GPUMLib  0.2.2
GPU Machine Learning Library
NMFmultiplicativeDivergence.h
1 /*
2  Noel Lopes is an Assistant Professor at the Polytechnic Institute of Guarda, Portugal
3  Copyright (C) 2009, 2010, 2011, 2012 Noel de Jesus Mendonša Lopes
4 
5  This file is part of GPUMLib.
6 
7  GPUMLib is free software: you can redistribute it and/or modify
8  it under the terms of the GNU General Public License as published by
9  the Free Software Foundation, either version 3 of the License, or
10  (at your option) any later version.
11 
12  This program is distributed in the hope that it will be useful,
13  but WITHOUT ANY WARRANTY; without even the implied warranty of
14  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
15  GNU General Public License for more details.
16 
17  You should have received a copy of the GNU General Public License
18  along with this program. If not, see <http://www.gnu.org/licenses/>.
19 */
20 
21 #ifndef GPUMLib_NMF_MultiplicativeDivergence_h
22 #define GPUMLib_NMF_MultiplicativeDivergence_h
23 
24 #include "../memory/DeviceArray.h"
25 #include "../common/Utilities.h"
26 #include "BaseNMF.h"
27 
28 namespace GPUMLib {
29 
32 
35  private:
37 
38  dim3 bh, gh;
39  dim3 bw, gw;
40 
41  public:
47  NMF_MultiplicativeDivergence(HostMatrix<cudafloat> & v, int r) : NMF(v, r), sum(r), bh(32, 16), gh(NumberBlocks(v.Columns(), 32), NumberBlocks(r, 32)), bw(16, 32), gw(NumberBlocks(r, 32), NumberBlocks(v.Rows(), 32)) {
48  }
49 
56  NMF_MultiplicativeDivergence(HostMatrix<cudafloat> & v, HostMatrix<cudafloat> & w, HostMatrix<cudafloat> & h) : NMF(v, w, h), sum(w.Columns()), bh(32, 16), gh(NumberBlocks(v.Columns(), 32), NumberBlocks(w.Columns(), 32)), bw(16, 32), gw(NumberBlocks(w.Columns(), 32), NumberBlocks(v.Rows(), 32)) {
57  }
58 
61  void DoIteration(bool updateW = true);
62 };
63 
65 
66 }
67 
68 #endif
NMF_MultiplicativeDivergence(HostMatrix< cudafloat > &v, int r)
Represents a Non-Negative Matrix Factorization (NMF) algorithm that uses multiplicative update rules ...
int NumberBlocks(int threads, int blockSize)
Definition: Utilities.h:49
Base class for all Non-Negative Matrix Factorization classes.
Definition: BaseNMF.h:40
NMF_MultiplicativeDivergence(HostMatrix< cudafloat > &v, HostMatrix< cudafloat > &w, HostMatrix< cudafloat > &h)