## Uses of Class
org.apache.sysds.runtime.instructions.gpu.context.GPUContext

Packages that use GPUContext
org.apache.sysds.runtime.controlprogram.caching
org.apache.sysds.runtime.controlprogram.context
org.apache.sysds.runtime.instructions.gpu.context
org.apache.sysds.runtime.lineage
org.apache.sysds.runtime.matrix.data

### Uses of GPUContext in org.apache.sysds.runtime.controlprogram.caching

Methods in org.apache.sysds.runtime.controlprogram.caching with parameters of type GPUContext
`GPUObject` CacheableData.`getGPUObject​(GPUContext gCtx)`
`void` CacheableData.`removeGPUObject​(GPUContext gCtx)`
`void` CacheableData.`setGPUObject​(GPUContext gCtx, GPUObject gObj)`

### Uses of GPUContext in org.apache.sysds.runtime.controlprogram.context

Methods in org.apache.sysds.runtime.controlprogram.context that return GPUContext
`GPUContext` ExecutionContext.`getGPUContext​(int index)` Get the i-th GPUContext

Methods in org.apache.sysds.runtime.controlprogram.context that return types with arguments of type GPUContext
`List<GPUContext>` ExecutionContext.`getGPUContexts()` Gets the list of GPUContexts

Method parameters in org.apache.sysds.runtime.controlprogram.context with type arguments of type GPUContext
`void` ExecutionContext.`setGPUContexts​(List<GPUContext> gpuContexts)` Sets the list of GPUContexts

### Uses of GPUContext in org.apache.sysds.runtime.instructions.gpu.context

Methods in org.apache.sysds.runtime.instructions.gpu.context that return types with arguments of type GPUContext
`static List<GPUContext>` GPUContextPool.`reserveAllGPUContexts()` Reserves and gets an initialized list of GPUContexts

Methods in org.apache.sysds.runtime.instructions.gpu.context with parameters of type GPUContext
`static CSRPointer` CSRPointer.`allocateEmpty​(GPUContext gCtx, long nnz2, long rows)`
`static CSRPointer` CSRPointer.`allocateEmpty​(GPUContext gCtx, long nnz2, long rows, boolean initialize)` 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.
`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.
`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
`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

Constructors in org.apache.sysds.runtime.instructions.gpu.context with parameters of type GPUContext
`GPUMemoryManager​(GPUContext gpuCtx)`
`GPUObject​(GPUContext gCtx, MatrixObject mat, jcuda.Pointer ptr)`
`GPUObject​(GPUContext gCtx, GPUObject that, MatrixObject mat)`

### Uses of GPUContext in org.apache.sysds.runtime.lineage

Methods in org.apache.sysds.runtime.lineage with parameters of type GPUContext
`static void` LineageGPUCacheEviction.`setGPUContext​(GPUContext gpuCtx)`

### Uses of GPUContext in org.apache.sysds.runtime.matrix.data

Methods in org.apache.sysds.runtime.matrix.data with parameters of type GPUContext
`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 int` LibMatrixCUDA.`computeNNZ​(GPUContext gCtx, jcuda.Pointer densePtr, int length)` Utility to compute number of non-zeroes on the GPU
`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 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.`cudnnPoolingBackwardDescriptors​(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, LibMatrixDNN.PoolingType poolingType)` Get descriptors for maxpooling backward operation
`static LibMatrixCuDNNPoolingDescriptors` LibMatrixCuDNNPoolingDescriptors.`cudnnPoolingDescriptors​(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, LibMatrixDNN.PoolingType poolingType)` Get descriptors for maxpooling operation
`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.`denseTranspose​(ExecutionContext ec, GPUContext gCtx, String instName, jcuda.Pointer A, jcuda.Pointer C, long numRowsA, long numColsA)` Computes C = t(A)
`void` CudaSupportFunctions.`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` SinglePrecisionCudaSupportFunctions.`deviceToHost​(GPUContext gCtx, jcuda.Pointer src, double[] dest, String instName, boolean isEviction)`
`static jcuda.Pointer` LibMatrixCUDA.`double2float​(GPUContext gCtx, jcuda.Pointer A, jcuda.Pointer ret, int numElems)`
`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 jcuda.Pointer` LibMatrixCUDA.`float2double​(GPUContext gCtx, jcuda.Pointer A, jcuda.Pointer ret, int numElems)`
`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 JCudaKernels` LibMatrixCUDA.`getCudaKernels​(GPUContext gCtx)`
`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.
`void` CudaSupportFunctions.`hostToDevice​(GPUContext gCtx, double[] src, jcuda.Pointer dest, String instName)`
`void` DoublePrecisionCudaSupportFunctions.`hostToDevice​(GPUContext gCtx, double[] src, jcuda.Pointer dest, String instName)`
`void` SinglePrecisionCudaSupportFunctions.`hostToDevice​(GPUContext gCtx, double[] src, jcuda.Pointer dest, String instName)`
`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 void` LibMatrixCuDNN.`lstm​(ExecutionContext ec, GPUContext gCtx, String instName, jcuda.Pointer X, jcuda.Pointer wPointer, jcuda.Pointer out0, jcuda.Pointer c0, boolean return_sequences, String outputName, String cyName, int N, int M, int D, int T)` Computes the forward pass for an LSTM layer with M neurons.
`static void` LibMatrixCuDNN.`lstmBackward​(ExecutionContext ec, GPUContext gCtx, String instName, jcuda.Pointer x, jcuda.Pointer hx, jcuda.Pointer cx, jcuda.Pointer wPointer, String doutName, String dcyName, String dxName, String dwName, String dbName, String dhxName, String dcxName, boolean return_sequences, int N, int M, int D, int T)`

`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 GPUContext
`LibMatrixCuDNNInputRowFetcher​(GPUContext gCtx, String instName, MatrixObject image)` Initialize the input fetcher
`LibMatrixCuDNNRnnAlgorithm​(ExecutionContext ec, GPUContext gCtx, String instName, String rnnMode, int N, int T, int M, int D, boolean isTraining, jcuda.Pointer w)`