bool ClustFlat(const ClustOptions& opts,
const std::vector<DenseMatrix<T> >& topic_vectors,
const MatrixType<T>& A,
T* buf_w,
T* buf_h)
{
int m = opts.nmf_opts.height;
int n = opts.nmf_opts.width;
int k = opts.num_clusters;
DenseMatrix<T> W(m, k, buf_w, m);
// load matrix W with the topic vectors
DenseMatrix<T> col_w;
for (int c=0; c<k; ++c)
{
// create a view of the cth column of W
View(col_w, W, 0, c, m, 1);
// copy the next topic vector into place
Copy(topic_vectors[c], col_w);
}
// randomly initialize matrix H
Random rng;
rng.SeedFromTime();
RandomMatrix(buf_h, k, k, n, rng, T(0.5), T(0.5));
DenseMatrix<T> H(k, n, buf_h, k);
bool ok = NnlsHals(A, W, H,
opts.nmf_opts.tol,
opts.verbose,
opts.nmf_opts.max_iter);
return ok;
}
template<typename T> void RunOneTest( const unsigned int randSeed,
const size_t memAllowed,
const char transA, const char transB,
const int matrixSize,
const T min, const T max,
const T alpha, const T beta,
const unsigned int nRepeats,
std::ostream &os ) {
// Routine to run a single comparision of the cleaver
T *A, *B, *C;
T *resBLAS, *resCleaver;
int m, n, k, lda, ldb, ldc;
int hA, wA, hB, wB, hC, wC;
SciGPUgemm::GEMMcleaver testCleaver( memAllowed );
Chronometer t_cpu, t_cleaver;
// Initialise PRNG
srand( randSeed );
// Set the matrix sizes
m = n = k = matrixSize;
lda = wA = hA = ldb = wB = hB = ldc = wC = hC = matrixSize;
// Allocate memory
A = new T[lda*wA];
B = new T[ldb*wB];
C = new T[ldc*wC];
resBLAS = new T[ldc*wC];
resCleaver = new T[ldc*wC];
// Fill with data
RandomMatrix( A, lda, hA, wA, min, max );
RandomMatrix( B, ldb, hB, wB, min, max );
RandomMatrix( C, ldc, hC, wC, min, max );
// Average over designated number of runs
for( unsigned int iRepeat=0; iRepeat<nRepeats; iRepeat++ ) {
memcpy( resBLAS, C, ldc*wC*sizeof(T) );
memcpy( resCleaver, C, ldc*wC*sizeof(T) );
// Run the CPU multiplication
t_cpu.Start();
gemm_gold( A, B, resBLAS,
alpha, beta,
transA, transB,
m, n, k, lda, ldb, ldc );
t_cpu.Stop();
// Run the GPU multiplication
t_cleaver.Start();
RunCleaver( transA, transB,
m, n, k,
alpha,
A, lda, B, ldb,
beta,
resCleaver, ldc,
testCleaver );
t_cleaver.Stop();
}
// Output the results
WriteStream( os, matrixSize );
WriteStream( os, t_cpu.GetAverageTime() );
WriteStream( os, t_cleaver.GetAverageTime() );
os << std::endl;
// Release memory
delete[] A;
delete[] B;
delete[] C;
delete[] resBLAS;
delete[] resCleaver;
}
