A specilalization of above class, used for 1D Reduce operation. Please note that the class name is same. The only difference is how you instantiate it either by passing 1 user function (i.e. 1D reduction) or 2 user function (i.e. 2D reduction). See code examples for more information. More...

#include <reduce.h>

Public Member Functions
	Reduce (ReduceFunc *reduceFunc)

	~Reduce ()

template<typename T >
T	operator() (Vector< T > &input)

template<typename T >
T	operator() (Matrix< T > &input)

template<typename T >
T	operator() (SparseMatrix< T > &input)

template<typename T >
Vector< T >	operator() (Matrix< T > &input, ReducePolicy reducePolicy)

template<typename T >
Vector< T >	operator() (SparseMatrix< T > &input, ReducePolicy reducePolicy)

template<typename InputIterator >
InputIterator::value_type	operator() (InputIterator inputBegin, InputIterator inputEnd)

template<typename T >
T	CPU (Vector< T > &input)

template<typename T >
T	CPU (Matrix< T > &input)

template<typename T >
T	CPU (SparseMatrix< T > &input)

template<typename T >
Vector< T >	CPU (Matrix< T > &input, ReducePolicy reducePolicy)

template<typename T >
Vector< T >	CPU (SparseMatrix< T > &input, ReducePolicy reducePolicy)

template<typename InputIterator >
InputIterator::value_type	CPU (InputIterator inputBegin, InputIterator inputEnd)

template<typename T >
T	OMP (Vector< T > &input)

template<typename T >
T	OMP (Matrix< T > &input)

template<typename T >
T	OMP (SparseMatrix< T > &input)

template<typename InputIterator >
InputIterator::value_type	OMP (InputIterator inputBegin, InputIterator inputEnd)

template<typename T >
T	CU (Vector< T > &input, int useNumGPU=1)

template<typename T >
T	CU (Matrix< T > &input, int useNumGPU=1)

template<typename T >
T	CU (SparseMatrix< T > &input, int useNumGPU=1)

template<typename InputIterator >
InputIterator::value_type	CU (InputIterator inputBegin, InputIterator inputEnd, int useNumGPU=1)

template<typename T >
T	CL (Vector< T > &input, int useNumGPU=1)

template<typename T >
T	CL (Matrix< T > &input, int useNumGPU=1)

template<typename T >
T	CL (SparseMatrix< T > &input, int useNumGPU=1)

template<typename T >
Vector< T >	CL (Matrix< T > &input, ReducePolicy reducePolicy, int useNumGPU=1)

template<typename T >
Vector< T >	CL (SparseMatrix< T > &input, ReducePolicy reducePolicy, int useNumGPU=1)

template<typename InputIterator >
InputIterator::value_type	CL (InputIterator inputBegin, InputIterator inputEnd, int useNumGPU=1)

template<typename T >
skepu::Vector< T >	CU (Matrix< T > &input, ReducePolicy reducePolicy, int useNumGPU)

template<typename T >
skepu::Vector< T >	CU (SparseMatrix< T > &input, ReducePolicy reducePolicy, int useNumGPU)

template<typename T >
skepu::Vector< T >	OMP (Matrix< T > &input, ReducePolicy reducePolicy)

template<typename T >
skepu::Vector< T >	OMP (SparseMatrix< T > &input, ReducePolicy reducePolicy)

Detailed Description

template<typename ReduceFunc>
class skepu::Reduce< ReduceFunc, ReduceFunc >

A specilalization of above class, used for 1D Reduce operation. Please note that the class name is same. The only difference is how you instantiate it either by passing 1 user function (i.e. 1D reduction) or 2 user function (i.e. 2D reduction). See code examples for more information.

Constructor & Destructor Documentation

template<typename ReduceFunc >

skepu::Reduce< ReduceFunc, ReduceFunc >::Reduce ( ReduceFunc * reduceFunc )

When creating an instance of the Reduce skeleton, a pointer to a binary user function must be provided. Also the Environment is set and if SKEPU_OPENCL is defined, the appropriate OpenCL program and kernel are created. Also creates a default execution plan which the skeleton will use if no other is specified.

Parameters

reduceFunc A pointer to a valid binary user function. Will be deleted in the destructor.

References skepu::ExecPlan::calibrated, and skepu::Environment< T >::getInstance().

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template<typename ReduceFunc >

skepu::Reduce< ReduceFunc, ReduceFunc >::~Reduce ( )

When the Reduce skeleton is destroyed, it deletes the user function it was created with.

Member Function Documentation

template<typename ReduceFunc >

template<typename T >

T skepu::Reduce< ReduceFunc, ReduceFunc >::CL	(	Vector< T > &	input,
		int	useNumGPU = `1`
	)

Performs the Reduction on a whole Vector. Returns a scalar result. A wrapper for CL(InputIterator inputBegin, InputIterator inputEnd, int useNumGPU). Using OpenCL as backend.

Parameters

input	A vector which the reduction will be performed on.
useNumGPU	Integer specifying how many devices to use. 0 = implementation decides.

Returns: The scalar result of the reduction performed.

References skepu::Vector< T >::begin(), skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CL(), and skepu::Vector< T >::end().

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template<typename ReduceFunc >

template<typename T >

T skepu::Reduce< ReduceFunc, ReduceFunc >::CL	(	Matrix< T > &	input,
		int	useNumGPU = `1`
	)

Performs the Reduction on a whole Matrix. Returns a scalar result. A wrapper for CL(InputIterator inputBegin, InputIterator inputEnd, int useNumGPU). Using OpenCL as backend.

Parameters

input	A matrix which the reduction will be performed on.
useNumGPU	Integer specifying how many devices to use. 0 = implementation decides.

Returns: The scalar result of the reduction performed.

References skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CL().

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template<typename ReduceFunc >

template<typename T >

T skepu::Reduce< ReduceFunc, ReduceFunc >::CL	(	SparseMatrix< T > &	input,
		int	useNumGPU = `1`
	)

Performs the Reduction on non-zero elements of a SparseMatrix. Returns a scalar result. Using OpenCL as backend.

Parameters

input	A sparse matrix which the reduction will be performed on.
useNumGPU	Integer specifying how many devices to use. 0 = implementation decides.

Returns: The scalar result of the reduction performed.

References skepu::DeviceMemPointer_CL< T >::changeDeviceData(), skepu::DeviceMemPointer_CL< T >::copyDeviceToHost(), skepu::SparseMatrix< T >::get_values(), skepu::DeviceMemPointer_CL< T >::getDeviceDataPointer(), skepu::getNumBlocksAndThreads(), MAX_GPU_DEVICES, skepu::printCLError(), skepu::SparseMatrix< T >::total_nnz(), and skepu::SparseMatrix< T >::updateDevice_CL().

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template<typename ReduceFunc >

template<typename T >

Vector< T > skepu::Reduce< ReduceFunc, ReduceFunc >::CL	(	Matrix< T > &	input,
		ReducePolicy	reducePolicy,
		int	useNumGPU = `1`
	)

Performs the Reduction, either row-wise or column-wise, on a Matrix. Returns a SkePU vector of reduction result. Using OpenCL as backend.

Parameters

input	A matrix which the reduction will be performed on.
reducePolicy	The policy specifying how reduction will be performed, can be either REDUCE_ROW_WISE_ONLY of REDUCE_COL_WISE_ONLY
useNumGPU	Integer specifying how many devices to use. 0 = implementation decides.

Returns: A skepu Vector containing reduction results either row-wise or column-wise depending upon supplied ReducePolicy.

References skepu::getNumBlocksAndThreads(), MAX_GPU_DEVICES, and skepu::Matrix< T >::size().

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template<typename ReduceFunc >

template<typename T >

Vector< T > skepu::Reduce< ReduceFunc, ReduceFunc >::CL	(	SparseMatrix< T > &	input,
		ReducePolicy	reducePolicy,
		int	useNumGPU = `1`
	)

Performs the Reduction on a whole SparseMatrix. Returns a SkePU vector of reduction result. Using OpenCL as backend.

Parameters

input	A sparse matrix which the reduction will be performed on.
reducePolicy	The policy specifying how reduction will be performed, can be either REDUCE_ROW_WISE_ONLY of REDUCE_COL_WISE_ONLY
useNumGPU	Integer specifying how many devices to use. 0 = implementation decides.

Returns: A skepu Vector containing reduction results either row-wise or column-wise depending upon supplied ReducePolicy.

References skepu::SparseMatrix< T >::begin(), skepu::SparseMatrix< T >::get_values(), skepu::DeviceMemPointer_CL< T >::getDeviceDataPointer(), skepu::getNumBlocksAndThreads(), MAX_GPU_DEVICES, skepu::SparseMatrix< T >::total_nnz(), skepu::SparseMatrix< T >::total_rows(), and skepu::SparseMatrix< T >::updateDevice_CL().

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template<typename ReduceFunc >

template<typename InputIterator >

InputIterator::value_type skepu::Reduce< ReduceFunc, ReduceFunc >::CL	(	InputIterator	inputBegin,
		InputIterator	inputEnd,
		int	useNumGPU = `1`
	)

Performs the Reduction on a range of elements. Returns a scalar result. The function decides whether to perform the reduction on one device, calling reduceSingle_CL(InputIterator inputBegin, InputIterator inputEnd, unsigned int deviceID) or on multiple devices, calling reduceNumDevices_CL(InputIterator inputBegin, InputIterator inputEnd, size_t numDevices). Using OpenCL as backend.

Parameters

inputBegin	An iterator to the first element in the range.
inputEnd	An iterator to the last element of the range.
useNumGPU	Integer specifying how many devices to use. 0 = implementation decides.

Returns: The scalar result of the reduction performed.

References skepu::DeviceMemPointer_CL< T >::getDeviceDataPointer(), skepu::getNumBlocksAndThreads(), MAX_GPU_DEVICES, and skepu::printCLError().

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template<typename ReduceFunc >

template<typename T >

T skepu::Reduce< ReduceFunc, ReduceFunc >::CPU ( Vector< T > & input )

Performs the Reduction on a whole Vector. Returns a scalar result. A wrapper for CPU(InputIterator inputBegin, InputIterator inputEnd). Using the CPU as backend.

Parameters

input A vector which the reduction will be performed on.

Returns: The scalar result of the reduction performed.

References skepu::Vector< T >::begin(), skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CPU(), and skepu::Vector< T >::end().

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template<typename ReduceFunc >

template<typename T >

T skepu::Reduce< ReduceFunc, ReduceFunc >::CPU ( Matrix< T > & input )

Performs the Reduction on a whole Matrix. Returns a scalar result. A wrapper for CPU(InputIterator inputBegin, InputIterator inputEnd). Using the CPU as backend.

Parameters

input A matrix which the reduction will be performed on.

Returns: The scalar result of the reduction performed.

References skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CPU().

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template<typename ReduceFunc >

template<typename T >

T skepu::Reduce< ReduceFunc, ReduceFunc >::CPU ( SparseMatrix< T > & input )

Performs the Reduction on non-zero elements of a SparseMatrix. Returns a scalar result. Using the CPU as backend.

Parameters

input A sparse matrix which the reduction will be performed on.

Returns: The scalar result of the reduction performed.

References skepu::SparseMatrix< T >::get_values(), skepu::SparseMatrix< T >::total_nnz(), and skepu::SparseMatrix< T >::updateHost().

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template<typename ReduceFunc >

template<typename T >

Vector< T > skepu::Reduce< ReduceFunc, ReduceFunc >::CPU	(	Matrix< T > &	input,
		ReducePolicy	reducePolicy
	)

Performs the Reduction on a whole Matrix either row-wise or column-wise. Returns a SkePU vector of reduction result. Using the CPU as backend.

Parameters

input	A matrix which the reduction will be performed on.
reducePolicy	The policy specifying how reduction will be performed, can be either REDUCE_ROW_WISE_ONLY of REDUCE_COL_WISE_ONLY

Returns: A skepu Vector containing reduction results either row-wise or column-wise depending upon supplied ReducePolicy.

template<typename ReduceFunc >

template<typename T >

Vector< T > skepu::Reduce< ReduceFunc, ReduceFunc >::CPU	(	SparseMatrix< T > &	input,
		ReducePolicy	reducePolicy
	)

Performs the Reduction on non-zero elements of a SparseMatrix either row-wise or column-wise. Returns a vector of reduction result. Using the CPU as backend.

Parameters

input	A matrix which the reduction will be performed on.
reducePolicy	The policy specifying how reduction will be performed, can be either REDUCE_ROW_WISE_ONLY of REDUCE_COL_WISE_ONLY

Returns: A skepu Vector containing reduction results either row-wise or column-wise depending upon supplied ReducePolicy.

References skepu::SparseMatrix< T >::begin(), skepu::SparseMatrix< T >::total_cols(), skepu::SparseMatrix< T >::total_nnz(), skepu::SparseMatrix< T >::total_rows(), and skepu::SparseMatrix< T >::updateHost().

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template<typename ReduceFunc >

template<typename InputIterator >

InputIterator::value_type skepu::Reduce< ReduceFunc, ReduceFunc >::CPU	(	InputIterator	inputBegin,
		InputIterator	inputEnd
	)

Performs the Reduction on a range of elements. Returns a scalar result. Does the reduction on the CPU by iterating over all elements in the range.

Parameters

inputBegin	An iterator to the first element in the range.
inputEnd	An iterator to the last element of the range.

Returns: The scalar result of the reduction performed.

template<typename ReduceFunc >

template<typename T >

T skepu::Reduce< ReduceFunc, ReduceFunc >::CU	(	Vector< T > &	input,
		int	useNumGPU = `1`
	)

Performs the Reduction on a whole Vector. Returns a scalar result. A wrapper for CU(InputIterator inputBegin, InputIterator inputEnd, int useNumGPU). Using CUDA as backend.

Parameters

input	A vector which the reduction will be performed on.
useNumGPU	Integer specifying how many devices to use. 0 = implementation decides.

Returns: The scalar result of the reduction performed.

References skepu::Vector< T >::begin(), skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CU(), and skepu::Vector< T >::end().

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template<typename ReduceFunc >

template<typename T >

T skepu::Reduce< ReduceFunc, ReduceFunc >::CU	(	Matrix< T > &	input,
		int	useNumGPU = `1`
	)

Performs the Reduction on a whole Matrix. Returns a scalar result. A wrapper for CU(InputIterator inputBegin, InputIterator inputEnd, int useNumGPU). Using CUDA as backend.

Parameters

input	A matrix which the reduction will be performed on.
useNumGPU	Integer specifying how many devices to use. 0 = implementation decides.

Returns: The scalar result of the reduction performed.

References skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CU().

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template<typename ReduceFunc >

template<typename T >

T skepu::Reduce< ReduceFunc, ReduceFunc >::CU	(	SparseMatrix< T > &	input,
		int	useNumGPU = `1`
	)

Performs the Reduction on non-zero elements of a SparseMatrix. Returns a scalar result. The function decides whether to perform the reduction on one device, calling reduceSingleThread_CU(SparseMatrix<T> &input, int deviceID) or on multiple devices, dividing the range of elements equally among the participating devices each reducing its part. The results are then reduced themselves on the CPU. Using CUDA as backend.

Parameters

input	A sparse matrix which the reduction will be performed on.
useNumGPU	Integer specifying how many devices to use. 0 = implementation decides.

Returns: The scalar result of the reduction performed.

References skepu::DeviceMemPointer_CU< T >::changeDeviceData(), skepu::DeviceMemPointer_CU< T >::copyDeviceToHost(), skepu::SparseMatrix< T >::get_values(), skepu::DeviceMemPointer_CU< T >::getDeviceDataPointer(), skepu::getNumBlocksAndThreads(), MAX_GPU_DEVICES, skepu::SparseMatrix< T >::total_nnz(), and skepu::SparseMatrix< T >::updateDevice_CU().

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template<typename ReduceFunc >

template<typename InputIterator >

InputIterator::value_type skepu::Reduce< ReduceFunc, ReduceFunc >::CU	(	InputIterator	inputBegin,
		InputIterator	inputEnd,
		int	useNumGPU = `1`
	)

Performs the Reduction on a range of elements. Returns a scalar result. The function decides whether to perform the reduction on one device, calling reduceSingleThread_CU(InputIterator inputBegin, InputIterator inputEnd, int deviceID) or on multiple devices, dividing the range of elements equally among the participating devices each reducing its part. The results are then reduced themselves on the CPU.

Parameters

inputBegin	An iterator to the first element in the range.
inputEnd	An iterator to the last element of the range.
useNumGPU	Integer specifying how many devices to use. 0 = implementation decides.

Returns: The scalar result of the reduction performed.

References skepu::getNumBlocksAndThreads(), and MAX_GPU_DEVICES.

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template<typename ReduceFunc >

template<typename T >

skepu::Vector<T> skepu::Reduce< ReduceFunc, ReduceFunc >::CU	(	Matrix< T > &	input,
		ReducePolicy	reducePolicy,
		int	useNumGPU
	)

Performs the Reduction on a whole Matrix either row-wise or column-wise. Returns a SkePU vector of reduction result. Using CUDA as backend.

Parameters

input	A matrix which the reduction will be performed on.
reducePolicy	The policy specifying how reduction will be performed, can be either REDUCE_ROW_WISE_ONLY of REDUCE_COL_WISE_ONLY
useNumGPU	Integer specifying how many devices to use. 0 = implementation decides.

Returns: A skepu Vector containing reduction results either row-wise or column-wise depending upon supplied ReducePolicy.

References skepu::Device_CU::getNoConcurrentKernels(), skepu::getNumBlocksAndThreads(), and MAX_GPU_DEVICES.

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template<typename ReduceFunc >

template<typename T >

skepu::Vector<T> skepu::Reduce< ReduceFunc, ReduceFunc >::CU	(	SparseMatrix< T > &	input,
		ReducePolicy	reducePolicy,
		int	useNumGPU
	)

Performs the Reduction, either row-wise or column-wise, on non-zero elements of a SparseMatrix. Returns a SkePU vector of reduction result. Using CUDA as backend.

Parameters

input	A sparse matrix which the reduction will be performed on.
reducePolicy	The policy specifying how reduction will be performed, can be either REDUCE_ROW_WISE_ONLY of REDUCE_COL_WISE_ONLY
useNumGPU	Integer specifying how many devices to use. 0 = implementation decides.

Returns: A skepu Vector containing reduction results either row-wise or column-wise depending upon supplied ReducePolicy.

References skepu::SparseMatrix< T >::begin(), skepu::SparseMatrix< T >::get_values(), skepu::DeviceMemPointer_CU< T >::getDeviceDataPointer(), skepu::Device_CU::getNoConcurrentKernels(), skepu::getNumBlocksAndThreads(), MAX_GPU_DEVICES, skepu::SparseMatrix< T >::total_nnz(), skepu::SparseMatrix< T >::total_rows(), and skepu::SparseMatrix< T >::updateDevice_CU().

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template<typename ReduceFunc >

template<typename T >

skepu::Vector<T> skepu::Reduce< ReduceFunc, ReduceFunc >::OMP	(	Matrix< T > &	input,
		ReducePolicy	reducePolicy
	)

Performs the Reduction on a whole Matrix. Returns a SkePU vector of reduction result. Using OpenMP as backend.

Parameters

input	A matrix which the reduction will be performed on.
reducePolicy	The policy specifying how reduction will be performed, can be either REDUCE_ROW_WISE_ONLY of REDUCE_COL_WISE_ONLY

Returns: A skepu Vector containing reduction results either row-wise or column-wise depending upon supplied ReducePolicy.

template<typename ReduceFunc >

template<typename T >

skepu::Vector<T> skepu::Reduce< ReduceFunc, ReduceFunc >::OMP	(	SparseMatrix< T > &	input,
		ReducePolicy	reducePolicy
	)

Performs the Reduction on non-zero elements of a SparseMatrix. Returns a SkePU vector of reduction result. Using OpenMP as backend. Can apply two different algorithms depending upon whether the workload is regular or irregular across different rows.

Parameters

input	A matrix which the reduction will be performed on.
reducePolicy	The policy specifying how reduction will be performed, can be either REDUCE_ROW_WISE_ONLY of REDUCE_COL_WISE_ONLY

Returns: A skepu Vector containing reduction results either row-wise or column-wise depending upon supplied ReducePolicy.

References skepu::SparseMatrix< T >::total_nnz(), skepu::SparseMatrix< T >::total_rows(), and skepu::SparseMatrix< T >::updateHost().

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template<typename ReduceFunc >

template<typename T >

T skepu::Reduce< ReduceFunc, ReduceFunc >::OMP ( Vector< T > & input )

Performs the Reduction on a whole Vector. Returns a scalar result. A wrapper for OMP(InputIterator inputBegin, InputIterator inputEnd). Using OpenMP as backend.

Parameters

input A vector which the reduction will be performed on.

Returns: The scalar result of the reduction performed.

References skepu::Vector< T >::begin(), skepu::Vector< T >::end(), and skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::OMP().

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template<typename ReduceFunc >

template<typename T >

T skepu::Reduce< ReduceFunc, ReduceFunc >::OMP ( Matrix< T > & input )

Performs the Reduction on a whole Matrix. Returns a scalar result. A wrapper for OMP(InputIterator inputBegin, InputIterator inputEnd). Using OpenMP as backend.

Parameters

input A matrix which the reduction will be performed on.

Returns: The scalar result of the reduction performed.

References skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::OMP().

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template<typename ReduceFunc >

template<typename T >

T skepu::Reduce< ReduceFunc, ReduceFunc >::OMP ( SparseMatrix< T > & input )

Performs the Reduction on non-zero elements of a SparseMatrix. Returns a scalar result. Using OpenMP as backend.

Parameters

input A sparse matrix which the reduction will be performed on.

Returns: The scalar result of the reduction performed.

References skepu::SparseMatrix< T >::get_values(), skepu::SparseMatrix< T >::total_nnz(), and skepu::SparseMatrix< T >::updateHost().

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template<typename ReduceFunc >

template<typename InputIterator >

InputIterator::value_type skepu::Reduce< ReduceFunc, ReduceFunc >::OMP	(	InputIterator	inputBegin,
		InputIterator	inputEnd
	)

Performs the Reduction on a range of elements. Returns a scalar result. Divides the elements among all OpenMP threads and does reduction of the parts in parallel. The results from each thread are then reduced on the CPU.

Parameters

inputBegin	An iterator to the first element in the range.
inputEnd	An iterator to the last element of the range.

Returns: The scalar result of the reduction performed.

template<typename ReduceFunc >

template<typename T >

T skepu::Reduce< ReduceFunc, ReduceFunc >::operator() ( Vector< T > & input )

Performs the Reduction on a Vector. Returns a scalar result.

Depending on which backend was used, different versions of the skeleton is called. If SKEPU_CUDA is defined, the CUDA backend is used, similarly if SKEPU_OPENCL or SKEPU_OPENMP are defined then the OpenCL or OpenMP backend is used. As a fallback there is always a CPU version.

Parameters

input A vector which the reduction will be performed on.

Returns: The scalar result of the reduction performed.

References skepu::ExecPlan::calibrated, skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CL(), skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CPU(), skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CU(), skepu::Vector< T >::isModified_CU(), skepu::Vector< T >::isVectorOnDevice_CU(), skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::OMP(), and skepu::Vector< T >::size().

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template<typename ReduceFunc >

template<typename T >

T skepu::Reduce< ReduceFunc, ReduceFunc >::operator() ( Matrix< T > & input )

Performs the Reduction on a Matrix. Returns a scalar result.

Depending on which backend was used, different versions of the skeleton is called. If SKEPU_CUDA is defined, the CUDA backend is used, similarly if SKEPU_OPENCL or SKEPU_OPENMP are defined then the OpenCL or OpenMP backend is used. As a fallback there is always a CPU version.

Parameters

input A matrix which the reduction will be performed on.

Returns: The scalar result of the reduction performed.

References skepu::ExecPlan::calibrated, skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CL(), skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CPU(), skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CU(), and skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::OMP().

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template<typename ReduceFunc >

template<typename T >

T skepu::Reduce< ReduceFunc, ReduceFunc >::operator() ( SparseMatrix< T > & input )

Performs the Reduction on non-zero elements of a SparseMatrix. Returns a scalar result.

Depending on which backend was used, different versions of the skeleton is called. If SKEPU_CUDA is defined, the CUDA backend is used, similarly if SKEPU_OPENCL or SKEPU_OPENMP are defined then the OpenCL or OpenMP backend is used. As a fallback there is always a CPU version.

Parameters

input A sparse matrix which the reduction will be performed on.

Returns: The scalar result of the reduction performed.

References skepu::ExecPlan::calibrated, skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CL(), skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CPU(), skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CU(), skepu::SparseMatrix< T >::isModified_CU(), skepu::SparseMatrix< T >::isSparseMatrixOnDevice_CU(), skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::OMP(), and skepu::SparseMatrix< T >::total_nnz().

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template<typename ReduceFunc >

template<typename T >

Vector< T > skepu::Reduce< ReduceFunc, ReduceFunc >::operator()	(	Matrix< T > &	input,
		ReducePolicy	reducePolicy
	)

Performs the Reduction on a Matrix either row or column-wise. Returns a skepu Vector containing reduction results either row-wise or column-wise depending upon supplied ReducePolicy.

Depending on which backend was used, different versions of the skeleton is called. If SKEPU_CUDA is defined, the CUDA backend is used, similarly if SKEPU_OPENCL or SKEPU_OPENMP are defined then the OpenCL or OpenMP backend is used. As a fallback there is always a CPU version.

Parameters

input	A matrix which the reduction will be performed on.
reducePolicy	The policy specifying how reduction will be performed, can be either REDUCE_ROW_WISE_ONLY of REDUCE_COL_WISE_ONLY

Returns: A skepu Vector containing reduction results either row-wise or column-wise depending upon supplied ReducePolicy.

References skepu::ExecPlan::calibrated, skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CL(), skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CPU(), skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CU(), and skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::OMP().

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template<typename ReduceFunc >

template<typename T >

Vector< T > skepu::Reduce< ReduceFunc, ReduceFunc >::operator()	(	SparseMatrix< T > &	input,
		ReducePolicy	reducePolicy
	)

Performs the Reduction on non-zero elements of a sparse Matrix either row or column-wise. Returns a skepu Vector containing reduction results either row-wise or column-wise depending upon supplied ReducePolicy.

Depending on which backend was used, different versions of the skeleton is called. If SKEPU_CUDA is defined, the CUDA backend is used, similarly if SKEPU_OPENCL or SKEPU_OPENMP are defined then the OpenCL or OpenMP backend is used. As a fallback there is always a CPU version.

Parameters

input	A sparse matrix which the reduction will be performed on.
reducePolicy	The policy specifying how reduction will be performed, can be either REDUCE_ROW_WISE_ONLY of REDUCE_COL_WISE_ONLY

Returns: A skepu Vector containing reduction results either row-wise or column-wise depending upon supplied ReducePolicy.

References skepu::ExecPlan::calibrated, skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CL(), skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CPU(), skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CU(), skepu::SparseMatrix< T >::isModified_CU(), skepu::SparseMatrix< T >::isSparseMatrixOnDevice_CU(), skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::OMP(), and skepu::SparseMatrix< T >::total_nnz().

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template<typename ReduceFunc >

template<typename InputIterator >

InputIterator::value_type skepu::Reduce< ReduceFunc, ReduceFunc >::operator()	(	InputIterator	inputBegin,
		InputIterator	inputEnd
	)

Performs the Reduction on a range of elements. Returns a scalar result.

Depending on which backend was used, different versions of the skeleton is called. If SKEPU_CUDA is defined, the CUDA backend is used, similarly if SKEPU_OPENCL or SKEPU_OPENMP are defined then the OpenCL or OpenMP backend is used. As a fallback there is always a CPU version.

Parameters

inputBegin	An iterator to the first element in the range.
inputEnd	An iterator to the last element of the range.

Returns: The scalar result of the reduction performed.

References skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CL(), skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CPU(), skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::CU(), and skepu::Reduce< ReduceFuncRowWise, ReduceFuncColWise >::OMP().

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The documentation for this class was generated from the following files:

include/skepu/reduce.h
include/skepu/src/reduce.inl
include/skepu/src/reduce_cl.inl
include/skepu/src/reduce_cpu.inl
include/skepu/src/reduce_cu.inl
include/skepu/src/reduce_omp.inl

Public Member Functions

Detailed Description

template<typename ReduceFunc> class skepu::Reduce< ReduceFunc, ReduceFunc >

Constructor & Destructor Documentation

Member Function Documentation

template<typename ReduceFunc>
class skepu::Reduce< ReduceFunc, ReduceFunc >