/usr/include/trilinos/TbbTsqr_RevealRankTask.hpp is in libtrilinos-tpetra-dev 12.10.1-3.
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// Kokkos: Node API and Parallel Node Kernels
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#ifndef __TSQR_TBB_RevealRankTask_hpp
#define __TSQR_TBB_RevealRankTask_hpp
#include <tbb/task.h>
#include <TbbTsqr_Partitioner.hpp>
#include <Tsqr_SequentialTsqr.hpp>
////////////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////
namespace TSQR {
namespace TBB {
/// \class RevealRankTask
/// \brief TBB task for recursive TSQR "rank-revealing" phase.
///
/// This part of the factorization doesn't actually reveal the
/// rank in parallel; we assume that this has already been done
/// and the columns of U form a basis for the column space of the
/// R factor (in the QR factorization of the original matrix).
/// All we need to do here is compute Q*U in parallel, respecting
/// the original partitioning and cache blocking scheme.
template<class LocalOrdinal, class Scalar>
class RevealRankTask : public tbb::task {
public:
typedef MatView<LocalOrdinal, Scalar> mat_view_type;
typedef ConstMatView<LocalOrdinal, Scalar> const_mat_view_type;
typedef std::pair<mat_view_type, mat_view_type> split_type;
typedef SequentialTsqr<LocalOrdinal, Scalar> seq_tsqr_type;
RevealRankTask (const size_t P_first,
const size_t P_last,
const mat_view_type& Q,
const const_mat_view_type& U,
const seq_tsqr_type& seq,
const bool contiguous_cache_blocks) :
P_first_ (P_first),
P_last_ (P_last),
Q_ (Q),
U_ (U),
seq_ (seq),
contiguous_cache_blocks_ (contiguous_cache_blocks)
{}
void
execute_base_case ()
{
// Use SequentialTsqr to compute Q*U for this core's local
// part of Q. The method is called "Q_times_B" so that it
// doesn't suggest any orthogonality of the B input matrix,
// though in this case B is U and U is orthogonal
// (resp. unitary if Scalar is complex).
seq_.Q_times_B (Q_.nrows(), Q_.ncols(), Q_.get(), Q_.lda(),
U_.get(), U_.lda(), contiguous_cache_blocks_);
}
tbb::task* execute ()
{
using tbb::task;
if (P_first_ > P_last_ || Q_.empty())
return NULL; // shouldn't get here, but just in case...
else if (P_first_ == P_last_)
{
execute_base_case ();
return NULL;
}
else
{
// Recurse on two intervals: [P_first, P_mid] and
// [P_mid+1, P_last]
const size_t P_mid = (P_first_ + P_last_) / 2;
split_type out_split =
partitioner_.split (Q_, P_first_, P_mid, P_last_,
contiguous_cache_blocks_);
// The partitioner may decide that the current block Q_
// has too few rows to be worth splitting. In that case,
// out_split.second (the bottom block) will be empty. We
// can deal with this by treating it as the base case.
if (out_split.second.empty() || out_split.second.nrows() == 0)
{
execute_base_case ();
return NULL;
}
// "c": continuation task
tbb::empty_task& c =
*new( allocate_continuation() ) tbb::empty_task;
// Recurse on the split
RevealRankTask& topTask = *new( c.allocate_child() )
RevealRankTask (P_first_, P_mid, out_split.first, U_,
seq_, contiguous_cache_blocks_);
RevealRankTask& botTask = *new( c.allocate_child() )
RevealRankTask (P_mid+1, P_last_, out_split.second, U_,
seq_, contiguous_cache_blocks_);
// Set reference count of parent (in this case, the
// continuation task) to 2 (since 2 children -- no
// additional task since no waiting).
c.set_ref_count (2);
c.spawn (botTask);
return &topTask; // scheduler bypass optimization
}
}
private:
size_t P_first_, P_last_;
mat_view_type Q_;
const_mat_view_type U_;
SequentialTsqr<LocalOrdinal, Scalar> seq_;
Partitioner<LocalOrdinal, Scalar> partitioner_;
bool contiguous_cache_blocks_;
};
} // namespace TBB
} // namespace TSQR
#endif // __TSQR_TBB_RevealRankTask_hpp
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