cpu.c File Reference

#include "include/cpu.h"
#include "include/base.h"
#include "include/util.h"
#include "include/global.h"

Include dependency graph for cpu.c:

Functions
void	init_cpu (BRUTE_RECORD *brute_record, BRUTE_PARAMETERS *params)
void	fit_cpu (FLOAT_TYPE *Xtrain, int nXtrain, int dXtrain, BRUTE_RECORD *brute_record, BRUTE_PARAMETERS *params)
void	free_resources_cpu (BRUTE_RECORD *brute_record, BRUTE_PARAMETERS *params)
void	neighbors_cpu (FLOAT_TYPE *Xtest, int nXtest, int dXtest, FLOAT_TYPE *d_mins, int *idx_mins, BRUTE_RECORD *brute_record, BRUTE_PARAMETERS *params)
void	compute_neighbors_single_instance_cpu (FLOAT_TYPE *Xtrain, int nXtrain, int dim, FLOAT_TYPE *test_pattern, FLOAT_TYPE *d_min, int *idx_min, int K)
FLOAT_TYPE	squared_dist_cpu (FLOAT_TYPE *a, FLOAT_TYPE *b, int dim)
void	insert_cpu (FLOAT_TYPE pattern_dist, int pattern_idx, FLOAT_TYPE *nearest_dist, int *nearest_idx, int K)

Function Documentation

void compute_neighbors_single_instance_cpu	(	FLOAT_TYPE *	Xtrain,
		int	nXtrain,
		int	dim,
		FLOAT_TYPE *	test_pattern,
		FLOAT_TYPE *	d_min,
		int *	idx_min,
		int	K
	)

Computes nearest neighbors for a single test instance.

Parameters

*Xtrain	Training patterns
nXtrain	Number of training patterns
dim	Dimensionality of training patterns
*test_pattern	Test pattern
*d_min	Pointer to array that shall be used to store the distances
*idx_min	Pointer ot array that shall be used to store the indices
K	The number of neighbors

void fit_cpu	(	FLOAT_TYPE *	Xtrain,
		int	nXtrain,
		int	dXtrain,
		BRUTE_RECORD *	brute_record,
		BRUTE_PARAMETERS *	params
	)

Fits a model given the training data (and parameters)

Parameters

*Xtrain	Training patterns
nXtrain	Number of training patterns
dXtrain	Dimensionality of training patterns
*brute_record	Pointer to record storing the model
*params	Pointer to struct storing the parameters

void free_resources_cpu	(	BRUTE_RECORD *	brute_record,
		BRUTE_PARAMETERS *	params
	)

Does some clean up (before exiting the program).

Parameters

*brute_record	Pointer to record storing the model
*params	Pointer to struct storing the parameters

void init_cpu	(	BRUTE_RECORD *	brute_record,
		BRUTE_PARAMETERS *	params
	)

Intializes components if needed.

Parameters

*brute_record	Pointer to record storing the model
*params	Pointer to struct storing the parameters

void insert_cpu	(	FLOAT_TYPE	pattern_dist,
		int	pattern_idx,
		FLOAT_TYPE *	nearest_dist,
		int *	nearest_idx,
		int	K
	)

Inserts the value pattern_dist with index pattern_idx in the list nearest_dist of FLOAT_TYPEs and the list nearest_idx of indices. Both lists contain at most K elements.

Parameters

pattern_dist	Distance to the current pattern
pattern_idx	Associated index
*nearest_dist	Array of distances to be updated
*nearest_idx	Arra of indices to be updated
K	Number of nearest neighbors

void neighbors_cpu	(	FLOAT_TYPE *	Xtest,
		int	nXtest,
		int	dXtest,
		FLOAT_TYPE *	d_mins,
		int *	idx_mins,
		BRUTE_RECORD *	brute_record,
		BRUTE_PARAMETERS *	params
	)

Computes the neighbors (for test patterns)

Parameters

*Xtest	Pointer to the set of query/test points (stored as FLOAT_TYPE)
nXtest	The number of query points
dXtest	The dimension of each query point
*d_mins	The distances array (FLOAT_TYPE) used to store the computed distances
*idx_mins	Pointer to arrray storing the indices of the k nearest neighbors for each query point
*brute_record	Pointer to struct storing all relevant information for model
*params	Pointer to struct containing all relevant parameters

FLOAT_TYPE squared_dist_cpu ( FLOAT_TYPE *  a, FLOAT_TYPE *  b, int  dim  )

inline

Computes the distance between point a and b in R^dim

Parameters

*a	Pointer to first point
*b	Pointer to second point
dim	Dimensionality of the points