mlsa_cpu.c File Reference

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Functions
int	dmlsa_cpu (const int m, const int n, const int k, const double *A, double *W, double *H, const int uType, const int nIter)
	dmlsa_cpu performs NNMF using betadivergence when beta=2 using double precision More...
int	smlsa_cpu (const int m, const int n, const int k, const float *A, float *W, float *H, const int uType, const int nIter)
	smlsa_cpu performs NNMF using betadivergence when beta=2 using simple precision More...
void	ddotdiv_x86 (const int n, const double *x, const double *y, double *__restrict__ z)
	This function calls the appropiate funtions to performs double precision element-wise z[i]=z[i]*x[i]/y[i] for all positions of x, y and z. More...
void	sdotdiv_x86 (const int n, const float *x, const float *y, float *__restrict__ z)
	This function calls the appropiate funtions to performs simple precision element-wise z[i]=z[i]*x[i]/y[i] for all positions of x, y and z. More...

Function Documentation

ddotdiv_x86()

void ddotdiv_x86	(	const int	n,
		const double *	x,
		const double *	y,
		double *__restrict__	z
	)

This function calls the appropiate funtions to performs double precision element-wise z[i]=z[i]*x[i]/y[i] for all positions of x, y and z.

Parameters

n	(input) Number of elements of x, y and z
x	(input) Double precision input vector/matrix (1D column-major)
y	(input) Double precision input vector/matrix (1D column-major)
z	(inout) Double precision input/output vector/matrix (1D column-major)

Definition at line 471 of file mlsa_cpu.c.

dmlsa_cpu()

int dmlsa_cpu	(	const int	m,
		const int	n,
		const int	k,
		const double *	A,
		double *	W,
		double *	H,
		const int	uType,
		const int	nIter
	)

dmlsa_cpu performs NNMF using betadivergence when beta=2 using double precision

The algorithm is
  repit nIter times
    STEP 1
      L=W*H
      B=W'A
      C=W'*L
      H=H(.)B(./)C

    STEP 2
      L=W*H
      D=A*H'
      E=L*H'
      W=W(.*)D(./)E
    end repit
End algorithm

To save some FLOPs and RAM a modified Lee and Seung version is used, so we have Step 1: L=W'*W, C=L*H and then B=W'*A; Step 2: L=H*H', E=W*L and D=A*H'. W'*W (H*H') and L*H (W*L) can do in parallel with W'*A (A*H'). Because dgemm works fine we don't use threads to do in parallel.

In real live B and C are (k*n) matrices used in STEP 1, and D and E are (m*k) matrices used in STEP 2. B/C and D/E are independent. For this reason only 2 matrices are declared to save space. They are matrices B and C with size max(m,n)*k

Parameters

m	(input) Number of rows of matrix A and matrix W
n	(input) Number of columns of matrix A and matrix H
k	(input) Number of columns of matrix W and rows of H
A	(input) Double precision input matrix of (m * n) number of elements stored using 1D column-major
W	(inout) Double precision input/output matrix of (m * k) number of elements stored using 1D column-major
H	(inout) Double precision input/output matrix of (k * n) number of elements stored using 1D column-major
uType	(input) It can be UpdateAll (W and H are updated), UpdateW (only H is updated) or UpdateH (only W is updated)
nIter	(input) Number of iterations

Returns

: 0 if all is OK, -1 otherwise

Definition at line 74 of file mlsa_cpu.c.

sdotdiv_x86()

void sdotdiv_x86	(	const int	n,
		const float *	x,
		const float *	y,
		float *__restrict__	z
	)

This function calls the appropiate funtions to performs simple precision element-wise z[i]=z[i]*x[i]/y[i] for all positions of x, y and z.

Parameters

n	(input) Number of elements of x, y and z
x	(input) Simple precision input vector/matrix (1D column-major)
y	(input) Simple precision input vector/matrix (1D column-major)
z	(inout) Simple precision input/output vector/matrix (1D column-major)

Definition at line 509 of file mlsa_cpu.c.

smlsa_cpu()

int smlsa_cpu	(	const int	m,
		const int	n,
		const int	k,
		const float *	A,
		float *	W,
		float *	H,
		const int	uType,
		const int	nIter
	)

smlsa_cpu performs NNMF using betadivergence when beta=2 using simple precision

Parameters

m	(input) Number of rows of matrix A and matrix W
n	(input) Number of columns of matrix A and matrix H
k	(input) Number of columns of matrix W and rows of H
A	(input) Simple precision input matrix of (m * n) number of elements stored using 1D column-major
W	(inout) Simple precision input/output matrix of (m * k) number of elements stored using 1D column-major
H	(inout) Simple precision input/output matrix of (k * n) number of elements stored using 1D column-major
uType	(input) It can be UpdateAll (W and H are updated), UpdateW (only H is updated) or UpdateH (only W is updated)
nIter	(input) Number of iterations

Returns

: 0 if all is OK, -1 otherwise

Definition at line 275 of file mlsa_cpu.c.