vector_kernel.cu
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vector_kernel.cu
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	// -------------------------------------------------------------
	// CUDPP -- CUDA Data Parallel Primitives library
	// -------------------------------------------------------------
	// $Revision: 5632 $
	// $Date: 2009-07-01 14:36:01 +1000 (Wed, 01 Jul 2009) $
	// -------------------------------------------------------------
	// This source code is distributed under the terms of license.txt in
	// the root directory of this source distribution.
	// -------------------------------------------------------------

	/**
	* @file
	* vector_kernel.cu
	*
	* @brief CUDA kernel methods for basic operations on vectors.
	*
	* CUDA kernel methods for basic operations on vectors.
	*
	* Examples:
	* - vectorAddConstant(): d_vector + constant
	* - vectorAddUniform(): d_vector + uniform (per-block constants)
	* - vectorAddVectorVector(): d_vector + d_vector
	*/

	// MJH: these functions assume there are 2N elements for N threads.
	// Is this always going to be a good idea? There may be cases where
	// we have as many threads as elements, but for large problems
	// we are probably limited by max CTA size for simple kernels like
	// this so we should process multiple elements per thread.
	// we may want to extend these with looping versions that process
	// many elements per thread.

	#include "cudpp_util.h"
	#include "sharedmem.h"
	#include "cudpp.h"

	/** \addtogroup cudpp_kernel
	* @{
	*/

	/** @name Vector Functions
	* CUDA kernel methods for basic operations on vectors.
	* @{
	*/

	/** @brief Adds a constant value to all values in the input d_vector
	*
	* Each thread adds two pairs of elements.
	* @todo Test this function -- it is currently not yet used.
	*
	* @param[in,out] d_vector The array of elements to be modified
	* @param[in] constant The constant value to be added to elements of
	* \a d_vector
	* @param[in] n The number of elements in the d_vector to be modified
	* @param[in] baseIndex An optional offset to the beginning of the
	* elements in the input array to be processed
	*/
	template <class T>
	__global__ void vectorAddConstant(T *d_vector,
	T constant,
	int n,
	int baseIndex)
	{
	// Compute this thread's output address
	unsigned int address = baseIndex + threadIdx.x +
	__mul24(blockIdx.x, (blockDim.x << 1));

	// note two adds per thread: one in first half of the block, one in last
	d_vector[address] += constant;
	d_vector[address + blockDim.x] += (threadIdx.x + blockDim.x < n) * constant;
	}

	/** @brief Add a uniform value to each data element of an array
	*
	* This function reads one value per CTA from \a d_uniforms into shared
	* memory and adds that value to all values "owned" by the CTA in \a
	* d_vector. Each thread adds two pairs of values.
	*
	* @param[out] d_vector The d_vector whose values will have the uniform added
	* @param[in] d_uniforms The array of uniform values (one per CTA)
	* @param[in] numElements The number of elements in \a d_vector to process
	* @param[in] blockOffset an optional offset to the beginning of this block's
	* data.
	* @param[in] baseIndex an optional offset to the beginning of the array
	* within \a d_vector.
	*/
	template <class T>
	__global__ void vectorAddUniform(T *d_vector,
	const T *d_uniforms,
	int numElements,
	int blockOffset,
	int baseIndex)
	{
	__shared__ T uni;
	// Get this block's uniform value from the uniform array in device memory
	// We store it in shared memory so that the hardware's shared memory
	// broadcast capability can be used to share among all threads in each warp
	// in a single cycle
	if (threadIdx.x == 0)
	{
	uni = d_uniforms[blockIdx.x + __mul24(gridDim.x, blockIdx.y) + blockOffset];
	}

	// Compute this thread's output address
	int width = __mul24(gridDim.x,(blockDim.x << 1));

	unsigned int address = baseIndex + __mul24(width, blockIdx.y)
	+ threadIdx.x + __mul24(blockIdx.x, (blockDim.x << 1));

	__syncthreads();

	// note two adds per thread: one in first half of the block, one in last
	d_vector[address] += uni;
	if (threadIdx.x + blockDim.x < numElements) d_vector[address + blockDim.x] += uni;
	}


	/** @brief Add a uniform value to each data element of an array (vec4 version)
	*
	* This function reads one value per CTA from \a d_uniforms into shared
	* memory and adds that value to all values "owned" by the CTA in \a d_vector.
	* Each thread adds the uniform value to eight values in \a d_vector.
	*
	* @param[out] d_vector The d_vector whose values will have the uniform added
	* @param[in] d_uniforms The array of uniform values (one per CTA)
	* @param[in] numElements The number of elements in \a d_vector to process
	* @param[in] vectorRowPitch For 2D arrays, the pitch (in elements) of the
	* rows of \a d_vector.
	* @param[in] uniformRowPitch For 2D arrays, the pitch (in elements) of the
	* rows of \a d_uniforms.
	* @param[in] blockOffset an optional offset to the beginning of this block's
	* data.
	* @param[in] baseIndex an optional offset to the beginning of the array
	* within \a d_vector.
	*/
	template <class T, CUDPPOperator op, int elementsPerThread>
	__global__ void vectorAddUniform4(T *d_vector,
	const T *d_uniforms,
	int numElements,
	int vectorRowPitch, // width of input array in elements
	int uniformRowPitch, // width of uniform array in elements
	int blockOffset,
	int baseIndex)
	{
	__shared__ T uni;
	// Get this block's uniform value from the uniform array in device memory
	// We store it in shared memory so that the hardware's shared memory
	// broadcast capability can be used to share among all threads in each warp
	// in a single cycle
	if (threadIdx.x == 0)
	{
	uni = d_uniforms[blockIdx.x + __umul24(uniformRowPitch, blockIdx.y) + blockOffset];
	}

	// Compute this thread's output address
	//int width = __mul24(gridDim.x,(blockDim.x << 1));

	unsigned int address = baseIndex + __umul24(vectorRowPitch, blockIdx.y)
	+ threadIdx.x + __umul24(blockIdx.x, (blockDim.x * elementsPerThread));
	numElements += __umul24(vectorRowPitch, blockIdx.y);

	__syncthreads();

	switch (op)
	{
	case CUDPP_ADD:
	for (int i = 0; i < elementsPerThread && address < numElements; i++)
	{
	d_vector[address] += uni;
	address += blockDim.x;
	}
	break;

	case CUDPP_MULTIPLY:
	for (int i = 0; i < elementsPerThread && address < numElements; i++)
	{
	d_vector[address] *= uni;
	address += blockDim.x;
	}
	break;

	case CUDPP_MAX:
	for (int i = 0; i < elementsPerThread && address < numElements; i++)
	{
	d_vector[address] = max(d_vector[address], uni);
	address += blockDim.x;
	}
	break;

	case CUDPP_MIN:
	for (int i = 0; i < elementsPerThread && address < numElements; i++)
	{
	d_vector[address] = min(d_vector[address], uni);
	address += blockDim.x;
	}
	break;
	default:
	break;
	}
	}

	/** @brief Adds together two vectors
	*
	* Each thread adds two pairs of elements.
	* @todo Test this function -- it is currently not yet used.
	*
	* @param[out] d_vectorA The left operand array and the result
	* @param[in] d_vectorB The right operand array
	* @param[in] numElements The number of elements in the vectors to be added.
	* @param[in] baseIndex An optional offset to the beginning of the
	* elements in the input arrays to be processed
	*/
	template <class T>
	__global__ void vectorAddVector(T *d_vectorA, // A += B
	const T *d_vectorB,
	int numElements,
	int baseIndex)
	{
	// Compute this thread's output address
	unsigned int address = baseIndex + threadIdx.x +
	__mul24(blockIdx.x, (blockDim.x << 1));

	// note two adds per thread: one in first half of the block, one in last
	d_vectorA[address] += d_vectorB[address];
	d_vectorA[address + blockDim.x] +=
	(threadIdx.x + blockDim.x < numElements) * d_vectorB[address];
	}

	/** @brief Add a uniform value to data elements of an array (vec4 version)
	*
	* This function reads one value per CTA from \a d_uniforms into shared
	* memory and adds that value to values "owned" by the CTA in \a d_vector.
	* The uniform value is added to only those values "owned" by the CTA which
	* have an index less than d_maxIndex. If d_maxIndex for that CTA is UINT_MAX
	* it adds the uniform to all values "owned" by the CTA.
	* Each thread adds the uniform value to eight values in \a d_vector.
	*
	* @param[out] d_vector The d_vector whose values will have the uniform added
	* @param[in] d_uniforms The array of uniform values (one per CTA)
	* @param[in] d_maxIndices The array of maximum indices (one per CTA). This is
	* index upto which the uniform would be added. If this is UINT_MAX
	* the uniform is added to all elements of the CTA. This index is
	* 1-based.
	* @param[in] numElements The number of elements in \a d_vector to process
	* @param[in] blockOffset an optional offset to the beginning of this block's
	* data.
	* @param[in] baseIndex an optional offset to the beginning of the array
	* within \a d_vector.
	*/
	template <class T, CUDPPOperator oper, bool isLastBlockFull>
	__global__ void vectorSegmentedAddUniform4(T *d_vector,
	const T *d_uniforms,
	const unsigned int *d_maxIndices,
	unsigned int numElements,
	int blockOffset,
	int baseIndex)
	{
	__shared__ T uni[2];

	unsigned int blockAddress =
	blockIdx.x + __mul24(gridDim.x, blockIdx.y) + blockOffset;

	// Get this block's uniform value from the uniform array in device memory
	// We store it in shared memory so that the hardware's shared memory
	// broadcast capability can be used to share among all threads in each warp
	// in a single cycle

	if (threadIdx.x == 0)
	{
	if (blockAddress > 0)
	uni[0] = d_uniforms[blockAddress-1];
	else
	uni[0] = Operator<T, oper>::identity();

	// Tacit assumption that T is four-byte wide
	uni[1] = (T)(d_maxIndices[blockAddress]);
	}

	// Compute this thread's output address
	int width = __mul24(gridDim.x,(blockDim.x << 1));

	unsigned int address = baseIndex + __mul24(width, blockIdx.y)
	+ threadIdx.x + __mul24(blockIdx.x, (blockDim.x << 3));

	__syncthreads();

	unsigned int maxIndex = (unsigned int)(uni[1]);

	bool isLastBlock = (blockIdx.x == (gridDim.x-1));

	if (maxIndex < UINT_MAX)
	{
	// Since maxIndex is a 1 based index
	--maxIndex;
	bool leftLess = address < maxIndex;
	bool rightLess = (address + 7 * blockDim.x) < maxIndex;

	if (leftLess)
	{
	if (rightLess)
	{
	for (unsigned int i = 0; i < 8; ++i)
	d_vector[address + i * blockDim.x] =
	Operator<T, oper>::op(d_vector[address + i * blockDim.x], uni[0]);
	}
	else
	{
	for (unsigned int i=0; i < 8; ++i)
	{
	if (address < maxIndex)
	d_vector[address] =
	Operator<T, oper>::op(d_vector[address], uni[0]);

	address += blockDim.x;
	}
	}
	}
	}
	else
	{
	if (!isLastBlockFull && isLastBlock)
	{
	for (unsigned int i = 0; i < 8; ++i)
	{
	if (address < numElements)
	d_vector[address] =
	Operator<T, oper>::op(d_vector[address], uni[0]);

	address += blockDim.x;
	}
	}
	else
	{
	for (unsigned int i=0; i<8; ++i)
	{
	d_vector[address] =
	Operator<T, oper>::op(d_vector[address], uni[0]);

	address += blockDim.x;
	}
	}
	}
	}

	/** @brief Add a uniform value to data elements of an array (vec4 version)
	*
	* This function reads one value per CTA from \a d_uniforms into shared
	* memory and adds that value to values "owned" by the CTA in \a d_vector.
	* The uniform value is added to only those values "owned" by the CTA which
	* have an index greater than d_minIndex. If d_minIndex for that CTA is 0
	* it adds the uniform to all values "owned" by the CTA.
	* Each thread adds the uniform value to eight values in \a d_vector.
	*
	* @param[out] d_vector The d_vector whose values will have the uniform added
	* @param[in] d_uniforms The array of uniform values (one per CTA)
	* @param[in] d_minIndices The array of minimum indices (one per CTA). The
	* uniform is added to the right of this index (that is, to every index
	* that is greater than this index). If this is 0, the uniform is
	* added to all elements of the CTA. This index is 1-based to
	* prevent overloading of what 0 means. In our case it means
	* absence of a flag. But if the first element of a CTA has
	* flag the index will also be 0. Hence we use 1-based indices
	* so the index is 1 in the latter case.
	* @param[in] numElements The number of elements in \a d_vector to process
	* @param[in] blockOffset an optional offset to the beginning of this block's
	* data.
	* @param[in] baseIndex an optional offset to the beginning of the array
	* within \a d_vector.
	*
	*/
	template <class T, CUDPPOperator oper, bool isLastBlockFull>
	__global__ void vectorSegmentedAddUniformToRight4(T *d_vector,
	const T *d_uniforms,
	const unsigned int *d_minIndices,
	unsigned int numElements,
	int blockOffset,
	int baseIndex)
	{
	__shared__ T uni[2];

	unsigned int blockAddress =
	blockIdx.x + __mul24(gridDim.x, blockIdx.y) + blockOffset;

	// Get this block's uniform value from the uniform array in device memory
	// We store it in shared memory so that the hardware's shared memory
	// broadcast capability can be used to share among all threads in each warp
	// in a single cycle

	if (threadIdx.x == 0)
	{
	// FIXME - blockAddress test here is incompatible with how it is calculated
	// above
	if (blockAddress < (gridDim.x-1))
	uni[0] = d_uniforms[blockAddress+1];
	else
	uni[0] = Operator<T, oper>::identity();

	// Tacit assumption that T is four-byte wide
	uni[1] = (T)(d_minIndices[blockAddress]);
	}

	// Compute this thread's output address
	int width = __mul24(gridDim.x,(blockDim.x << 1));

	unsigned int address = baseIndex + __mul24(width, blockIdx.y)
	+ threadIdx.x + __mul24(blockIdx.x, (blockDim.x << 3));

	__syncthreads();

	unsigned int minIndex = (unsigned int)(uni[1]);

	bool isLastBlock = (blockIdx.x == (gridDim.x-1));

	if (minIndex > 0)
	{
	// Since minIndex is a 1 based index
	--minIndex;
	bool leftInRange = address > minIndex;
	bool rightInRange = (address + 7 * blockDim.x) > minIndex;

	if (rightInRange)
	{
	if (leftInRange)
	{
	for (unsigned int i = 0; i < 8; ++i)
	d_vector[address + i * blockDim.x] =
	Operator<T, oper>::op(d_vector[address + i * blockDim.x], uni[0]);
	}
	else
	{
	for (unsigned int i=0; i < 8; ++i)
	{
	if (address > minIndex)
	d_vector[address] =
	Operator<T, oper>::op(d_vector[address], uni[0]);

	address += blockDim.x;
	}
	}
	}
	}
	else
	{
	if (!isLastBlockFull && isLastBlock)
	{
	for (unsigned int i = 0; i < 8; ++i)
	{
	if (address < numElements)
	d_vector[address] =
	Operator<T, oper>::op(d_vector[address], uni[0]);

	address += blockDim.x;
	}
	}
	else
	{
	for (unsigned int i=0; i<8; ++i)
	{
	d_vector[address] =
	Operator<T, oper>::op(d_vector[address], uni[0]);

	address += blockDim.x;
	}
	}
	}
	}

	/** @} */ // end d_vector functions
	/** @} */ // end cudpp_kernel

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