mlsa_mic.h File Reference

Header file for using the mlsa algorithm with MIC/MIC. More...

Go to the source code of this file.

Functions
int	dmlsa_mic (const int m, const int n, const int k, const double *A, double *W, double *H, const int uType, const int nIter)
	dmlsa_mic performs NNMF using betadivergence when beta=2 using double precision More...
int	smlsa_mic (const int m, const int n, const int k, const float *A, float *W, float *H, const int uType, const int nIter)
	smlsa_mic performs NNMF using betadivergence when beta=2 using simple precision More...

Detailed Description

Header file for using the mlsa algorithm with MIC/MIC.

Author

Information Retrieval and Parallel Computing Group (IRPCG)

University of Oviedo, Spain

Interdisciplinary Computation and Communication Group (INCO2)

Universitat Politecnica de Valencia, Spain.

Contact: nnmfp.nosp@m.ack@.nosp@m.gmail.nosp@m..com

Date

12/03/18

Definition in file mlsa_mic.h.

Function Documentation

dmlsa_mic()

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

dmlsa_mic 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 72 of file mlsa_mic.c.

smlsa_mic()

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

smlsa_mic 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 111 of file mlsa_mic.c.