PLSSVM - Parallel Least Squares Support Vector Machine  2.0.0
A Least Squares Support Vector Machine implementation using different backends.
Public Types | Public Member Functions | List of all members
plssvm::sycl::detail::device_kernel_w_linear< T > Class Template Reference

Calculate the w vector to speed up the prediction of the labels for data points using the linear kernel function. More...

#include <predict_kernel.hpp>

Public Types

using real_type = T
 The type of the data.
 

Public Member Functions

 device_kernel_w_linear (real_type *w_d, const real_type *data_d, const real_type *data_last_d, const real_type *alpha_d, const kernel_index_type num_data_points, const kernel_index_type num_features)
 Construct a new device kernel generating the w vector used to speedup the prediction when using the linear kernel function. More...
 
void operator() (::sycl::id< 1 > index) const
 Function call operator overload performing the actual calculation. More...
 

Detailed Description

template<typename T>
class plssvm::sycl::detail::device_kernel_w_linear< T >

Calculate the w vector to speed up the prediction of the labels for data points using the linear kernel function.

Supports multi-GPU execution.

Template Parameters
Tthe type of the data

Constructor & Destructor Documentation

◆ device_kernel_w_linear()

template<typename T >
plssvm::sycl::detail::device_kernel_w_linear< T >::device_kernel_w_linear ( real_type w_d,
const real_type data_d,
const real_type data_last_d,
const real_type alpha_d,
const kernel_index_type  num_data_points,
const kernel_index_type  num_features 
)
inline

Construct a new device kernel generating the w vector used to speedup the prediction when using the linear kernel function.

Currently only single GPU execution is supported.

Parameters
[out]w_dthe w vector to assemble
[in]data_dthe one-dimension support vector matrix
[in]data_last_dthe last row of the support vector matrix
[in]alpha_dthe previously calculated weight for each data point
[in]num_data_pointsthe total number of support vectors
[in]num_featuresthe number of features per support vector

Member Function Documentation

◆ operator()()

template<typename T >
void plssvm::sycl::detail::device_kernel_w_linear< T >::operator() ( ::sycl::id< 1 >  index) const
inline

Function call operator overload performing the actual calculation.

Parameters
[in]indexthe sycl::id identifying an instance of the functor executing at each point in a sycl::range

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