Package org.apache.sysds.runtime.matrix.data

Class LibMatrixCuMatMult

java.lang.Object

org.apache.sysds.runtime.matrix.data.LibMatrixCUDA

org.apache.sysds.runtime.matrix.data.LibMatrixCuMatMult

public class LibMatrixCuMatMult
extends LibMatrixCUDA

Field Summary

Fields inherited from class org.apache.sysds.runtime.matrix.data.LibMatrixCUDA

cudaSupportFunctions, customKernelSuffix, sizeOfDataType

Constructor Summary

Constructors

Constructor	Description
LibMatrixCuMatMult()

Method Summary

Modifier and Type	Method	Description
static MatrixObject	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 inherited from class org.apache.sysds.runtime.matrix.data.LibMatrixCUDA

abs, acos, asin, atan, axpy, biasAdd, biasMultiply, cbind, ceil, channelSums, computeNNZ, cos, cosh, cumulativeScan, cumulativeSumProduct, denseTranspose, deviceCopy, double2float, exp, float2double, floor, getCudaKernels, getDenseMatrixOutputForGPUInstruction, getDenseMatrixOutputForGPUInstruction, getDensePointer, getNnz, isInSparseFormat, log, matmultTSMM, matrixMatrixArithmetic, matrixMatrixRelational, matrixScalarArithmetic, matrixScalarOp, matrixScalarRelational, one, rbind, reluBackward, resetFloatingPointPrecision, round, sigmoid, sign, sin, sinh, sliceOperations, solve, sqrt, tan, tanh, toInt, transpose, unaryAggregate, zero

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

LibMatrixCuMatMult

public LibMatrixCuMatMult()

Method Details

matmult

public static MatrixObject 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);

Parameters:

ec - Current ExecutionContext instance

gCtx - a valid GPUContext

instName - name of the invoking instruction to recordStatistics.

left - Matrix A

right - Matrix B

outputName - Name of the output matrix C (in code generated after LOP layer)

isLeftTransposed - op for A, transposed or not

isRightTransposed - op for B, tranposed or not

Returns:

output of matrix multiply