jcuda.jcublas.JCublas.cublasGetVectorNative java code examples

/**
 * Wrapper for CUBLAS function.<br />
 * <br />
 * cublasStatus<br />
 * cublasGetVector (int n, int elemSize, const void *x, int incx,
 *                  void *y, int incy)<br />
 *<br />
 * copies n elements from a vector x in GPU memory space to a vector y
 * in CPU memory space. Elements in both vectors are assumed to have a
 * size of elemSize bytes. Storage spacing between consecutive elements
 * is incx for the source vector x and incy for the destination vector
 * y. In general, x points to an object, or part of an object, allocated
 * via cublasAlloc(). Column major format for two-dimensional matrices
 * is assumed throughout CUBLAS. Therefore, if the increment for a vector
 * is equal to 1, this access a column vector while using an increment
 * equal to the leading dimension of the respective matrix accesses a
 * row vector.<br />
 *<br />
 * Return Values<br />
 * -------------<br />
 * CUBLAS_STATUS_NOT_INITIALIZED  if CUBLAS library not been initialized<br />
 * CUBLAS_STATUS_INVALID_VALUE    if incx, incy, or elemSize <= 0<br />
 * CUBLAS_STATUS_MAPPING_ERROR    if an error occurred accessing GPU memory<br />
 * CUBLAS_STATUS_SUCCESS          if the operation completed successfully<br />
 */
public static int cublasGetVector (int n, int elemSize, Pointer x, int incx, Pointer y, int incy)
{
  return checkResult(cublasGetVectorNative(n, elemSize, x, incx, y, incy));
}

/**
 * Wrapper for CUBLAS function.<br />
 * <br />
 * cublasStatus<br />
 * cublasGetVector (int n, int elemSize, const void *x, int incx,
 *                  void *y, int incy)<br />
 *<br />
 * copies n elements from a vector x in GPU memory space to a vector y
 * in CPU memory space. Elements in both vectors are assumed to have a
 * size of elemSize bytes. Storage spacing between consecutive elements
 * is incx for the source vector x and incy for the destination vector
 * y. In general, x points to an object, or part of an object, allocated
 * via cublasAlloc(). Column major format for two-dimensional matrices
 * is assumed throughout CUBLAS. Therefore, if the increment for a vector
 * is equal to 1, this access a column vector while using an increment
 * equal to the leading dimension of the respective matrix accesses a
 * row vector.<br />
 *<br />
 * Return Values<br />
 * -------------<br />
 * CUBLAS_STATUS_NOT_INITIALIZED  if CUBLAS library not been initialized<br />
 * CUBLAS_STATUS_INVALID_VALUE    if incx, incy, or elemSize <= 0<br />
 * CUBLAS_STATUS_MAPPING_ERROR    if an error occurred accessing GPU memory<br />
 * CUBLAS_STATUS_SUCCESS          if the operation completed successfully<br />
 */
public static int cublasGetVector (int n, int elemSize, Pointer x, int incx, Pointer y, int incy)
{
  return checkResult(cublasGetVectorNative(n, elemSize, x, incx, y, incy));
}

/**
 * Wrapper for CUBLAS function.<br />
 * <br />
 * cublasStatus<br />
 * cublasGetVector (int n, int elemSize, const void *x, int incx,
 *                  void *y, int incy)<br />
 *<br />
 * copies n elements from a vector x in GPU memory space to a vector y
 * in CPU memory space. Elements in both vectors are assumed to have a
 * size of elemSize bytes. Storage spacing between consecutive elements
 * is incx for the source vector x and incy for the destination vector
 * y. In general, x points to an object, or part of an object, allocated
 * via cublasAlloc(). Column major format for two-dimensional matrices
 * is assumed throughout CUBLAS. Therefore, if the increment for a vector
 * is equal to 1, this access a column vector while using an increment
 * equal to the leading dimension of the respective matrix accesses a
 * row vector.<br />
 *<br />
 * Return Values<br />
 * -------------<br />
 * CUBLAS_STATUS_NOT_INITIALIZED  if CUBLAS library not been initialized<br />
 * CUBLAS_STATUS_INVALID_VALUE    if incx, incy, or elemSize <= 0<br />
 * CUBLAS_STATUS_MAPPING_ERROR    if an error occurred accessing GPU memory<br />
 * CUBLAS_STATUS_SUCCESS          if the operation completed successfully<br />
 */
public static int cublasGetVector (int n, int elemSize, Pointer x, int incx, Pointer y, int incy)
{
 return checkResult(cublasGetVectorNative(n, elemSize, x, incx, y, incy));
}

/**
 * Wrapper for CUBLAS function.<br />
 * <br />
 * cublasStatus<br />
 * cublasGetVector (int n, int elemSize, const void *x, int incx,
 *                  void *y, int incy)<br />
 *<br />
 * copies n elements from a vector x in GPU memory space to a vector y
 * in CPU memory space. Elements in both vectors are assumed to have a
 * size of elemSize bytes. Storage spacing between consecutive elements
 * is incx for the source vector x and incy for the destination vector
 * y. In general, x points to an object, or part of an object, allocated
 * via cublasAlloc(). Column major format for two-dimensional matrices
 * is assumed throughout CUBLAS. Therefore, if the increment for a vector
 * is equal to 1, this access a column vector while using an increment
 * equal to the leading dimension of the respective matrix accesses a
 * row vector.<br />
 *<br />
 * Return Values<br />
 * -------------<br />
 * CUBLAS_STATUS_NOT_INITIALIZED  if CUBLAS library not been initialized<br />
 * CUBLAS_STATUS_INVALID_VALUE    if incx, incy, or elemSize <= 0<br />
 * CUBLAS_STATUS_MAPPING_ERROR    if an error occurred accessing GPU memory<br />
 * CUBLAS_STATUS_SUCCESS          if the operation completed successfully<br />
 */
public static int cublasGetVector (int n, int elemSize, Pointer x, int incx, Pointer y, int incy)
{
  return checkResult(cublasGetVectorNative(n, elemSize, x, incx, y, incy));
}

/**
 * Wrapper for CUBLAS function.<br />
 * <br />
 * cublasStatus<br />
 * cublasGetVector (int n, int elemSize, const void *x, int incx,
 *                  void *y, int incy)<br />
 *<br />
 * copies n elements from a vector x in GPU memory space to a vector y
 * in CPU memory space. Elements in both vectors are assumed to have a
 * size of elemSize bytes. Storage spacing between consecutive elements
 * is incx for the source vector x and incy for the destination vector
 * y. In general, x points to an object, or part of an object, allocated
 * via cublasAlloc(). Column major format for two-dimensional matrices
 * is assumed throughout CUBLAS. Therefore, if the increment for a vector
 * is equal to 1, this access a column vector while using an increment
 * equal to the leading dimension of the respective matrix accesses a
 * row vector.<br />
 *<br />
 * Return Values<br />
 * -------------<br />
 * CUBLAS_STATUS_NOT_INITIALIZED  if CUBLAS library not been initialized<br />
 * CUBLAS_STATUS_INVALID_VALUE    if incx, incy, or elemSize <= 0<br />
 * CUBLAS_STATUS_MAPPING_ERROR    if an error occurred accessing GPU memory<br />
 * CUBLAS_STATUS_SUCCESS          if the operation completed successfully<br />
 */
public static int cublasGetVector (int n, int elemSize, Pointer x, int incx, Pointer y, int incy)
{
  return checkResult(cublasGetVectorNative(n, elemSize, x, incx, y, incy));
}

/**
 * Wrapper for CUBLAS function.<br />
 * <br />
 * cublasStatus<br />
 * cublasGetVector (int n, int elemSize, const void *x, int incx,
 *                  void *y, int incy)<br />
 *<br />
 * copies n elements from a vector x in GPU memory space to a vector y
 * in CPU memory space. Elements in both vectors are assumed to have a
 * size of elemSize bytes. Storage spacing between consecutive elements
 * is incx for the source vector x and incy for the destination vector
 * y. In general, x points to an object, or part of an object, allocated
 * via cublasAlloc(). Column major format for two-dimensional matrices
 * is assumed throughout CUBLAS. Therefore, if the increment for a vector
 * is equal to 1, this access a column vector while using an increment
 * equal to the leading dimension of the respective matrix accesses a
 * row vector.<br />
 *<br />
 * Return Values<br />
 * -------------<br />
 * CUBLAS_STATUS_NOT_INITIALIZED  if CUBLAS library not been initialized<br />
 * CUBLAS_STATUS_INVALID_VALUE    if incx, incy, or elemSize <= 0<br />
 * CUBLAS_STATUS_MAPPING_ERROR    if an error occurred accessing GPU memory<br />
 * CUBLAS_STATUS_SUCCESS          if the operation completed successfully<br />
 */
public static int cublasGetVector (int n, int elemSize, Pointer x, int incx, Pointer y, int incy)
{
  return checkResult(cublasGetVectorNative(n, elemSize, x, incx, y, incy));
}

/**
 * Extended wrapper for arrays of cuDoubleComplex values. Note that this method
 * only exists for convenience and compatibility with native C code. It
 * is much more efficient to provide a Pointer to a double array that may
 * store the complex numbers, where each pair of consecutive numbers in
 * the array describes the real- and imaginary part of one complex number.
 *
 * @see JCublas#cublasGetVector(int, int, Pointer, int, Pointer, int)
 */
public static int cublasGetVector (int n, Pointer x, int incx, cuDoubleComplex y[], int offsety, int incy)
{
  ByteBuffer byteBuffery = ByteBuffer.allocateDirect(y.length * 8 * 2);
  byteBuffery.order(ByteOrder.nativeOrder());
  DoubleBuffer doubleBuffery = byteBuffery.asDoubleBuffer();
  int status = cublasGetVectorNative(n, 16, x, incx, Pointer.to(doubleBuffery).withByteOffset(offsety * 8 * 2), incy);
  if (status == cublasStatus.CUBLAS_STATUS_SUCCESS)
  {
    doubleBuffery.rewind();
    int indexy = offsety;
    for (int i=0; i<n; i++, indexy+=incy)
    {
      y[indexy].x = doubleBuffery.get(indexy*2+0);
      y[indexy].y = doubleBuffery.get(indexy*2+1);
    }
  }
  return checkResult(status);
}

/**
 * Extended wrapper for arrays of cuComplex values. Note that this method
 * only exists for convenience and compatibility with native C code. It
 * is much more efficient to provide a Pointer to a float array that may
 * store the complex numbers, where each pair of consecutive numbers in
 * the array describes the real- and imaginary part of one complex number.
 *
 * @see jcuda.jcublas.JCublas#cublasGetVector(int, int, jcuda.Pointer, int, jcuda.Pointer, int)
 */
public static int cublasGetVector (int n, Pointer x, int incx, cuComplex y[], int offsety, int incy)
{
  ByteBuffer byteBuffery = ByteBuffer.allocateDirect(y.length * 4 * 2);
  byteBuffery.order(ByteOrder.nativeOrder());
  FloatBuffer floatBuffery = byteBuffery.asFloatBuffer();
  int status = cublasGetVectorNative(n, 8, x, incx, Pointer.to(floatBuffery).withByteOffset(offsety * 4 * 2), incy);
  if (status == cublasStatus.CUBLAS_STATUS_SUCCESS)
  {
    floatBuffery.rewind();
    int indexy = offsety;
    for (int i=0; i<n; i++, indexy+=incy)
    {
      y[indexy].x = floatBuffery.get(indexy*2+0);
      y[indexy].y = floatBuffery.get(indexy*2+1);
    }
  }
  return checkResult(status);
}

/**
 * Extended wrapper for arrays of cuDoubleComplex values. Note that this method
 * only exists for convenience and compatibility with native C code. It
 * is much more efficient to provide a Pointer to a double array that may
 * store the complex numbers, where each pair of consecutive numbers in
 * the array describes the real- and imaginary part of one complex number.
 *
 * @see JCublas#cublasGetVector(int, int, Pointer, int, Pointer, int)
 */
public static int cublasGetVector (int n, Pointer x, int incx, cuDoubleComplex y[], int offsety, int incy)
{
  ByteBuffer byteBuffery = ByteBuffer.allocateDirect(y.length * 8 * 2);
  byteBuffery.order(ByteOrder.nativeOrder());
  DoubleBuffer doubleBuffery = byteBuffery.asDoubleBuffer();
  int status = cublasGetVectorNative(n, 16, x, incx, Pointer.to(doubleBuffery).withByteOffset(offsety * 8 * 2), incy);
  if (status == cublasStatus.CUBLAS_STATUS_SUCCESS)
  {
    doubleBuffery.rewind();
    int indexy = offsety;
    for (int i=0; i<n; i++, indexy+=incy)
    {
      y[indexy].x = doubleBuffery.get(indexy*2+0);
      y[indexy].y = doubleBuffery.get(indexy*2+1);
    }
  }
  return checkResult(status);
}

/**
 * Extended wrapper for arrays of cuDoubleComplex values. Note that this method
 * only exists for convenience and compatibility with native C code. It
 * is much more efficient to provide a Pointer to a double array that may
 * store the complex numbers, where each pair of consecutive numbers in
 * the array describes the real- and imaginary part of one complex number.
 *
 * @see JCublas#cublasGetVector(int, int, Pointer, int, Pointer, int)
 */
public static int cublasGetVector (int n, Pointer x, int incx, cuDoubleComplex y[], int offsety, int incy)
{
  ByteBuffer byteBuffery = ByteBuffer.allocateDirect(y.length * 8 * 2);
  byteBuffery.order(ByteOrder.nativeOrder());
  DoubleBuffer doubleBuffery = byteBuffery.asDoubleBuffer();
  int status = cublasGetVectorNative(n, 16, x, incx, Pointer.to(doubleBuffery).withByteOffset(offsety * 8 * 2), incy);
  if (status == cublasStatus.CUBLAS_STATUS_SUCCESS)
  {
    doubleBuffery.rewind();
    int indexy = offsety;
    for (int i=0; i<n; i++, indexy+=incy)
    {
      y[indexy].x = doubleBuffery.get(indexy*2+0);
      y[indexy].y = doubleBuffery.get(indexy*2+1);
    }
  }
  return checkResult(status);
}

/**
 * Extended wrapper for arrays of cuDoubleComplex values. Note that this method
 * only exists for convenience and compatibility with native C code. It
 * is much more efficient to provide a Pointer to a double array that may
 * store the complex numbers, where each pair of consecutive numbers in
 * the array describes the real- and imaginary part of one complex number.
 *
 * @see JCublas#cublasGetVector(int, int, Pointer, int, Pointer, int)
 */
public static int cublasGetVector (int n, Pointer x, int incx, cuDoubleComplex y[], int offsety, int incy)
{
  ByteBuffer byteBuffery = ByteBuffer.allocateDirect(y.length * 8 * 2);
  byteBuffery.order(ByteOrder.nativeOrder());
  DoubleBuffer doubleBuffery = byteBuffery.asDoubleBuffer();
  int status = cublasGetVectorNative(n, 16, x, incx, Pointer.to(doubleBuffery).withByteOffset(offsety * 8 * 2), incy);
  if (status == cublasStatus.CUBLAS_STATUS_SUCCESS)
  {
    doubleBuffery.rewind();
    int indexy = offsety;
    for (int i=0; i<n; i++, indexy+=incy)
    {
      y[indexy].x = doubleBuffery.get(indexy*2+0);
      y[indexy].y = doubleBuffery.get(indexy*2+1);
    }
  }
  return checkResult(status);
}

/**
 * Extended wrapper for arrays of cuDoubleComplex values. Note that this method
 * only exists for convenience and compatibility with native C code. It
 * is much more efficient to provide a Pointer to a double array that may
 * store the complex numbers, where each pair of consecutive numbers in
 * the array describes the real- and imaginary part of one complex number.
 *
 * @see jcuda.jcublas.JCublas#cublasGetVector(int, int, jcuda.Pointer, int, jcuda.Pointer, int)
 */
public static int cublasGetVector (int n, Pointer x, int incx, cuDoubleComplex y[], int offsety, int incy)
{
  ByteBuffer byteBuffery = ByteBuffer.allocateDirect(y.length * 8 * 2);
  byteBuffery.order(ByteOrder.nativeOrder());
  DoubleBuffer doubleBuffery = byteBuffery.asDoubleBuffer();
  int status = cublasGetVectorNative(n, 16, x, incx, Pointer.to(doubleBuffery).withByteOffset(offsety * 8 * 2), incy);
  if (status == cublasStatus.CUBLAS_STATUS_SUCCESS)
  {
    doubleBuffery.rewind();
    int indexy = offsety;
    for (int i=0; i<n; i++, indexy+=incy)
    {
      y[indexy].x = doubleBuffery.get(indexy*2+0);
      y[indexy].y = doubleBuffery.get(indexy*2+1);
    }
  }
  return checkResult(status);
}

/**
 * Extended wrapper for arrays of cuComplex values. Note that this method
 * only exists for convenience and compatibility with native C code. It
 * is much more efficient to provide a Pointer to a float array that may
 * store the complex numbers, where each pair of consecutive numbers in
 * the array describes the real- and imaginary part of one complex number.
 *
 * @see JCublas#cublasGetVector(int, int, Pointer, int, Pointer, int)
 */
public static int cublasGetVector (int n, Pointer x, int incx, cuComplex y[], int offsety, int incy)
{
  ByteBuffer byteBuffery = ByteBuffer.allocateDirect(y.length * 4 * 2);
  byteBuffery.order(ByteOrder.nativeOrder());
  FloatBuffer floatBuffery = byteBuffery.asFloatBuffer();
  int status = cublasGetVectorNative(n, 8, x, incx, Pointer.to(floatBuffery).withByteOffset(offsety * 4 * 2), incy);
  if (status == cublasStatus.CUBLAS_STATUS_SUCCESS)
  {
    floatBuffery.rewind();
    int indexy = offsety;
    for (int i=0; i<n; i++, indexy+=incy)
    {
      y[indexy].x = floatBuffery.get(indexy*2+0);
      y[indexy].y = floatBuffery.get(indexy*2+1);
    }
  }
  return checkResult(status);
}

/**
 * Extended wrapper for arrays of cuComplex values. Note that this method
 * only exists for convenience and compatibility with native C code. It
 * is much more efficient to provide a Pointer to a float array that may
 * store the complex numbers, where each pair of consecutive numbers in
 * the array describes the real- and imaginary part of one complex number.
 *
 * @see JCublas#cublasGetVector(int, int, Pointer, int, Pointer, int)
 */
public static int cublasGetVector (int n, Pointer x, int incx, cuComplex y[], int offsety, int incy)
{
  ByteBuffer byteBuffery = ByteBuffer.allocateDirect(y.length * 4 * 2);
  byteBuffery.order(ByteOrder.nativeOrder());
  FloatBuffer floatBuffery = byteBuffery.asFloatBuffer();
  int status = cublasGetVectorNative(n, 8, x, incx, Pointer.to(floatBuffery).withByteOffset(offsety * 4 * 2), incy);
  if (status == cublasStatus.CUBLAS_STATUS_SUCCESS)
  {
    floatBuffery.rewind();
    int indexy = offsety;
    for (int i=0; i<n; i++, indexy+=incy)
    {
      y[indexy].x = floatBuffery.get(indexy*2+0);
      y[indexy].y = floatBuffery.get(indexy*2+1);
    }
  }
  return checkResult(status);
}

/**
 * Extended wrapper for arrays of cuComplex values. Note that this method
 * only exists for convenience and compatibility with native C code. It
 * is much more efficient to provide a Pointer to a float array that may
 * store the complex numbers, where each pair of consecutive numbers in
 * the array describes the real- and imaginary part of one complex number.
 *
 * @see JCublas#cublasGetVector(int, int, Pointer, int, Pointer, int)
 */
public static int cublasGetVector (int n, Pointer x, int incx, cuComplex y[], int offsety, int incy)
{
  ByteBuffer byteBuffery = ByteBuffer.allocateDirect(y.length * 4 * 2);
  byteBuffery.order(ByteOrder.nativeOrder());
  FloatBuffer floatBuffery = byteBuffery.asFloatBuffer();
  int status = cublasGetVectorNative(n, 8, x, incx, Pointer.to(floatBuffery).withByteOffset(offsety * 4 * 2), incy);
  if (status == cublasStatus.CUBLAS_STATUS_SUCCESS)
  {
    floatBuffery.rewind();
    int indexy = offsety;
    for (int i=0; i<n; i++, indexy+=incy)
    {
      y[indexy].x = floatBuffery.get(indexy*2+0);
      y[indexy].y = floatBuffery.get(indexy*2+1);
    }
  }
  return checkResult(status);
}

/**
 * Extended wrapper for arrays of cuComplex values. Note that this method
 * only exists for convenience and compatibility with native C code. It
 * is much more efficient to provide a Pointer to a float array that may
 * store the complex numbers, where each pair of consecutive numbers in
 * the array describes the real- and imaginary part of one complex number.
 *
 * @see JCublas#cublasGetVector(int, int, Pointer, int, Pointer, int)
 */
public static int cublasGetVector (int n, Pointer x, int incx, cuComplex y[], int offsety, int incy)
{
 ByteBuffer byteBuffery = ByteBuffer.allocateDirect(y.length * 4 * 2);
 byteBuffery.order(ByteOrder.nativeOrder());
 FloatBuffer floatBuffery = byteBuffery.asFloatBuffer();
 int status = cublasGetVectorNative(n, 8, x, incx, Pointer.to(floatBuffery).withByteOffset(offsety * 4 * 2), incy);
 if (status == cublasStatus.CUBLAS_STATUS_SUCCESS)
 {
  floatBuffery.rewind();
  int indexy = offsety;
  for (int i=0; i<n; i++, indexy+=incy)
  {
   y[indexy].x = floatBuffery.get(indexy*2+0);
   y[indexy].y = floatBuffery.get(indexy*2+1);
  }
 }
 return checkResult(status);
}

/**
 * Extended wrapper for arrays of cuComplex values. Note that this method
 * only exists for convenience and compatibility with native C code. It
 * is much more efficient to provide a Pointer to a float array that may
 * store the complex numbers, where each pair of consecutive numbers in
 * the array describes the real- and imaginary part of one complex number.
 *
 * @see JCublas#cublasGetVector(int, int, Pointer, int, Pointer, int)
 */
public static int cublasGetVector (int n, Pointer x, int incx, cuComplex y[], int offsety, int incy)
{
  ByteBuffer byteBuffery = ByteBuffer.allocateDirect(y.length * 4 * 2);
  byteBuffery.order(ByteOrder.nativeOrder());
  FloatBuffer floatBuffery = byteBuffery.asFloatBuffer();
  int status = cublasGetVectorNative(n, 8, x, incx, Pointer.to(floatBuffery).withByteOffset(offsety * 4 * 2), incy);
  if (status == cublasStatus.CUBLAS_STATUS_SUCCESS)
  {
    floatBuffery.rewind();
    int indexy = offsety;
    for (int i=0; i<n; i++, indexy+=incy)
    {
      y[indexy].x = floatBuffery.get(indexy*2+0);
      y[indexy].y = floatBuffery.get(indexy*2+1);
    }
  }
  return checkResult(status);
}

/**
 * Extended wrapper for arrays of cuDoubleComplex values. Note that this method
 * only exists for convenience and compatibility with native C code. It
 * is much more efficient to provide a Pointer to a double array that may
 * store the complex numbers, where each pair of consecutive numbers in
 * the array describes the real- and imaginary part of one complex number.
 *
 * @see JCublas#cublasGetVector(int, int, Pointer, int, Pointer, int)
 */
public static int cublasGetVector (int n, Pointer x, int incx, cuDoubleComplex y[], int offsety, int incy)
{
 ByteBuffer byteBuffery = ByteBuffer.allocateDirect(y.length * 8 * 2);
 byteBuffery.order(ByteOrder.nativeOrder());
 DoubleBuffer doubleBuffery = byteBuffery.asDoubleBuffer();
 int status = cublasGetVectorNative(n, 16, x, incx, Pointer.to(doubleBuffery).withByteOffset(offsety * 8 * 2), incy);
 if (status == cublasStatus.CUBLAS_STATUS_SUCCESS)
 {
  doubleBuffery.rewind();
  int indexy = offsety;
  for (int i=0; i<n; i++, indexy+=incy)
  {
   y[indexy].x = doubleBuffery.get(indexy*2+0);
   y[indexy].y = doubleBuffery.get(indexy*2+1);
  }
 }
 return checkResult(status);
}

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How to use cublasGetVectorNativemethodin jcuda.jcublas.JCublas

Best Java code snippets using jcuda.jcublas.JCublas.cublasGetVectorNative (Showing top 18 results out of 315)

How to use
cublasGetVectorNative
method
in
jcuda.jcublas.JCublas