Uses of Class
org.apache.sysds.runtime.controlprogram.caching.MatrixObject

Packages that use MatrixObject

Package	Description
org.apache.sysds.api.mlcontext
org.apache.sysds.hops.rewrite
org.apache.sysds.runtime.controlprogram.caching
org.apache.sysds.runtime.controlprogram.context
org.apache.sysds.runtime.controlprogram.paramserv
org.apache.sysds.runtime.controlprogram.paramserv.dp
org.apache.sysds.runtime.controlprogram.parfor
org.apache.sysds.runtime.controlprogram.parfor.opt
org.apache.sysds.runtime.instructions.fed
org.apache.sysds.runtime.instructions.gpu.context
org.apache.sysds.runtime.matrix.data

Uses of MatrixObject in org.apache.sysds.api.mlcontext

Methods in org.apache.sysds.api.mlcontext that return MatrixObject

Modifier and Type	Method and Description
static MatrixObject	MLContextConversionUtil.binaryBlocksToMatrixObject(org.apache.spark.api.java.JavaPairRDD<MatrixIndexes,MatrixBlock> binaryBlocks) Convert a JavaPairRDD<MatrixIndexes, MatrixBlock> to a MatrixObject.
static MatrixObject	MLContextConversionUtil.binaryBlocksToMatrixObject(org.apache.spark.api.java.JavaPairRDD<MatrixIndexes,MatrixBlock> binaryBlocks, MatrixMetadata matrixMetadata) Convert a JavaPairRDD<MatrixIndexes, MatrixBlock> to a MatrixObject.
static MatrixObject	MLContextConversionUtil.dataFrameToMatrixObject(org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> dataFrame) Convert a DataFrame to a MatrixObject.
static MatrixObject	MLContextConversionUtil.dataFrameToMatrixObject(org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> dataFrame, MatrixMetadata matrixMetadata) Convert a DataFrame to a MatrixObject.
static MatrixObject	MLContextConversionUtil.doubleMatrixToMatrixObject(String variableName, double[][] doubleMatrix) Convert a two-dimensional double array to a MatrixObject.
static MatrixObject	MLContextConversionUtil.doubleMatrixToMatrixObject(String variableName, double[][] doubleMatrix, MatrixMetadata matrixMetadata) Convert a two-dimensional double array to a MatrixObject.
MatrixObject	MLResults.getMatrixObject(String outputName) Obtain an output as a MatrixObject
static MatrixObject	MLContextConversionUtil.javaRDDStringCSVToMatrixObject(org.apache.spark.api.java.JavaRDD<String> javaRDD) Convert a JavaRDD<String> in CSV format to a MatrixObject
static MatrixObject	MLContextConversionUtil.javaRDDStringCSVToMatrixObject(org.apache.spark.api.java.JavaRDD<String> javaRDD, MatrixMetadata matrixMetadata) Convert a JavaRDD<String> in CSV format to a MatrixObject
static MatrixObject	MLContextConversionUtil.javaRDDStringIJVToMatrixObject(org.apache.spark.api.java.JavaRDD<String> javaRDD, MatrixMetadata matrixMetadata) Convert a JavaRDD<String> in IJV format to a MatrixObject .
static MatrixObject	MLContextConversionUtil.matrixBlockToMatrixObject(String variableName, MatrixBlock matrixBlock, MatrixMetadata matrixMetadata) Convert a MatrixBlock to a MatrixObject.
static MatrixObject	MLContextConversionUtil.rddStringCSVToMatrixObject(org.apache.spark.rdd.RDD<String> rdd) Convert a RDD<String> in CSV format to a MatrixObject
static MatrixObject	MLContextConversionUtil.rddStringCSVToMatrixObject(org.apache.spark.rdd.RDD<String> rdd, MatrixMetadata matrixMetadata) Convert a RDD<String> in CSV format to a MatrixObject
static MatrixObject	MLContextConversionUtil.rddStringIJVToMatrixObject(org.apache.spark.rdd.RDD<String> rdd, MatrixMetadata matrixMetadata) Convert a RDD<String> in IJV format to a MatrixObject.
MatrixObject	Matrix.toMatrixObject() Obtain the matrix as a SystemDS MatrixObject.
static MatrixObject	MLContextConversionUtil.urlToMatrixObject(URL url, MatrixMetadata matrixMetadata) Convert a matrix at a URL to a MatrixObject.

Methods in org.apache.sysds.api.mlcontext with parameters of type MatrixObject

Modifier and Type	Method and Description
static double[][]	MLContextConversionUtil.matrixObjectTo2DDoubleArray(MatrixObject matrixObject) Convert a MatrixObject to a two-dimensional double array.
static org.apache.spark.api.java.JavaPairRDD<MatrixIndexes,MatrixBlock>	MLContextConversionUtil.matrixObjectToBinaryBlocks(MatrixObject matrixObject, SparkExecutionContext sparkExecutionContext) Convert a MatrixObject to a JavaPairRDD<MatrixIndexes, MatrixBlock>.
static org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>	MLContextConversionUtil.matrixObjectToDataFrame(MatrixObject matrixObject, SparkExecutionContext sparkExecutionContext, boolean isVectorDF) Convert a MatrixObject to a DataFrame.
static org.apache.spark.api.java.JavaRDD<String>	MLContextConversionUtil.matrixObjectToJavaRDDStringCSV(MatrixObject matrixObject) Convert a MatrixObject to a JavaRDD<String> in CSV format.
static org.apache.spark.api.java.JavaRDD<String>	MLContextConversionUtil.matrixObjectToJavaRDDStringIJV(MatrixObject matrixObject) Convert a MatrixObject to a JavaRDD<String> in IJV format.
static List<String>	MLContextConversionUtil.matrixObjectToListStringCSV(MatrixObject matrixObject) Convert a MatrixObject to a List<String> in CSV format.
static List<String>	MLContextConversionUtil.matrixObjectToListStringIJV(MatrixObject matrixObject) Convert a MatrixObject to a List<String> in IJV format.
static org.apache.spark.rdd.RDD<String>	MLContextConversionUtil.matrixObjectToRDDStringCSV(MatrixObject matrixObject) Convert a MatrixObject to a RDD<String> in CSV format.
static org.apache.spark.rdd.RDD<String>	MLContextConversionUtil.matrixObjectToRDDStringIJV(MatrixObject matrixObject) Convert a MatrixObject to a RDD<String> in IJV format.

Constructors in org.apache.sysds.api.mlcontext with parameters of type MatrixObject

Constructor and Description
Matrix(MatrixObject matrixObject, SparkExecutionContext sparkExecutionContext)

Uses of MatrixObject in org.apache.sysds.hops.rewrite

Methods in org.apache.sysds.hops.rewrite with parameters of type MatrixObject

Modifier and Type	Method and Description
static void	HopRewriteUtils.copyLineNumbers(MatrixObject mo, Hop tread)
static DataOp	HopRewriteUtils.createTransientRead(String name, MatrixObject mo)

Uses of MatrixObject in org.apache.sysds.runtime.controlprogram.caching

Constructors in org.apache.sysds.runtime.controlprogram.caching with parameters of type MatrixObject

Constructor and Description
MatrixObject(MatrixObject mo) Copy constructor that copies meta data but NO data.

Uses of MatrixObject in org.apache.sysds.runtime.controlprogram.context

Methods in org.apache.sysds.runtime.controlprogram.context that return MatrixObject

Modifier and Type	Method and Description
MatrixObject	ExecutionContext.allocateGPUMatrixObject(String varName, long numRows, long numCols) Allocates the GPUObject for a given LOPS Variable (eg.
static MatrixObject	ExecutionContext.createMatrixObject(MatrixBlock mb)
MatrixObject	ExecutionContext.getMatrixInputForGPUInstruction(String varName, String opcode)
MatrixObject	ExecutionContext.getMatrixObject(CPOperand input)
MatrixObject	ExecutionContext.getMatrixObject(String varname)

Methods in org.apache.sysds.runtime.controlprogram.context that return types with arguments of type MatrixObject

Modifier and Type	Method and Description
Pair<MatrixObject,Boolean>	ExecutionContext.getDenseMatrixOutputForGPUInstruction(String varName, long numRows, long numCols) Allocates a dense matrix on the GPU (for output)
Pair<MatrixObject,Boolean>	ExecutionContext.getSparseMatrixOutputForGPUInstruction(String varName, long numRows, long numCols, long nnz) Allocates a sparse matrix in CSR format on the GPU.

Methods in org.apache.sysds.runtime.controlprogram.context with parameters of type MatrixObject

Modifier and Type	Method and Description
PartitionedBroadcast<MatrixBlock>	SparkExecutionContext.getBroadcastForMatrixObject(MatrixObject mo)
org.apache.spark.api.java.JavaPairRDD<?,?>	SparkExecutionContext.getRDDHandleForMatrixObject(MatrixObject mo, Types.FileFormat fmt)
org.apache.spark.api.java.JavaPairRDD<?,?>	SparkExecutionContext.getRDDHandleForMatrixObject(MatrixObject mo, Types.FileFormat fmt, int numParts, boolean inclEmpty)

Uses of MatrixObject in org.apache.sysds.runtime.controlprogram.paramserv

Methods in org.apache.sysds.runtime.controlprogram.paramserv that return MatrixObject

Modifier and Type	Method and Description
static MatrixObject	ParamservUtils.createShallowCopy(MatrixObject mo)
MatrixObject	PSWorker.getFeatures()
MatrixObject	PSWorker.getLabels()
static MatrixObject	ParamservUtils.newMatrixObject(MatrixBlock mb)
static MatrixObject	ParamservUtils.newMatrixObject(MatrixBlock mb, boolean cleanup)
static MatrixObject	ParamservUtils.sliceMatrix(MatrixObject mo, long rl, long rh) Slice the matrix

Methods in org.apache.sysds.runtime.controlprogram.paramserv with parameters of type MatrixObject

Modifier and Type	Method and Description
static MatrixObject	ParamservUtils.createShallowCopy(MatrixObject mo)
static org.apache.spark.api.java.JavaPairRDD<Integer,scala.Tuple2<MatrixBlock,MatrixBlock>>	ParamservUtils.doPartitionOnSpark(SparkExecutionContext sec, MatrixObject features, MatrixObject labels, Statement.PSScheme scheme, int workerNum)
void	PSWorker.setFeatures(MatrixObject features)
void	PSWorker.setLabels(MatrixObject labels)
static MatrixObject	ParamservUtils.sliceMatrix(MatrixObject mo, long rl, long rh) Slice the matrix

Uses of MatrixObject in org.apache.sysds.runtime.controlprogram.paramserv.dp

Fields in org.apache.sysds.runtime.controlprogram.paramserv.dp with type parameters of type MatrixObject

Modifier and Type	Field and Description
List<MatrixObject>	DataPartitionLocalScheme.Result.pFeatures
List<MatrixObject>	DataPartitionLocalScheme.Result.pLabels

Constructor parameters in org.apache.sysds.runtime.controlprogram.paramserv.dp with type arguments of type MatrixObject

Constructor and Description
Result(List<MatrixObject> pFeatures, List<MatrixObject> pLabels)
Result(List<MatrixObject> pFeatures, List<MatrixObject> pLabels)

Uses of MatrixObject in org.apache.sysds.runtime.controlprogram.parfor

Methods in org.apache.sysds.runtime.controlprogram.parfor that return MatrixObject

Modifier and Type	Method and Description
MatrixObject	DataPartitioner.createPartitionedMatrixObject(MatrixObject in, MatrixObject out, boolean force) Creates a partitioned matrix object based on the given input matrix object, according to the specified split format.
MatrixObject	DataPartitioner.createPartitionedMatrixObject(MatrixObject in, String fnameNew)
MatrixObject	DataPartitioner.createPartitionedMatrixObject(MatrixObject in, String fnameNew, boolean force)
MatrixObject	ResultMergeRemoteSparkWCompare.executeParallelMerge(int par)
MatrixObject	ResultMergeRemoteSpark.executeParallelMerge(int par)
MatrixObject	ResultMergeLocalAutomatic.executeParallelMerge(int par)
abstract MatrixObject	ResultMerge.executeParallelMerge(int par) Merge all given input matrices in parallel into the given output matrix.
MatrixObject	ResultMergeLocalFile.executeParallelMerge(int par)
MatrixObject	ResultMergeLocalMemory.executeParallelMerge(int par)
MatrixObject	ResultMergeRemoteSparkWCompare.executeSerialMerge()
MatrixObject	ResultMergeRemoteSpark.executeSerialMerge()
MatrixObject	ResultMergeLocalAutomatic.executeSerialMerge()
abstract MatrixObject	ResultMerge.executeSerialMerge() Merge all given input matrices sequentially into the given output matrix.
MatrixObject	ResultMergeLocalFile.executeSerialMerge()
MatrixObject	ResultMergeLocalMemory.executeSerialMerge()

Methods in org.apache.sysds.runtime.controlprogram.parfor with parameters of type MatrixObject

Modifier and Type	Method and Description
MatrixObject	DataPartitioner.createPartitionedMatrixObject(MatrixObject in, MatrixObject out, boolean force) Creates a partitioned matrix object based on the given input matrix object, according to the specified split format.
MatrixObject	DataPartitioner.createPartitionedMatrixObject(MatrixObject in, String fnameNew)
MatrixObject	DataPartitioner.createPartitionedMatrixObject(MatrixObject in, String fnameNew, boolean force)
static RemoteParForJobReturn	RemoteDPParForSpark.runJob(long pfid, String itervar, String matrixvar, String program, HashMap<String,byte[]> clsMap, String resultFile, MatrixObject input, ExecutionContext ec, ParForProgramBlock.PartitionFormat dpf, Types.FileFormat fmt, boolean tSparseCol, boolean enableCPCaching, int numReducers)

Constructors in org.apache.sysds.runtime.controlprogram.parfor with parameters of type MatrixObject

Constructor and Description
ResultMerge(MatrixObject out, MatrixObject[] in, String outputFilename, boolean accum)
ResultMerge(MatrixObject out, MatrixObject[] in, String outputFilename, boolean accum)
ResultMergeLocalAutomatic(MatrixObject out, MatrixObject[] in, String outputFilename, boolean accum)
ResultMergeLocalAutomatic(MatrixObject out, MatrixObject[] in, String outputFilename, boolean accum)
ResultMergeLocalFile(MatrixObject out, MatrixObject[] in, String outputFilename, boolean accum)
ResultMergeLocalFile(MatrixObject out, MatrixObject[] in, String outputFilename, boolean accum)
ResultMergeLocalMemory(MatrixObject out, MatrixObject[] in, String outputFilename, boolean accum)
ResultMergeLocalMemory(MatrixObject out, MatrixObject[] in, String outputFilename, boolean accum)
ResultMergeRemoteSpark(MatrixObject out, MatrixObject[] in, String outputFilename, boolean accum, ExecutionContext ec, int numMappers, int numReducers)
ResultMergeRemoteSpark(MatrixObject out, MatrixObject[] in, String outputFilename, boolean accum, ExecutionContext ec, int numMappers, int numReducers)

Uses of MatrixObject in org.apache.sysds.runtime.controlprogram.parfor.opt

Methods in org.apache.sysds.runtime.controlprogram.parfor.opt with parameters of type MatrixObject

Modifier and Type	Method and Description
static boolean	OptimizerRuleBased.allowsBinaryCellPartitions(MatrixObject mo, ParForProgramBlock.PartitionFormat dpf)

Uses of MatrixObject in org.apache.sysds.runtime.instructions.fed

Methods in org.apache.sysds.runtime.instructions.fed with parameters of type MatrixObject

Modifier and Type	Method and Description
static void	MultiReturnParameterizedBuiltinFEDInstruction.encodeFederatedFrames(FederationMap fedMapping, Encoder globalEncoder, MatrixObject transformedMat)
void	InitFEDInstruction.federateMatrix(MatrixObject output, List<org.apache.commons.lang3.tuple.Pair<FederatedRange,FederatedData>> workers)

Uses of MatrixObject in org.apache.sysds.runtime.instructions.gpu.context

Methods in org.apache.sysds.runtime.instructions.gpu.context with parameters of type MatrixObject

Modifier and Type	Method and Description
GPUObject	GPUContext.createGPUObject(MatrixObject mo) Instantiates a new GPUObject initialized with the given MatrixObject.

Uses of MatrixObject in org.apache.sysds.runtime.matrix.data

Methods in org.apache.sysds.runtime.matrix.data that return MatrixObject

Modifier and Type	Method and Description
static MatrixObject	LibMatrixCUDA.getDenseMatrixOutputForGPUInstruction(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
static MatrixObject	LibMatrixCuMatMult.matmult(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject left, 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);

Methods in org.apache.sysds.runtime.matrix.data with parameters of type MatrixObject

Modifier and Type	Method and Description
static void	LibMatrixCUDA.abs(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "abs" operation on a matrix on the GPU
static void	LibMatrixCUDA.acos(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "acos" operation on a matrix on the GPU
static void	LibMatrixCUDA.asin(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "asin" operation on a matrix on the GPU
static void	LibMatrixCUDA.atan(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "atan" operation on a matrix on the GPU
static void	LibMatrixCUDA.axpy(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, MatrixObject in2, String outputName, double constant) Performs daxpy operation
static void	LibMatrixCuDNN.batchNormalizationBackward(GPUContext gCtx, String instName, MatrixObject image, MatrixObject dout, MatrixObject scale, MatrixObject dX, MatrixObject dScale, MatrixObject dBias, double epsilon, MatrixObject resultSaveMean, MatrixObject resultSaveInvVariance) This method computes the backpropagation errors for image, scale and bias of batch normalization layer
static void	LibMatrixCuDNN.batchNormalizationForwardInference(GPUContext gCtx, String instName, MatrixObject image, MatrixObject scale, MatrixObject bias, MatrixObject runningMean, MatrixObject runningVar, MatrixObject ret, double epsilon) Performs the forward BatchNormalization layer computation for inference
static void	LibMatrixCuDNN.batchNormalizationForwardTraining(GPUContext gCtx, String instName, MatrixObject image, MatrixObject scale, MatrixObject bias, MatrixObject runningMean, MatrixObject runningVar, MatrixObject ret, MatrixObject retRunningMean, MatrixObject retRunningVar, double epsilon, double exponentialAverageFactor, MatrixObject resultSaveMean, MatrixObject resultSaveInvVariance) Performs the forward BatchNormalization layer computation for training
static void	LibMatrixCUDA.biasAdd(GPUContext gCtx, String instName, MatrixObject input, MatrixObject bias, 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	LibMatrixCUDA.biasMultiply(GPUContext gCtx, String instName, MatrixObject input, MatrixObject bias, 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	LibMatrixCUDA.cbind(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, MatrixObject in2, String outputName)
static void	LibMatrixCUDA.ceil(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "ceil" operation on a matrix on the GPU
static void	LibMatrixCUDA.channelSums(GPUContext gCtx, String instName, MatrixObject input, MatrixObject outputBlock, long C, long HW) Perform channel_sums operations: out = rowSums(matrix(colSums(A), rows=C, cols=HW))
static void	LibMatrixCuDNN.conv2d(GPUContext gCtx, String instName, MatrixObject image, MatrixObject filter, 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	LibMatrixCuDNN.conv2dBackwardData(GPUContext gCtx, String instName, MatrixObject filter, MatrixObject dout, 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	LibMatrixCuDNN.conv2dBackwardFilter(GPUContext gCtx, String instName, MatrixObject image, MatrixObject dout, 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	LibMatrixCuDNN.conv2dBiasAdd(GPUContext gCtx, String instName, MatrixObject image, MatrixObject bias, MatrixObject filter, 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
static void	LibMatrixCUDA.cos(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "cos" operation on a matrix on the GPU
static void	LibMatrixCUDA.cosh(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "cosh" operation on a matrix on the GPU
static void	LibMatrixCUDA.cumulativeScan(ExecutionContext ec, GPUContext gCtx, String instName, String kernelFunction, MatrixObject in, String outputName) Cumulative scan
static void	LibMatrixCUDA.cumulativeSumProduct(ExecutionContext ec, GPUContext gCtx, String instName, String kernelFunction, MatrixObject in, String outputName) Cumulative sum-product kernel cascade invokation
static void	LibMatrixCUDA.exp(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "exp" operation on a matrix on the GPU
static void	LibMatrixCUDA.floor(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "floor" operation on a matrix on the GPU
static jcuda.Pointer	LibMatrixCUDA.getDensePointer(GPUContext gCtx, MatrixObject input, String instName) Convenience method to get jcudaDenseMatrixPtr.
static jcuda.Pointer	LibMatrixCuDNN.getDensePointerForCuDNN(GPUContext gCtx, MatrixObject image, String instName, int numRows, int numCols) Convenience method to get jcudaDenseMatrixPtr.
static long	LibMatrixCUDA.getNnz(GPUContext gCtx, String instName, MatrixObject mo, boolean recomputeDenseNNZ) Note: if the matrix is in dense format, it explicitly re-computes the number of nonzeros.
static boolean	LibMatrixCUDA.isInSparseFormat(GPUContext gCtx, MatrixObject mo)
static void	LibMatrixCUDA.log(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "log" operation on a matrix on the GPU
static MatrixObject	LibMatrixCuMatMult.matmult(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject left, 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(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject left, String outputName, boolean isLeftTransposed) Performs tsmm, A %*% A' or A' %*% A, on GPU by exploiting cublasDsyrk(...)
static void	LibMatrixCUDA.matrixMatrixArithmetic(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, MatrixObject in2, String outputName, boolean isLeftTransposed, boolean isRightTransposed, BinaryOperator op) Performs elementwise arithmetic operation specified by op of two input matrices in1 and in2
static void	LibMatrixCUDA.matrixMatrixRelational(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, MatrixObject in2, String outputName, BinaryOperator op) Performs elementwise operation relational specified by op of two input matrices in1 and in2
static void	LibMatrixCUDA.matrixScalarArithmetic(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in, String outputName, boolean isInputTransposed, ScalarOperator op) Entry point to perform elementwise matrix-scalar arithmetic operation specified by op
static void	LibMatrixCUDA.matrixScalarOp(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in, String outputName, boolean isInputTransposed, ScalarOperator op) Utility to do matrix-scalar operation kernel
static void	LibMatrixCUDA.matrixScalarRelational(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in, String outputName, ScalarOperator op) Entry point to perform elementwise matrix-scalar relational operation specified by op
static void	LibMatrixCuDNN.pooling(GPUContext gCtx, String instName, MatrixObject image, 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, LibMatrixDNN.PoolingType poolingType, double intermediateMemoryBudget) performs maxpooling on GPU by exploiting cudnnPoolingForward(...)
static void	LibMatrixCuDNN.poolingBackward(GPUContext gCtx, String instName, MatrixObject image, MatrixObject dout, MatrixObject maxpoolOutput, 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, LibMatrixDNN.PoolingType poolingType, double intermediateMemoryBudget) Performs maxpoolingBackward on GPU by exploiting cudnnPoolingBackward(...) This method computes the backpropogation errors for previous layer of maxpooling operation
static void	LibMatrixCUDA.rbind(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, MatrixObject in2, String outputName)
static void	LibMatrixCuDNN.relu(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in, String outputName) Performs the relu operation on the GPU.
static void	LibMatrixCUDA.reluBackward(GPUContext gCtx, String instName, MatrixObject input, MatrixObject dout, MatrixObject outputBlock) This method computes the backpropagation errors for previous layer of relu operation
static void	LibMatrixCUDA.round(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "round" operation on a matrix on the GPU
static void	LibMatrixCUDA.sigmoid(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "sigmoid" operation on a matrix on the GPU
static void	LibMatrixCUDA.sign(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "sign" operation on a matrix on the GPU
static void	LibMatrixCUDA.sin(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "sin" operation on a matrix on the GPU
static void	LibMatrixCUDA.sinh(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "sinh" operation on a matrix on the GPU
static void	LibMatrixCUDA.sliceOperations(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, IndexRange ixrange, String outputName) Method to perform rightIndex operation for a given lower and upper bounds in row and column dimensions.
static void	LibMatrixCuDNN.softmax(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "softmax" operation on a matrix on the GPU
static void	LibMatrixCUDA.solve(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, MatrixObject in2, String outputName) Implements the "solve" function for systemds Ax = B (A is of size m*n, B is of size m*1, x is of size n*1)
static void	LibMatrixCUDA.sqrt(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "sqrt" operation on a matrix on the GPU
static void	LibMatrixCUDA.tan(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "tan" operation on a matrix on the GPU
static void	LibMatrixCUDA.tanh(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName) Performs an "tanh" operation on a matrix on the GPU
static void	LibMatrixCUDA.transpose(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in, String outputName) Transposes the input matrix using cublasDgeam
static void	LibMatrixCUDA.unaryAggregate(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String output, AggregateUnaryOperator op) Entry point to perform Unary aggregate operations on the GPU.

Constructors in org.apache.sysds.runtime.matrix.data with parameters of type MatrixObject

Constructor and Description
LibMatrixCuDNNInputRowFetcher(GPUContext gCtx, String instName, MatrixObject image) Initialize the input fetcher