixCell.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
double scalarThat,
double scalarThat2,
CTableMap resultMap,
MatrixBlock resultBlock) |
void |
CM_N_COVCell.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
double scalarThat,
double scalarThat2,
CTableMap resultMap,
MatrixBlock resultBlock) |
void |
MatrixBlock.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
double scalarThat,
MatrixValue that2Val,
CTableMap resultMap,
MatrixBlock resultBlock)
D = ctable(A,v2,W)
this <- A; scalarThat <- v2; that2 <- W; result <- D
(i1,j1,v1) from input1 (this)
(v2) from sclar_input2 (scalarThat)
(i3,j3,w) from input3 (that2)
|
abstract void |
MatrixValue.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
double scalarThat,
MatrixValue that2,
CTableMap ctableResult,
MatrixBlock ctableResultBlock) |
void |
MatrixCell.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
double scalarThat,
MatrixValue that2,
CTableMap resultMap,
MatrixBlock resultBlock) |
void |
CM_N_COVCell.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
double scalarThat,
MatrixValue that2,
CTableMap resultMap,
MatrixBlock resultBlock) |
void |
MatrixBlock.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixIndexes ix1,
double scalarThat,
boolean left,
int brlen,
CTableMap resultMap,
MatrixBlock resultBlock)
Specific ctable case of ctable(seq(...),X), where X is the only
matrix input.
|
abstract void |
MatrixValue.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixIndexes ix1,
double scalar_that,
boolean left,
int brlen,
CTableMap resultMap,
MatrixBlock resultBlock) |
void |
MatrixCell.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixIndexes ix1,
double scalarThat,
boolean left,
int brlen,
CTableMap resultMap,
MatrixBlock resultBlock) |
void |
CM_N_COVCell.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixIndexes ix1,
double scalarThat,
boolean left,
int brlen,
CTableMap resultMap,
MatrixBlock resultBlock) |
void |
MatrixBlock.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixValue thatVal,
double scalarThat2,
boolean ignoreZeros,
CTableMap resultMap,
MatrixBlock resultBlock)
D = ctable(A,B,w)
this <- A; that <- B; scalar_that2 <- w; result <- D
(i1,j1,v1) from input1 (this)
(i1,j1,v2) from input2 (that)
(w) from scalar_input3 (scalarThat2)
NOTE: This method supports both vectors and matrices.
|
abstract void |
MatrixValue.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixValue that,
double scalar_that2,
boolean ignoreZeros,
CTableMap resultMap,
MatrixBlock resultBlock) |
void |
MatrixCell.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixValue that,
double scalarThat2,
boolean ignoreZeros,
CTableMap ctableResult,
MatrixBlock ctableResultBlock) |
void |
CM_N_COVCell.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixValue that,
double scalarThat2,
boolean ignoreZeros,
CTableMap resultMap,
MatrixBlock resultBlock) |
void |
MatrixBlock.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixValue thatMatrix,
double thatScalar,
MatrixBlock resultBlock)
D = ctable(seq,A,w)
this <- seq; thatMatrix <- A; thatScalar <- w; result <- D
(i1,j1,v1) from input1 (this)
(i1,j1,v2) from input2 (that)
(w) from scalar_input3 (scalarThat2)
|
void |
MatrixBlock.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixValue thatVal,
MatrixValue that2Val,
CTableMap resultMap)
D = ctable(A,B,W)
this <- A; that <- B; that2 <- W; result <- D
(i1,j1,v1) from input1 (this)
(i1,j1,v2) from input2 (that)
(i1,j1,w) from input3 (that2)
|
void |
MatrixBlock.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixValue thatVal,
MatrixValue that2Val,
CTableMap resultMap,
MatrixBlock resultBlock) |
abstract void |
MatrixValue.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixValue that,
MatrixValue that2,
CTableMap resultMap,
MatrixBlock resultBlock) |
void |
MatrixCell.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixValue that,
MatrixValue that2,
CTableMap resultMap,
MatrixBlock resultBlock) |
void |
CM_N_COVCell.ternaryOperations(org.apache.sysml.runtime.matrix.operators.Operator op,
MatrixValue that,
MatrixValue that2,
CTableMap resultMap,
MatrixBlock resultBlock) |
static int |
LibMatrixCUDA.toInt(long num) |
static void |
LibMatrixCUDA.transpose(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in,
String outputName)
Transposes the input matrix using cublasDgeam
|
static MatrixBlock |
LibMatrixReorg.transpose(MatrixBlock in,
MatrixBlock out) |
static MatrixBlock |
LibMatrixReorg.transpose(MatrixBlock in,
MatrixBlock out,
int k) |
MatrixBlock |
MatrixBlock.transposeSelfMatrixMultOperations(MatrixBlock out,
org.apache.sysml.lops.MMTSJ.MMTSJType tstype) |
MatrixBlock |
MatrixBlock.transposeSelfMatrixMultOperations(MatrixBlock out,
org.apache.sysml.lops.MMTSJ.MMTSJType tstype,
int k) |
MatrixBlock |
MatrixBlock.uaggouterchainOperations(MatrixBlock mbLeft,
MatrixBlock mbRight,
MatrixBlock mbOut,
org.apache.sysml.runtime.matrix.operators.BinaryOperator bOp,
org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator uaggOp) |
static void |
LibMatrixCUDA.unaryAggregate(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec,
GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject in1,
String output,
org.apache.sysml.runtime.matrix.operators.AggregateUnaryOperator op)
Entry point to perform Unary aggregate operations on the GPU.
|
static MatrixBlock |
LibCommonsMath.unaryOperations(org.apache.sysml.runtime.controlprogram.caching.MatrixObject inj,
String opcode) |
MatrixValue |
MatrixBlock.unaryOperations(org.apache.sysml.runtime.matrix.operators.UnaryOperator op,
MatrixValue result) |
MatrixValue |
WeightedCell.unaryOperations(org.apache.sysml.runtime.matrix.operators.UnaryOperator op,
MatrixValue result) |
abstract MatrixValue |
MatrixValue.unaryOperations(org.apache.sysml.runtime.matrix.operators.UnaryOperator op,
MatrixValue result) |
MatrixValue |
MatrixCell.unaryOperations(org.apache.sysml.runtime.matrix.operators.UnaryOperator op,
MatrixValue result) |
MatrixValue |
CM_N_COVCell.unaryOperations(org.apache.sysml.runtime.matrix.operators.UnaryOperator op,
MatrixValue result) |
void |
MatrixBlock.unaryOperationsInPlace(org.apache.sysml.runtime.matrix.operators.UnaryOperator op) |
void |
WeightedCell.unaryOperationsInPlace(org.apache.sysml.runtime.matrix.operators.UnaryOperator op) |
abstract void |
MatrixValue.unaryOperationsInPlace(org.apache.sysml.runtime.matrix.operators.UnaryOperator op) |
void |
MatrixCell.unaryOperationsInPlace(org.apache.sysml.runtime.matrix.operators.UnaryOperator op) |
void |
CM_N_COVCell.unaryOperationsInPlace(org.apache.sysml.runtime.matrix.operators.UnaryOperator op) |
FrameBlock |
FrameBlock.zeroOutOperations(FrameBlock result,
org.apache.sysml.runtime.util.IndexRange range,
boolean complementary,
int iRowStartSrc,
int iRowStartDest,
int brlen,
int iMaxRowsToCopy)
This function ZERO OUT the data in the slicing window applicable for this block.
|
MatrixValue |
MatrixBlock.zeroOutOperations(MatrixValue result,
org.apache.sysml.runtime.util.IndexRange range,
boolean complementary) |
abstract MatrixValue |
MatrixValue.zeroOutOperations(MatrixValue result,
org.apache.sysml.runtime.util.IndexRange range,
boolean complementary) |
MatrixValue |
MatrixCell.zeroOutOperations(MatrixValue result,
org.apache.sysml.runtime.util.IndexRange range,
boolean complementary) |
MatrixValue |
CM_N_COVCell.zeroOutOperations(MatrixValue result,
org.apache.sysml.runtime.util.IndexRange range,
boolean complementary) |
Constructor and Description |
---|
ConvolutionParameters(long N,
long C,
long H,
long W,
long K,
long R,
long S,
long stride_h,
long stride_w,
long pad_h,
long pad_w,
int numThreads) |
LibMatrixCuDNNInputRowFetcher(GPUContext gCtx,
String instName,
org.apache.sysml.runtime.controlprogram.caching.MatrixObject image)
Initialize the input fetcher
|
RandomMatrixGenerator(org.apache.sysml.runtime.matrix.data.RandomMatrixGenerator.PDF pdf,
int r,
int c,
int rpb,
int cpb,
double sp)
Instantiates a Random number generator
|
RandomMatrixGenerator(org.apache.sysml.runtime.matrix.data.RandomMatrixGenerator.PDF pdf,
int r,
int c,
int rpb,
int cpb,
double sp,
double min,
double max)
Instantiates a Random number generator
|
RandomMatrixGenerator(org.apache.sysml.runtime.matrix.data.RandomMatrixGenerator.PDF pdf,
int r,
int c,
int rpb,
int cpb,
double sp,
double min,
double max,
double mean)
Instantiates a Random number generator with a specific poisson mean
|
RandomMatrixGenerator(String pdfStr,
int r,
int c,
int rpb,
int cpb,
double sp,
double min,
double max)
Instantiates a Random number generator
|
Modifier and Type | Method and Description |
---|---|
double[][] |
Matrix.getMatrixAsDoubleArray()
Method to get matrix as double array.
|
void |
ExternalFunctionInvocationInstruction.processInstruction(org.apache.sysml.runtime.controlprogram.context.ExecutionContext ec) |
void |
Matrix.setMatrixDoubleArray(double[] data)
Method to set matrix as double array.
|
void |
Matrix.setMatrixDoubleArray(double[][] data)
Method to set matrix as double array.
|
Copyright © 2017 The Apache Software Foundation. All rights reserved.