org.apache.sysds.runtime.matrix.data

## Class LibMatrixCUDA

- java.lang.Object
- - org.apache.sysds.runtime.matrix.data.LibMatrixCUDA

- Direct Known Subclasses:
    LibMatrixCuDNN, LibMatrixCuDNNInputRowFetcher, LibMatrixCuMatMult

      public class LibMatrixCUDA
      extends Object

  All CUDA kernels and library calls are redirected through this class
  See Also:
    `GPUContext`, `GPUObject`

- - ### Field Summary

    Fields
    Modifier and Type | Field and Description
    --- | ---
    `static CudaSupportFunctions` | `cudaSupportFunctions`
    `static String` | `customKernelSuffix`
    `static int` | `sizeOfDataType`

  - ### Constructor Summary

    Constructors
    Constructor and Description
    `LibMatrixCUDA()`

  - ### Method Summary

    All Methods Static Methods Concrete Methods
    Modifier and Type | Method and Description
    --- | ---
    `static void` | `abs(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName)` Performs an "abs" operation on a matrix on the GPU
    `static void` | `acos(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName)` Performs an "acos" operation on a matrix on the GPU
    `static void` | `asin(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName)` Performs an "asin" operation on a matrix on the GPU
    `static void` | `atan(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName)` Performs an "atan" operation on a matrix on the GPU
    `static void` | `axpy(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, MatrixObject in2, String outputName, double constant)` Performs daxpy operation
    `static void` | `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` | `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` | `cbind(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, MatrixObject in2, String outputName)`
    `static void` | `ceil(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName)` Performs an "ceil" operation on a matrix on the GPU
    `static void` | `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` | `computeNNZ(GPUContext gCtx, jcuda.Pointer densePtr, int length)` Utility to compute number of non-zeroes on the GPU
    `static void` | `cos(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName)` Performs an "cos" operation on a matrix on the GPU
    `static void` | `cosh(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName)` Performs an "cosh" operation on a matrix on the GPU
    `static void` | `cumulativeScan(ExecutionContext ec, GPUContext gCtx, String instName, String kernelFunction, MatrixObject in, String outputName)` Cumulative scan
    `static void` | `cumulativeSumProduct(ExecutionContext ec, GPUContext gCtx, String instName, String kernelFunction, MatrixObject in, String outputName)` Cumulative sum-product kernel cascade invokation
    `static void` | `denseTranspose(ExecutionContext ec, GPUContext gCtx, String instName, jcuda.Pointer A, jcuda.Pointer C, long numRowsA, long numColsA)` Computes C = t(A)
    `static void` | `deviceCopy(String instName, jcuda.Pointer src, jcuda.Pointer dest, int rlen, int clen)` Performs a deep copy of input device double pointer corresponding to matrix
    `static jcuda.Pointer` | `double2float(GPUContext gCtx, jcuda.Pointer A, jcuda.Pointer ret, int numElems)`
    `static void` | `exp(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName)` Performs an "exp" operation on a matrix on the GPU
    `static jcuda.Pointer` | `float2double(GPUContext gCtx, jcuda.Pointer A, jcuda.Pointer ret, int numElems)`
    `static void` | `floor(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName)` Performs an "floor" operation on a matrix on the GPU
    `static JCudaKernels` | `getCudaKernels(GPUContext gCtx)`
    `static MatrixObject` | `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 jcuda.Pointer` | `getDensePointer(GPUContext gCtx, MatrixObject input, String instName)` Convenience method to get jcudaDenseMatrixPtr.
    `static long` | `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` | `isInSparseFormat(GPUContext gCtx, MatrixObject mo)`
    `static void` | `log(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName)` Performs an "log" operation on a matrix on the GPU
    `static void` | `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` | `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` | `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` | `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` | `matrixScalarOp(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in, String outputName, boolean isInputTransposed, ScalarOperator op)` Utility to do matrix-scalar operation kernel
    `static void` | `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 jcuda.Pointer` | `one()` Convenience method to get a pointer to value '1.0' on device.
    `static void` | `rbind(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, MatrixObject in2, String outputName)`
    `static void` | `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` | `resetFloatingPointPrecision()` Sets the internal state based on the DMLScript.DATA_TYPE
    `static void` | `round(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName)` Performs an "round" operation on a matrix on the GPU
    `static void` | `sigmoid(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName)` Performs an "sigmoid" operation on a matrix on the GPU
    `static void` | `sign(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName)` Performs an "sign" operation on a matrix on the GPU
    `static void` | `sin(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName)` Performs an "sin" operation on a matrix on the GPU
    `static void` | `sinh(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName)` Performs an "sinh" operation on a matrix on the GPU
    `static void` | `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` | `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` | `sqrt(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName)` Performs an "sqrt" operation on a matrix on the GPU
    `static void` | `tan(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName)` Performs an "tan" operation on a matrix on the GPU
    `static void` | `tanh(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String outputName)` Performs an "tanh" operation on a matrix on the GPU
    `static int` | `toInt(long num)`
    `static void` | `transpose(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in, String outputName)` Transposes the input matrix using cublasDgeam
    `static void` | `unaryAggregate(ExecutionContext ec, GPUContext gCtx, String instName, MatrixObject in1, String output, AggregateUnaryOperator op)` Entry point to perform Unary aggregate operations on the GPU.
    `static jcuda.Pointer` | `zero()` Convenience method to get a pointer to value '0.0f' on device.

    - ### Methods inherited from class java.lang.Object

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

- - ### Field Detail

    - #### cudaSupportFunctions

          public static CudaSupportFunctions cudaSupportFunctions

    - #### sizeOfDataType

          public static int sizeOfDataType

    - #### customKernelSuffix

          public static String customKernelSuffix

  - ### Constructor Detail

    - #### LibMatrixCUDA

          public LibMatrixCUDA()

  - ### Method Detail

    - #### resetFloatingPointPrecision

          public static void resetFloatingPointPrecision()

      Sets the internal state based on the DMLScript.DATA_TYPE

    - #### isInSparseFormat

          public static boolean isInSparseFormat(GPUContext gCtx,
                                                 MatrixObject mo)

    - #### getNnz

          public static long 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.
      Parameters:
        `gCtx` - a valid GPU context
        `instName` - instruction name
        `mo` - matrix object
        `recomputeDenseNNZ` - recompute NNZ if dense
      Returns:
        number of non-zeroes

    - #### getCudaKernels

          public static JCudaKernels getCudaKernels(GPUContext gCtx)
                                             throws DMLRuntimeException

      Throws:
        `DMLRuntimeException`

    - #### double2float

          public static jcuda.Pointer double2float(GPUContext gCtx,
                                                   jcuda.Pointer A,
                                                   jcuda.Pointer ret,
                                                   int numElems)

    - #### float2double

          public static jcuda.Pointer float2double(GPUContext gCtx,
                                                   jcuda.Pointer A,
                                                   jcuda.Pointer ret,
                                                   int numElems)

    - #### one

          public static jcuda.Pointer one()

      Convenience method to get a pointer to value '1.0' on device. Instead of allocating and deallocating it for every kernel invocation.
      Returns:
        jcuda pointer

    - #### zero

          public static jcuda.Pointer zero()

      Convenience method to get a pointer to value '0.0f' on device. Instead of allocating and deallocating it for every kernel invocation.
      Returns:
        jcuda pointer

    - #### getDensePointer

          public static jcuda.Pointer getDensePointer(GPUContext gCtx,
                                                      MatrixObject input,
                                                      String instName)
                                               throws DMLRuntimeException

      Convenience method to get jcudaDenseMatrixPtr. This method explicitly converts sparse to dense format, so use it judiciously.
      Parameters:
        `gCtx` - a valid `GPUContext`
        `input` - input matrix object
        `instName` - the invoking instruction's name for record `Statistics`.
      Returns:
        jcuda pointer
      Throws:
        `DMLRuntimeException`

    - #### reluBackward

          public static void reluBackward(GPUContext gCtx,
                                          String instName,
                                          MatrixObject input,
                                          MatrixObject dout,
                                          MatrixObject outputBlock)

      This method computes the backpropagation errors for previous layer of relu operation
      Parameters:
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `input` - input image
        `dout` - next layer error propogation
        `outputBlock` - output

    - #### channelSums

          public static void 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))
      Parameters:
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `input` - input image
        `outputBlock` - output
        `C` - number of channels
        `HW` - height*width

    - #### biasMultiply

          public static void 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
      Parameters:
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `input` - input image
        `bias` - bias
        `outputBlock` - output

    - #### biasAdd

          public static void 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
      Parameters:
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `input` - input image
        `bias` - bias
        `outputBlock` - output

    - #### matmultTSMM

          public static void 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(...)

      Memory Usage - If dense, input space - rows * cols, no intermediate memory, output - Max(rows*rows, cols*cols) If sparse, calls matmult

      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `left` - input matrix, as in a tsmm expression like A %*% A' or A' %*% A, we just need to check whether the left one is transposed or not, I named it 'left'
        `outputName` - output matrix name
        `isLeftTransposed` - if true, left transposed

    - #### unaryAggregate

          public static void unaryAggregate(ExecutionContext ec,
                                            GPUContext gCtx,
                                            String instName,
                                            MatrixObject in1,
                                            String output,
                                            AggregateUnaryOperator op)

      Entry point to perform Unary aggregate operations on the GPU. The execution context object is used to allocate memory for the GPU.
      Parameters:
        `ec` - Instance of `ExecutionContext`, from which the output variable will be allocated
        `gCtx` - a valid `GPUContext`
        `instName` - name of the invoking instruction to record`Statistics`.
        `in1` - input matrix
        `output` - output matrix/scalar name
        `op` - Instance of `AggregateUnaryOperator` which encapsulates the direction of reduction/aggregation and the reduction operation.

    - #### matrixScalarRelational

          public static void 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
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in` - input matrix
        `outputName` - output matrix name
        `op` - scalar operator

    - #### matrixScalarArithmetic

          public static void 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
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in` - input matrix
        `outputName` - output matrix name
        `isInputTransposed` - true if input transposed
        `op` - scalar operator

    - #### matrixMatrixRelational

          public static void 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
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix 1
        `in2` - input matrix 2
        `outputName` - output matrix name
        `op` - binary operator

    - #### matrixMatrixArithmetic

          public static void 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
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix 1
        `in2` - input matrix 2
        `outputName` - output matrix name
        `isLeftTransposed` - true if left-transposed
        `isRightTransposed` - true if right-transposed
        `op` - binary operator

    - #### matrixScalarOp

          public static void matrixScalarOp(ExecutionContext ec,
                                            GPUContext gCtx,
                                            String instName,
                                            MatrixObject in,
                                            String outputName,
                                            boolean isInputTransposed,
                                            ScalarOperator op)

      Utility to do matrix-scalar operation kernel
      Parameters:
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `ec` - execution context
        `in` - input matrix
        `outputName` - output variable name
        `isInputTransposed` - true if input is transposed
        `op` - operator

    - #### deviceCopy

          public static void deviceCopy(String instName,
                                        jcuda.Pointer src,
                                        jcuda.Pointer dest,
                                        int rlen,
                                        int clen)

      Performs a deep copy of input device double pointer corresponding to matrix
      Parameters:
        `instName` - the invoking instruction's name for record `Statistics`.
        `src` - source matrix
        `dest` - destination matrix
        `rlen` - number of rows
        `clen` - number of columns

    - #### denseTranspose

          public static void denseTranspose(ExecutionContext ec,
                                            GPUContext gCtx,
                                            String instName,
                                            jcuda.Pointer A,
                                            jcuda.Pointer C,
                                            long numRowsA,
                                            long numColsA)
                                     throws DMLRuntimeException

      Computes C = t(A)
      Parameters:
        `ec` - execution context
        `gCtx` - gpu context
        `instName` - name of the instruction
        `A` - pointer to the input matrix
        `C` - pointer to the output matrix
        `numRowsA` - number of rows of the input matrix
        `numColsA` - number of columns of the output matrix
      Throws:
        `DMLRuntimeException` - if error

    - #### transpose

          public static void transpose(ExecutionContext ec,
                                       GPUContext gCtx,
                                       String instName,
                                       MatrixObject in,
                                       String outputName)

      Transposes the input matrix using cublasDgeam
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in` - input matrix
        `outputName` - output matrix name

    - #### toInt

          public static int toInt(long num)

    - #### sliceOperations

          public static void 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.
      Parameters:
        `ec` - current execution context
        `gCtx` - current gpu context
        `instName` - name of the instruction for maintaining statistics
        `in1` - input matrix object
        `ixrange` - index range (0-based)
        `outputName` - output matrix object

    - #### cbind

          public static void cbind(ExecutionContext ec,
                                   GPUContext gCtx,
                                   String instName,
                                   MatrixObject in1,
                                   MatrixObject in2,
                                   String outputName)

    - #### rbind

          public static void rbind(ExecutionContext ec,
                                   GPUContext gCtx,
                                   String instName,
                                   MatrixObject in1,
                                   MatrixObject in2,
                                   String outputName)

    - #### exp

          public static void exp(ExecutionContext ec,
                                 GPUContext gCtx,
                                 String instName,
                                 MatrixObject in1,
                                 String outputName)

      Performs an "exp" operation on a matrix on the GPU
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix
        `outputName` - output matrix name

    - #### sqrt

          public static void sqrt(ExecutionContext ec,
                                  GPUContext gCtx,
                                  String instName,
                                  MatrixObject in1,
                                  String outputName)

      Performs an "sqrt" operation on a matrix on the GPU
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix
        `outputName` - output matrix name

    - #### round

          public static void round(ExecutionContext ec,
                                   GPUContext gCtx,
                                   String instName,
                                   MatrixObject in1,
                                   String outputName)

      Performs an "round" operation on a matrix on the GPU
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix
        `outputName` - output matrix name

    - #### abs

          public static void abs(ExecutionContext ec,
                                 GPUContext gCtx,
                                 String instName,
                                 MatrixObject in1,
                                 String outputName)

      Performs an "abs" operation on a matrix on the GPU
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix
        `outputName` - output matrix name

    - #### log

          public static void log(ExecutionContext ec,
                                 GPUContext gCtx,
                                 String instName,
                                 MatrixObject in1,
                                 String outputName)

      Performs an "log" operation on a matrix on the GPU
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix
        `outputName` - output matrix name

    - #### floor

          public static void floor(ExecutionContext ec,
                                   GPUContext gCtx,
                                   String instName,
                                   MatrixObject in1,
                                   String outputName)

      Performs an "floor" operation on a matrix on the GPU
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix
        `outputName` - output matrix name

    - #### ceil

          public static void ceil(ExecutionContext ec,
                                  GPUContext gCtx,
                                  String instName,
                                  MatrixObject in1,
                                  String outputName)

      Performs an "ceil" operation on a matrix on the GPU
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix
        `outputName` - output matrix name

    - #### sin

          public static void sin(ExecutionContext ec,
                                 GPUContext gCtx,
                                 String instName,
                                 MatrixObject in1,
                                 String outputName)

      Performs an "sin" operation on a matrix on the GPU
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix
        `outputName` - output matrix name

    - #### cos

          public static void cos(ExecutionContext ec,
                                 GPUContext gCtx,
                                 String instName,
                                 MatrixObject in1,
                                 String outputName)

      Performs an "cos" operation on a matrix on the GPU
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix
        `outputName` - output matrix name

    - #### tan

          public static void tan(ExecutionContext ec,
                                 GPUContext gCtx,
                                 String instName,
                                 MatrixObject in1,
                                 String outputName)

      Performs an "tan" operation on a matrix on the GPU
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix
        `outputName` - output matrix name

    - #### sinh

          public static void sinh(ExecutionContext ec,
                                  GPUContext gCtx,
                                  String instName,
                                  MatrixObject in1,
                                  String outputName)

      Performs an "sinh" operation on a matrix on the GPU
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix
        `outputName` - output matrix name

    - #### cosh

          public static void cosh(ExecutionContext ec,
                                  GPUContext gCtx,
                                  String instName,
                                  MatrixObject in1,
                                  String outputName)

      Performs an "cosh" operation on a matrix on the GPU
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix
        `outputName` - output matrix name

    - #### tanh

          public static void tanh(ExecutionContext ec,
                                  GPUContext gCtx,
                                  String instName,
                                  MatrixObject in1,
                                  String outputName)

      Performs an "tanh" operation on a matrix on the GPU
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix
        `outputName` - output matrix name

    - #### asin

          public static void asin(ExecutionContext ec,
                                  GPUContext gCtx,
                                  String instName,
                                  MatrixObject in1,
                                  String outputName)

      Performs an "asin" operation on a matrix on the GPU
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix
        `outputName` - output matrix name

    - #### acos

          public static void acos(ExecutionContext ec,
                                  GPUContext gCtx,
                                  String instName,
                                  MatrixObject in1,
                                  String outputName)

      Performs an "acos" operation on a matrix on the GPU
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix
        `outputName` - output matrix name

    - #### atan

          public static void atan(ExecutionContext ec,
                                  GPUContext gCtx,
                                  String instName,
                                  MatrixObject in1,
                                  String outputName)

      Performs an "atan" operation on a matrix on the GPU
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix
        `outputName` - output matrix name

    - #### sign

          public static void sign(ExecutionContext ec,
                                  GPUContext gCtx,
                                  String instName,
                                  MatrixObject in1,
                                  String outputName)

      Performs an "sign" operation on a matrix on the GPU
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix
        `outputName` - output matrix name

    - #### sigmoid

          public static void sigmoid(ExecutionContext ec,
                                     GPUContext gCtx,
                                     String instName,
                                     MatrixObject in1,
                                     String outputName)

      Performs an "sigmoid" operation on a matrix on the GPU
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix
        `outputName` - output matrix name

    - #### cumulativeScan

          public static void cumulativeScan(ExecutionContext ec,
                                            GPUContext gCtx,
                                            String instName,
                                            String kernelFunction,
                                            MatrixObject in,
                                            String outputName)

      Cumulative scan
      Parameters:
        `ec` - valid execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `kernelFunction` - The name of the cuda kernel to call
        `in` - input matrix
        `outputName` - output matrix name

    - #### cumulativeSumProduct

          public static void cumulativeSumProduct(ExecutionContext ec,
                                                  GPUContext gCtx,
                                                  String instName,
                                                  String kernelFunction,
                                                  MatrixObject in,
                                                  String outputName)

      Cumulative sum-product kernel cascade invokation
      Parameters:
        `ec` - valid execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `kernelFunction` - The name of the cuda kernel to call
        `in` - input matrix
        `outputName` - output matrix name

    - #### axpy

          public static void axpy(ExecutionContext ec,
                                  GPUContext gCtx,
                                  String instName,
                                  MatrixObject in1,
                                  MatrixObject in2,
                                  String outputName,
                                  double constant)

      Performs daxpy operation
      Parameters:
        `ec` - execution context
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix 1
        `in2` - input matrix 2
        `outputName` - output matrix name
        `constant` - pointer constant

    - #### solve

          public static void 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)
      Parameters:
        `ec` - a valid `ExecutionContext`
        `gCtx` - a valid `GPUContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `in1` - input matrix A
        `in2` - input matrix B
        `outputName` - name of the output matrix

    - #### getDenseMatrixOutputForGPUInstruction

          public static MatrixObject 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`
      Parameters:
        `ec` - active `ExecutionContext`
        `instName` - the invoking instruction's name for record `Statistics`.
        `name` - name of input matrix (that the `ExecutionContext` is aware of)
        `numRows` - number of rows of output matrix object
        `numCols` - number of columns of output matrix object
      Returns:
        the matrix object

    - #### computeNNZ

          public static int computeNNZ(GPUContext gCtx,
                                       jcuda.Pointer densePtr,
                                       int length)

      Utility to compute number of non-zeroes on the GPU
      Parameters:
        `gCtx` - the associated GPUContext
        `densePtr` - device pointer to the dense matrix
        `length` - length of the dense pointer
      Returns:
        the number of non-zeroes

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