JCudaObject.CSRPointer (SystemML 0.14.0 API)

java.lang.Object
- org.apache.sysml.runtime.instructions.gpu.context.JCudaObject.CSRPointer

Enclosing class:

JCudaObject
```
public static class JCudaObject.CSRPointer
extends Object
```
Compressed Sparse Row (CSR) format for CUDA Generalized matrix multiply is implemented for CSR format in the cuSparse library among other operations

Field Summary

Fields
Modifier and Type	Field and Description
`jcuda.Pointer`	`colInd` integer array of nnz values' column indices
`jcuda.jcusparse.cusparseMatDescr`	`descr` descriptor of matrix, only CUSPARSE_MATRIX_TYPE_GENERAL supported
`static jcuda.jcusparse.cusparseMatDescr`	`matrixDescriptor`
`long`	`nnz` Number of non zeroes
`jcuda.Pointer`	`rowPtr` integer array of start of all rows and end of last row + 1
`jcuda.Pointer`	`val` double array of non zero values

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`static JCudaObject.CSRPointer`	`allocateEmpty(long nnz2, long rows)` Factory method to allocate an empty CSR Sparse matrix on the GPU
`static JCudaObject.CSRPointer`	`allocateForDgeam(jcuda.jcusparse.cusparseHandle handle, JCudaObject.CSRPointer A, JCudaObject.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 JCudaObject.CSRPointer`	`allocateForMatrixMultiply(jcuda.jcusparse.cusparseHandle handle, JCudaObject.CSRPointer A, int transA, JCudaObject.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 `JCudaObject.CSRPointer` to C with the appropriate GPU memory.
`static void`	`copyToDevice(JCudaObject.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 void`	`copyToHost(JCudaObject.CSRPointer src, int rows, long nnz, int[] rowPtr, int[] colInd, double[] values)` Static method to copy a CSR sparse matrix from Device to host
`void`	`deallocate()` Calls cudaFree lazily on the allocated `Pointer` instances
`void`	`deallocate(boolean eager)` Calls cudaFree lazily or eagerly on the allocated `Pointer` instances
`static long`	`estimateSize(long nnz2, long rows)` Estimate the size of a CSR matrix in GPU memory Size of pointers is not needed and is not added in
`static jcuda.jcusparse.cusparseMatDescr`	`getDefaultCuSparseMatrixDescriptor()`
`boolean`	`isUltraSparse(int rows, int cols)` Check for ultra sparsity
`jcuda.Pointer`	`toColumnMajorDenseMatrix(jcuda.jcusparse.cusparseHandle cusparseHandle, jcuda.jcublas.cublasHandle cublasHandle, int rows, int cols)` Copies this CSR matrix on the GPU to a dense column-major matrix on the GPU.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - matrixDescriptor
```
public static jcuda.jcusparse.cusparseMatDescr matrixDescriptor
```
  - nnz
```
public long nnz
```
    Number of non zeroes
  - val
```
public jcuda.Pointer val
```
    double array of non zero values
  - rowPtr
```
public jcuda.Pointer rowPtr
```
    integer array of start of all rows and end of last row + 1
  - colInd
```
public jcuda.Pointer colInd
```
    integer array of nnz values' column indices
  - descr
```
public jcuda.jcusparse.cusparseMatDescr descr
```
    descriptor of matrix, only CUSPARSE_MATRIX_TYPE_GENERAL supported
- Method Detail
  - getDefaultCuSparseMatrixDescriptor
```
public static jcuda.jcusparse.cusparseMatDescr getDefaultCuSparseMatrixDescriptor()
```
    Returns:
    
    Singleton default matrix descriptor object (set with CUSPARSE_MATRIX_TYPE_GENERAL, CUSPARSE_INDEX_BASE_ZERO)
  - isUltraSparse
```
public boolean isUltraSparse(int rows,
                             int cols)
```
    Check for ultra sparsity
    
    Parameters:
    
    rows - number of rows
    
    cols - number of columns
    
    Returns:
    
    true if ultra sparse
  - estimateSize
```
public static long estimateSize(long nnz2,
                                long rows)
```
    Estimate the size of a CSR matrix in GPU memory Size of pointers is not needed and is not added in
    
    Parameters:
    
    nnz2 - number of non zeroes
    
    rows - number of rows
    
    Returns:
    
    size estimate
  - allocateEmpty
```
public static JCudaObject.CSRPointer allocateEmpty(long nnz2,
                                                   long rows)
                                            throws DMLRuntimeException
```
    Factory method to allocate an empty CSR Sparse matrix on the GPU
    
    Parameters:
    
    nnz2 - number of non-zeroes
    
    rows - number of rows
    
    Returns:
    
    a JCudaObject.CSRPointer instance that encapsulates the CSR matrix on GPU
    
    Throws:
    
    DMLRuntimeException - if DMLRuntimeException occurs
  - copyToDevice
```
public static void copyToDevice(JCudaObject.CSRPointer dest,
                                int rows,
                                long nnz,
                                int[] rowPtr,
                                int[] colInd,
                                double[] values)
```
    Static method to copy a CSR sparse matrix from Host to Device
    
    Parameters:
    
    dest - [input] destination location (on GPU)
    
    rows - number of rows
    
    nnz - number of non-zeroes
    
    rowPtr - integer array of row pointers
    
    colInd - integer array of column indices
    
    values - double array of non zero values
  - copyToHost
```
public static void copyToHost(JCudaObject.CSRPointer src,
                              int rows,
                              long nnz,
                              int[] rowPtr,
                              int[] colInd,
                              double[] values)
```
    Static method to copy a CSR sparse matrix from Device to host
    
    Parameters:
    
    src - [input] source location (on GPU)
    
    rows - [input] number of rows
    
    nnz - [input] number of non-zeroes
    
    rowPtr - [output] pre-allocated integer array of row pointers of size (rows+1)
    
    colInd - [output] pre-allocated integer array of column indices of size nnz
    
    values - [output] pre-allocated double array of values of size nnz
  - allocateForDgeam
```
public static JCudaObject.CSRPointer allocateForDgeam(jcuda.jcusparse.cusparseHandle handle,
                                                      JCudaObject.CSRPointer A,
                                                      JCudaObject.CSRPointer B,
                                                      int m,
                                                      int n)
                                               throws DMLRuntimeException
```
    Estimates the number of non zero elements from the results of a sparse cusparseDgeam operation C = a op(A) + b op(B)
    
    Parameters:
    
    handle - a valid cusparseHandle
    
    A - Sparse Matrix A on GPU
    
    B - Sparse Matrix B on GPU
    
    m - Rows in A
    
    n - Columns in Bs
    
    Returns:
    
    CSR (compressed sparse row) pointer
    
    Throws:
    
    DMLRuntimeException - if DMLRuntimeException occurs
  - allocateForMatrixMultiply
```
public static JCudaObject.CSRPointer allocateForMatrixMultiply(jcuda.jcusparse.cusparseHandle handle,
                                                               JCudaObject.CSRPointer A,
                                                               int transA,
                                                               JCudaObject.CSRPointer B,
                                                               int transB,
                                                               int m,
                                                               int n,
                                                               int k)
                                                        throws DMLRuntimeException
```
    Estimates the number of non-zero elements from the result of a sparse matrix multiplication C = A * B and returns the JCudaObject.CSRPointer to C with the appropriate GPU memory.
    
    Parameters:
    
    handle - a valid cusparseHandle
    
    A - Sparse Matrix A on GPU
    
    transA - 'T' if A is to be transposed, 'N' otherwise
    
    B - Sparse Matrix B on GPU
    
    transB - 'T' if B is to be transposed, 'N' otherwise
    
    m - Rows in A
    
    n - Columns in B
    
    k - Columns in A / Rows in B
    
    Returns:
    
    a JCudaObject.CSRPointer instance that encapsulates the CSR matrix on GPU
    
    Throws:
    
    DMLRuntimeException - if DMLRuntimeException occurs
  - toColumnMajorDenseMatrix
```
public jcuda.Pointer toColumnMajorDenseMatrix(jcuda.jcusparse.cusparseHandle cusparseHandle,
                                              jcuda.jcublas.cublasHandle cublasHandle,
                                              int rows,
                                              int cols)
                                       throws DMLRuntimeException
```
    Copies this CSR matrix on the GPU to a dense column-major matrix on the GPU. This is a temporary matrix for operations such as cusparseDcsrmv. Since the allocated matrix is temporary, bookkeeping is not updated. The caller is responsible for calling "free" on the returned Pointer object
    
    Parameters:
    
    cusparseHandle - a valid cusparseHandle
    
    cublasHandle - a valid cublasHandle
    
    rows - number of rows in this CSR matrix
    
    cols - number of columns in this CSR matrix
    
    Returns:
    
    A Pointer to the allocated dense matrix (in column-major format)
    
    Throws:
    
    DMLRuntimeException - if DMLRuntimeException occurs
  - deallocate
```
public void deallocate()
```
    Calls cudaFree lazily on the allocated Pointer instances
  - deallocate
```
public void deallocate(boolean eager)
```
    Calls cudaFree lazily or eagerly on the allocated Pointer instances
    
    Parameters:
    
    eager - whether to do eager or lazy cudaFrees

Methods inherited from class java.lang.Object

matrixDescriptor

nnz

val

rowPtr

colInd

descr

getDefaultCuSparseMatrixDescriptor

isUltraSparse

estimateSize

allocateEmpty

copyToDevice

copyToHost

allocateForDgeam

allocateForMatrixMultiply

toColumnMajorDenseMatrix

deallocate

deallocate