void index_of(MatrixA const &mat,
MatrixB &indexed_of_mat,
graphblas::IndexType base_index)
{
graphblas::IndexType rows, cols;
mat.get_shape(rows, cols);
using T = typename MatrixA::ScalarType;
for (IndexType i = 0; i < rows; ++i)
{
for (IndexType j = 0; j < cols; ++j)
{
auto mat_ij = mat.get_value_at(i, j);
if (mat_ij > 0 || mat_ij == std::numeric_limits<T>::max())
{
indexed_of_mat.set_value_at(i, j, i + base_index);
}
else
{
// FIXME indexed_of_mat.get_zero()?
indexed_of_mat.set_value_at(i, j, mat.get_zero());
}
}
}
}
void operator()(const communicator& comm, const config& cfg,
T alpha, MatrixA& A, MatrixB& B, T beta, MatrixC& C)
{
using namespace matrix_constants;
len_type m = (Mat == MAT_A ? A.length(0) : Mat == MAT_B ? B.length(0) : C.length(0));
len_type n = (Mat == MAT_A ? A.length(1) : Mat == MAT_B ? B.length(1) : C.length(1));
if (!rscat)
{
if (comm.master())
{
scat_buffer = Pool.allocate<stride_type>(2*m + 2*n);
rscat = scat_buffer.get<stride_type>();
}
comm.broadcast(rscat);
cscat = rscat+m;
rbs = cscat+n;
cbs = rbs+m;
}
matrify_and_run<Mat>(*this, comm, cfg, alpha, A, B, beta, C);
}
matrify_and_run(Parent& parent, const communicator& comm, const config& cfg,
T alpha, MatrixA& A, MatrixB& B, T beta, MatrixC& C)
{
const len_type MB = cfg.gemm_kr.def<T>();
const len_type NB = cfg.gemm_nr.def<T>();
//block_scatter(comm, B, parent.rscat, MB, parent.rbs,
// parent.cscat, NB, parent.cbs);
B.fill_block_scatter(0, parent.rscat, MB, parent.rbs);
B.fill_block_scatter(1, parent.cscat, NB, parent.cbs);
block_scatter_matrix<T> M(B.length(0), B.length(1), B.data(),
parent.rscat, MB, parent.rbs,
parent.cscat, NB, parent.cbs);
parent.child(comm, cfg, alpha, A, M, beta, C);
}
inline void smat_smat_mult(const MatrixA& a, const MatrixB& b, MatrixC& c, Assign,
tag::col_major, // orientation a
tag::row_major) // orientation b
{
if (Assign::init_to_zero) set_to_zero(c);
// Average numbers of non-zeros per row
double ava= double(a.nnz()) / num_rows(a), avb= double(b.nnz()) / num_rows(b);
// Define Updater type corresponding to assign mode
typedef typename Collection<MatrixC>::value_type c_value_type;
typedef typename operations::update_assign_mode<Assign, c_value_type>::type Updater;
// Reserve 20% over the average's product for entries in c
matrix::inserter<MatrixC, Updater> ins(c, int( ava * avb * 1.2 ));
typename traits::row<MatrixA>::type row_a(a);
typename traits::col<MatrixA>::type col_a(a);
typename traits::const_value<MatrixA>::type value_a(a);
typename traits::row<MatrixB>::type row_b(b);
typename traits::col<MatrixB>::type col_b(b);
typename traits::const_value<MatrixB>::type value_b(b);
typedef typename traits::range_generator<tag::col, MatrixA>::type a_cursor_type;
a_cursor_type a_cursor = begin<tag::col>(a), a_cend = end<tag::col>(a);
typedef typename traits::range_generator<tag::row, MatrixB>::type b_cursor_type;
b_cursor_type b_cursor = begin<tag::row>(b);
for (unsigned ca= 0; a_cursor != a_cend; ++ca, ++a_cursor, ++b_cursor) {
// Iterate over non-zeros of A's column
typedef typename traits::range_generator<tag::nz, a_cursor_type>::type ia_cursor_type;
for (ia_cursor_type ia_cursor = begin<tag::nz>(a_cursor), ia_cend = end<tag::nz>(a_cursor);
ia_cursor != ia_cend; ++ia_cursor)
{
typename Collection<MatrixA>::size_type ra= row_a(*ia_cursor); // row of non-zero
typename Collection<MatrixA>::value_type va= value_a(*ia_cursor); // value of non-zero
// Iterate over non-zeros of B's row
typedef typename traits::range_generator<tag::nz, b_cursor_type>::type ib_cursor_type;
for (ib_cursor_type ib_cursor = begin<tag::nz>(b_cursor), ib_cend = end<tag::nz>(b_cursor);
ib_cursor != ib_cend; ++ib_cursor)
{
typename Collection<MatrixB>::size_type cb= col_b(*ib_cursor); // column of non-zero
typename Collection<MatrixB>::value_type vb= value_b(*ib_cursor); // value of non-zero
ins(ra, cb) << va * vb;
}
}
}
}
inline void smat_smat_mult(const MatrixA& A, const MatrixB& B, MatrixC& C, Assign,
tag::col_major, // orientation A
tag::row_major) // orientation B
{
if (Assign::init_to_zero) set_to_zero(C);
// Average numbers of non-zeros per row
double ava= double(A.nnz()) / num_rows(A), avb= double(B.nnz()) / num_rows(B);
// Define Updater type corresponding to assign mode
typedef typename Collection<MatrixC>::value_type C_value_type;
typedef typename operations::update_assign_mode<Assign, C_value_type>::type Updater;
// Reserve 20% over the average's product for entries in C
matrix::inserter<MatrixC, Updater> ins(C, int( ava * avb * 1.2 ));
typename traits::row<MatrixA>::type row_A(A);
typename traits::col<MatrixA>::type col_A(A);
typename traits::const_value<MatrixA>::type value_A(A);
typename traits::row<MatrixB>::type row_B(B);
typename traits::col<MatrixB>::type col_B(B);
typename traits::const_value<MatrixB>::type value_B(B);
typedef typename traits::range_generator<tag::col, MatrixA>::type A_cursor_type;
A_cursor_type A_cursor = begin<tag::col>(A), A_cend = end<tag::col>(A);
typedef typename traits::range_generator<tag::row, MatrixB>::type B_cursor_type;
B_cursor_type B_cursor = begin<tag::row>(B);
for (unsigned ca= 0; A_cursor != A_cend; ++ca, ++A_cursor, ++B_cursor) {
// Iterate over non-zeros of A's column
typedef typename traits::range_generator<tag::nz, A_cursor_type>::type ia_cursor_type;
for (ia_cursor_type ia_cursor = begin<tag::nz>(A_cursor), ia_cend = end<tag::nz>(A_cursor);
ia_cursor != ia_cend; ++ia_cursor)
{
typename Collection<MatrixA>::size_type ra= row_A(*ia_cursor); // row of non-zero
typename Collection<MatrixA>::value_type va= value_A(*ia_cursor); // value of non-zero
// Iterate over non-zeros of B's row
typedef typename traits::range_generator<tag::nz, B_cursor_type>::type ib_cursor_type;
for (ib_cursor_type ib_cursor = begin<tag::nz>(B_cursor), ib_cend = end<tag::nz>(B_cursor);
ib_cursor != ib_cend; ++ib_cursor)
{
typename Collection<MatrixB>::size_type cb= col_B(*ib_cursor); // column of non-zero
typename Collection<MatrixB>::value_type vb= value_B(*ib_cursor); // value of non-zero
ins(ra, cb) << va * vb;
}
}
}
}
inline void smat_smat_mult(const MatrixA& A, const MatrixB& B, MatrixC& C, Assign,
tag::row_major, // orientation A
tag::row_major) // orientation B
{
if (Assign::init_to_zero) set_to_zero(C);
// Average numbers of non-zeros per row
double ava= num_cols(A) ? double(A.nnz()) / num_cols(A) : 0,
avb= num_rows(B) ? double(B.nnz()) / num_rows(B) : 0;
// Define Updater type corresponding to assign mode
typedef typename Collection<MatrixC>::value_type C_value_type;
typedef typename operations::update_assign_mode<Assign, C_value_type>::type Updater;
// Reserve 20% over the average's product for entries in C
matrix::inserter<MatrixC, Updater> ins(C, int( ava * avb * 1.4 ));
typename traits::row<MatrixA>::type row_A(A);
typename traits::col<MatrixA>::type col_A(A);
typename traits::const_value<MatrixA>::type value_A(A);
typename traits::col<MatrixB>::type col_B(B);
typename traits::const_value<MatrixB>::type value_B(B);
typedef typename traits::range_generator<tag::row, MatrixA>::type cursor_type;
cursor_type cursor = begin<tag::row>(A), cend = end<tag::row>(A);
for (unsigned ra= 0; cursor != cend; ++ra, ++cursor) {
// Iterate over non-zeros of each row of A
typedef typename traits::range_generator<tag::nz, cursor_type>::type icursor_type;
for (icursor_type icursor = begin<tag::nz>(cursor), icend = end<tag::nz>(cursor); icursor != icend; ++icursor) {
typename Collection<MatrixA>::size_type ca= col_A(*icursor); // column of non-zero
typename Collection<MatrixA>::value_type va= value_A(*icursor); // value of non-zero
// Get cursor corresponding to row 'ca' in matrix B
typedef typename traits::range_generator<tag::row, MatrixB>::type B_cursor_type;
B_cursor_type B_cursor = begin<tag::row>(B);
B_cursor+= ca;
// Iterate over non-zeros of this row
typedef typename traits::range_generator<tag::nz, B_cursor_type>::type ib_cursor_type;
for (ib_cursor_type ib_cursor = begin<tag::nz>(B_cursor), ib_cend = end<tag::nz>(B_cursor);
ib_cursor != ib_cend; ++ib_cursor) {
typename Collection<MatrixB>::size_type cb= col_B(*ib_cursor); // column of non-zero
typename Collection<MatrixB>::value_type vb= value_B(*ib_cursor); // value of non-zero
ins(ra, cb) << va * vb;
}
}
}
}
void operator()(const communicator& comm, const config& cfg,
T alpha, MatrixA& A, MatrixB& B, T beta, MatrixC& C)
{
using namespace matrix_constants;
const len_type MR = (Mat == MAT_B ? cfg.gemm_kr.def<T>()
: cfg.gemm_mr.def<T>());
const len_type NR = (Mat == MAT_A ? cfg.gemm_kr.def<T>()
: cfg.gemm_nr.def<T>());
len_type m = (Mat == MAT_A ? A.length(0) : Mat == MAT_B ? B.length(0) : C.length(0));
len_type n = (Mat == MAT_A ? A.length(1) : Mat == MAT_B ? B.length(1) : C.length(1));
m = round_up(m, MR);
n = round_up(n, NR);
auto& pack_buffer = child.pack_buffer;
auto& pack_ptr = child.pack_ptr;
if (!pack_ptr)
{
if (comm.master())
{
len_type scatter_size = size_as_type<stride_type,T>(2*m + 2*n);
pack_buffer = Pool.allocate<T>(m*n + std::max(m,n)*TBLIS_MAX_UNROLL + scatter_size);
pack_ptr = pack_buffer.get();
}
comm.broadcast(pack_ptr);
rscat = convert_and_align<T,stride_type>(static_cast<T*>(pack_ptr) + m*n);
cscat = rscat+m;
rbs = cscat+n;
cbs = rbs+m;
}
Sib::operator()(comm, cfg, alpha, A, B, beta, C);
}
