tensor_operations_on_device.cu File Reference

Source file defining tensor operations that happen on device. More...

#include "tensor_operations_on_device.cuh"
#include <cmath>
#include <exceptions/unexpected_cuda_call_exception.h>
#include <gpu/assert.cuh>

Macros
#define	TILE_WIDTH   16
	Size of a tile when performing tiled matrix multiplication.

Functions
__global__ void	sumTensorKernel (const float *a, float *destination, size_t size, size_t n)
__global__ void	fillTensorKernel (float *tensor, float value, size_t size)
	Kernel method to fill a tensor with a value. More...
__global__ void	fillTensorKernel (float *tensor, const float *value, size_t size)
__global__ void	addTensorsKernel (const float *a, const float *b, float *destination, size_t size)
	Kernel method to add two tensors together. More...
__global__ void	addBroadcastKernel (const float *matrix, const float *vector, float *destination, size_t n, size_t m)
	Kernel method to perform broadcast-add operation. More...
__global__ void	subtractTensorsKernel (const float *a, const float *b, float *destination, size_t size)
	Kernel method to perform tensor subtraction. More...
__global__ void	mulMatrixVectorKernel (const float *matrix, const float *vector, float *destination, size_t n, size_t m)
	Kernel method to perform matrix-vector multiplication. More...
__global__ void	multiplyMatricesTilingKernel (const float *m1, const float *m2, float *destination, size_t n, size_t m, size_t k)
	Kernel method to multiply two matrices using a tiling method. More...
__global__ void	multiplyMatricesNoTilingKernel (const float *m1, const float *m2, float *destination, size_t n, size_t m, size_t k)
	Kernel method to perform naive matrix-matrix multiplication. More...
__global__ void	multiplyTensorKernel (const float *tensor, float constant, float *destination, size_t size)
	Kernel method to multiply a tensor with a constant. More...
__global__ void	hadamardTensorsKernel (const float *a, const float *b, float *destination, size_t size)
	Kernel method to apply hadamard product to two tensors. More...
__global__ void	divideTensorsKernel (const float *a, const float *b, float *destination, size_t size)
	Kernel method to element-wise divide one tensor by another. More...
__global__ void	logTensorKernel (const float *a, float *destination, size_t size)
	Kernel method to apply the natural logarithm to each element of the tensor. More...
__global__ void	transposeMatrixKernel (const float *matrix, float *destination, size_t n, size_t m)
	Kernel method to transpose a matrix. More...
__global__ void	reluKernel (const float *input, float *result, size_t size)
__global__ void	reluDerivativeKernel (const float *output, float *result, size_t size)
__global__ void	sigmoidKernel (float *input, float *result, size_t size)
void	sumTensorOnDevice (const Tensor &tensor, Tensor &destination)
void	fillTensorOnDevice (Tensor &tensor, float value)
	Fill a tensor with a constant value. More...
void	fillTensorOnDevice (Tensor &tensor, const Tensor &value)
void	addTensorsOnDevice (const Tensor &a, const Tensor &b, Tensor &destination)
	Element-wise add two tensors. More...
void	subtractTensorsOnDevice (const Tensor &a, const Tensor &b, Tensor &destination)
	Subtract one tensor from another. More...
void	hadamardTensorsOnDevice (const Tensor &a, const Tensor &b, Tensor &destination)
	Perform hadamard product (element-wise multiplication) between two tensors. More...
void	divideTensorsOnDevice (const Tensor &a, const Tensor &b, Tensor &destination)
	Divide one tensor by another. More...
void	logTensorOnDevice (const Tensor &a, Tensor &destination)
	Apply natural logarithm to each element of the tensor. More...
void	addBroadcastOnDevice (const Tensor &matrix, const Tensor &vector, Tensor &destination)
	Perform the broadcast-add operation. More...
void	multiplyTensorOnDevice (const Tensor &tensor, float constant, Tensor &destination)
	Multiply a tensor with a constant. More...
void	multiplyMatrixVectorOnDevice (const Tensor &matrix, const Tensor &vector, Tensor &destination)
	Multiply a matrix with a vector. More...
void	multiplyMatrixMatrixOnDevice (const Tensor &m1, const Tensor &m2, Tensor &destination)
	Multiply a matrix with a matrix. More...
void	transposeMatrixOnDevice (const Tensor &matrix, Tensor &destination)
	Transpose a matrix. More...
void	reluTensorOnDevice (const Tensor &tensor, Tensor &destination)
void	reluDerivativeTensorOnDevice (const Tensor &tensor, Tensor &destination)
void	sigmoidTensorOnDevice (const Tensor &tensor, Tensor &destination)

Detailed Description

Source file defining tensor operations that happen on device.

Author

Jan Warchocki

Date

29 August 2022

Function Documentation

addBroadcastKernel()

__global__ void addBroadcastKernel	(	const float *	matrix,
		const float *	vector,
		float *	destination,
		size_t	n,
		size_t	m
	)

Kernel method to perform broadcast-add operation.

Parameters

matrix	The data of the matrix.
vector	The data of the vector to broadcast.
destination	Where the result of the operation should be stored.
n	The number of rows of the matrix.
m	The number of columns of the matrix. Same as the size of the vector.

addBroadcastOnDevice()

void addBroadcastOnDevice	(	const Tensor &	matrix,
		const Tensor &	vector,
		Tensor &	destination
	)

Perform the broadcast-add operation.

Parameters

matrix	The matrix tensor.
vector	The vector tensor.
destination	Where the result of the addition should be stored.

addTensorsKernel()

__global__ void addTensorsKernel	(	const float *	a,
		const float *	b,
		float *	destination,
		size_t	size
	)

Kernel method to add two tensors together.

Parameters

a	The data of the first tensor.
b	The data of the second tensor.
destination	Where the result of the operation should be stored.
size	The size of the tensors.

addTensorsOnDevice()

void addTensorsOnDevice	(	const Tensor &	a,
		const Tensor &	b,
		Tensor &	destination
	)

Element-wise add two tensors.

Parameters

a	The first tensor.
b	The second tensor.
destination	Where the result of the addition should be stored.

divideTensorsKernel()

__global__ void divideTensorsKernel	(	const float *	a,
		const float *	b,
		float *	destination,
		size_t	size
	)

Kernel method to element-wise divide one tensor by another.

Parameters

a	The data of the first tensor.
b	The data of the second tensor.
destination	Where the result of the division should be stored.
size	The size of the tensors.

divideTensorsOnDevice()

void divideTensorsOnDevice	(	const Tensor &	a,
		const Tensor &	b,
		Tensor &	destination
	)

Divide one tensor by another.

Parameters

a	The tensor to divide.
b	The tensor to divide by.
destination	Where the result of the operation should be stored.

fillTensorKernel()

__global__ void fillTensorKernel	(	float *	tensor,
		float	value,
		size_t	size
	)

Kernel method to fill a tensor with a value.

Parameters

tensor	The tensor to fill.
value	The value to fill the tensor with.
size	The size of the tensor.

fillTensorOnDevice()

void fillTensorOnDevice	(	Tensor &	tensor,
		float	value
	)

Fill a tensor with a constant value.

Parameters

tensor	The tensor to fill.
value	The value to fill the tensor with.

hadamardTensorsKernel()

__global__ void hadamardTensorsKernel	(	const float *	a,
		const float *	b,
		float *	destination,
		size_t	size
	)

Kernel method to apply hadamard product to two tensors.

Parameters

a	The data of the first tensor.
b	The data of the second tensor.
destination	Where the result of the hadamard operation should be stored.
size	The size of the tensors.

hadamardTensorsOnDevice()

void hadamardTensorsOnDevice	(	const Tensor &	a,
		const Tensor &	b,
		Tensor &	destination
	)

Perform hadamard product (element-wise multiplication) between two tensors.

Parameters

a	The first tensor.
b	The second tensor.
destination	Where the result of the operation should be stored.

logTensorKernel()

__global__ void logTensorKernel	(	const float *	a,
		float *	destination,
		size_t	size
	)

Kernel method to apply the natural logarithm to each element of the tensor.

Parameters

a	The data of the tensor to apply natural logarithm to.
destination	Where the result of the natural logarithm should be stored.
size	The size of the tensor.

logTensorOnDevice()

void logTensorOnDevice	(	const Tensor &	a,
		Tensor &	destination
	)

Apply natural logarithm to each element of the tensor.

Parameters

a	The tensor to apply natural logarithm to.
destination	Where the result of the operation should be stored.

mulMatrixVectorKernel()

__global__ void mulMatrixVectorKernel	(	const float *	matrix,
		const float *	vector,
		float *	destination,
		size_t	n,
		size_t	m
	)

Kernel method to perform matrix-vector multiplication.

Parameters

matrix	The data of the matrix to multiply.
vector	The data of the vector to multiply.
destination	Where the result of the operation should be stored.
n	The number of rows of the matrix.
m	The number of columns of the matrix. Same as the size of the vector.

multiplyMatricesNoTilingKernel()

__global__ void multiplyMatricesNoTilingKernel	(	const float *	m1,
		const float *	m2,
		float *	destination,
		size_t	n,
		size_t	m,
		size_t	k
	)

Kernel method to perform naive matrix-matrix multiplication.

Parameters

m1	The data of the first matrix.
m2	The data of the second matrix.
destination	Where the result of the operation should be stored.
n	The number of rows of the first matrix.
m	The number of columns of the first matrix.
k	The number of columns of the second matrix.

multiplyMatricesTilingKernel()

__global__ void multiplyMatricesTilingKernel	(	const float *	m1,
		const float *	m2,
		float *	destination,
		size_t	n,
		size_t	m,
		size_t	k
	)

Kernel method to multiply two matrices using a tiling method.

This method currently is not used to perform matrix-matrix multiplication for performance reasons.

Parameters

m1	The data of the first matrix.
m2	The data of the second matrix.
destination	Where the result of the operation should be stored.
n	The number of rows of the first matrix.
m	The number of columns of the first matrix.
k	The number of columns of the second matrix.

multiplyMatrixMatrixOnDevice()

void multiplyMatrixMatrixOnDevice	(	const Tensor &	m1,
		const Tensor &	m2,
		Tensor &	destination
	)

Multiply a matrix with a matrix.

Parameters

m1	The first matrix tensor.
m2	The second matrix tensor.
destination	Where the result of the multiplication should be stored.

multiplyMatrixVectorOnDevice()

void multiplyMatrixVectorOnDevice	(	const Tensor &	matrix,
		const Tensor &	vector,
		Tensor &	destination
	)

Multiply a matrix with a vector.

Parameters

matrix	The matrix tensor.
vector	The vector tensor.
destination	Where the result of the multiplication should be stored.

multiplyTensorKernel()

__global__ void multiplyTensorKernel	(	const float *	tensor,
		float	constant,
		float *	destination,
		size_t	size
	)

Kernel method to multiply a tensor with a constant.

Parameters

tensor	The data of the tensor to multiply.
constant	The constant to multiply tensor with.
destination	Where the result of the operation should be stored.
size	The size of the tensor.

multiplyTensorOnDevice()

void multiplyTensorOnDevice	(	const Tensor &	tensor,
		float	constant,
		Tensor &	destination
	)

Multiply a tensor with a constant.

Parameters

tensor	The tensor to multiply.
constant	The constant to multiply with.
destination	Where the result of the multiplication should be stored.

subtractTensorsKernel()

__global__ void subtractTensorsKernel	(	const float *	a,
		const float *	b,
		float *	destination,
		size_t	size
	)

Kernel method to perform tensor subtraction.

Parameters

a	The data of the tensor to subtract from.
b	The data of the tensor to be subtracted.
destination	Where the result of the operation should be stored.
size	The size of the tensors.

subtractTensorsOnDevice()

void subtractTensorsOnDevice	(	const Tensor &	a,
		const Tensor &	b,
		Tensor &	destination
	)

Subtract one tensor from another.

Parameters

a	The tensor to subtract from.
b	The tensor to be subtracted.
destination	Where the result of the subtraction should be stored.

transposeMatrixKernel()

__global__ void transposeMatrixKernel	(	const float *	matrix,
		float *	destination,
		size_t	n,
		size_t	m
	)

Kernel method to transpose a matrix.

Parameters

matrix	The data of the matrix to transpose.
destination	Where the result of the transpose operation should be stored.
n	The number of rows of matrix.
m	The number of columns of matrix.

transposeMatrixOnDevice()

void transposeMatrixOnDevice	(	const Tensor &	matrix,
		Tensor &	destination
	)

Transpose a matrix.

Parameters

matrix	The matrix vector to transpose.
destination	Where the result of the transpose operation should be stored.