svm_kernel.cl File Reference

Defines the kernel functions for the C-SVM using the CUDA backend. More...

Functions
__kernel void	device_kernel_linear (__global const real_type *q, __global real_type *ret, __global const real_type *d, __global const real_type *data_d, const real_type QA_cost, const real_type cost, const kernel_index_type num_rows, const kernel_index_type feature_range, const real_type add, const kernel_index_type id)
	Calculates the C-SVM kernel using the linear kernel function. More...
__kernel void	device_kernel_polynomial (__global const real_type *q, __global real_type *ret, __global const real_type *d, __global const real_type *data_d, const real_type QA_cost, const real_type cost, const kernel_index_type num_rows, const kernel_index_type num_cols, const real_type add, const int degree, const real_type gamma, const real_type coef0)
	Calculates the C-SVM kernel using the polynomial kernel function. More...
__kernel void	device_kernel_rbf (__global const real_type *q, __global real_type *ret, __global const real_type *d, __global const real_type *data_d, const real_type QA_cost, const real_type cost, const kernel_index_type num_rows, const kernel_index_type num_cols, const real_type add, const real_type gamma)
	Calculates the C-SVM kernel using the radial basis function kernel function. More...

Detailed Description

Defines the kernel functions for the C-SVM using the CUDA backend.

Author

Alexander Van Craen

Marcel Breyer

Copyright

2018-today The PLSSVM project - All Rights Reserved

License

This file is part of the PLSSVM project which is released under the MIT license. See the LICENSE.md file in the project root for full license information.

Function Documentation

device_kernel_linear()

__kernel void device_kernel_linear	(	__global const real_type *	q,
		__global real_type *	ret,
		__global const real_type *	d,
		__global const real_type *	data_d,
		const real_type	QA_cost,
		const real_type	cost,
		const kernel_index_type	num_rows,
		const kernel_index_type	feature_range,
		const real_type	add,
		const kernel_index_type	id
	)

Calculates the C-SVM kernel using the linear kernel function.

Supports multi-GPU execution.

Template Parameters

real_type

the type of the data

Parameters

[in]	q	the q vector
[out]	ret	the result vector
[in]	d	the right-hand side of the equation
[in]	data_d	the one-dimension data matrix
[in]	QA_cost	the bottom right matrix entry multiplied by cost
[in]	cost	1 / the cost parameter in the C-SVM
[in]	num_rows	the number of columns in the data matrix
[in]	feature_range	number of features used for the calculation on the device id
[in]	add	denotes whether the values are added or subtracted from the result vector
[in]	id	the id of the current device

device_kernel_polynomial()

__kernel void device_kernel_polynomial	(	__global const real_type *	q,
		__global real_type *	ret,
		__global const real_type *	d,
		__global const real_type *	data_d,
		const real_type	QA_cost,
		const real_type	cost,
		const kernel_index_type	num_rows,
		const kernel_index_type	num_cols,
		const real_type	add,
		const int	degree,
		const real_type	gamma,
		const real_type	coef0
	)

Calculates the C-SVM kernel using the polynomial kernel function.

Currently only single GPU execution is supported.

Template Parameters

real_type

the type of the data

Parameters

[in]	q	the q vector
[out]	ret	the result vector
[in]	d	the right-hand side of the equation
[in]	data_d	the one-dimension data matrix
[in]	QA_cost	he bottom right matrix entry multiplied by cost
[in]	cost	1 / the cost parameter in the C-SVM
[in]	num_rows	the number of columns in the data matrix
[in]	num_cols	the number of rows in the data matrix
[in]	add	denotes whether the values are added or subtracted from the result vector
[in]	degree	the degree parameter used in the polynomial kernel function
[in]	gamma	the gamma parameter used in the polynomial kernel function
[in]	coef0	the coef0 parameter used in the polynomial kernel function

device_kernel_rbf()

__kernel void device_kernel_rbf	(	__global const real_type *	q,
		__global real_type *	ret,
		__global const real_type *	d,
		__global const real_type *	data_d,
		const real_type	QA_cost,
		const real_type	cost,
		const kernel_index_type	num_rows,
		const kernel_index_type	num_cols,
		const real_type	add,
		const real_type	gamma
	)

Calculates the C-SVM kernel using the radial basis function kernel function.

Currently only single GPU execution is supported.

Template Parameters

real_type

the type of the data

Parameters

[in]	q	the q vector
[out]	ret	the result vector
[in]	d	the right-hand side of the equation
[in]	data_d	the one-dimension data matrix
[in]	QA_cost	he bottom right matrix entry multiplied by cost
[in]	cost	1 / the cost parameter in the C-SVM
[in]	num_rows	the number of columns in the data matrix
[in]	num_cols	the number of rows in the data matrix
[in]	add	denotes whether the values are added or subtracted from the result vector
[in]	gamma	the gamma parameter used in the rbf kernel function