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//@HEADER
// ************************************************************************
//
// Kokkos v. 4.0
// Copyright (2022) National Technology & Engineering
// Solutions of Sandia, LLC (NTESS).
//
// Under the terms of Contract DE-NA0003525 with NTESS,
// the U.S. Government retains certain rights in this software.
//
// Part of Kokkos, under the Apache License v2.0 with LLVM Exceptions.
// See https://kokkos.org/LICENSE for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//@HEADER
#include <Kokkos_Core.hpp>
#include <benchmark/benchmark.h>
#include "PerfTest_Category.hpp"
#include <cmath>
#include "PerfTestBlasKernels.hpp"
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
namespace Test {
// Reduction : result = dot( Q(:,j) , Q(:,j) );
// PostProcess : R(j,j) = result ; inv = 1 / result ;
template <class VectorView, class ValueView>
struct InvNorm2 : public Kokkos::DotSingle<VectorView> {
using value_type = typename Kokkos::DotSingle<VectorView>::value_type;
ValueView Rjj;
ValueView inv;
InvNorm2(const VectorView& argX, const ValueView& argR,
const ValueView& argInv)
: Kokkos::DotSingle<VectorView>(argX), Rjj(argR), inv(argInv) {}
KOKKOS_INLINE_FUNCTION
void final(value_type& result) const {
result = Kokkos::sqrt(result);
Rjj() = result;
inv() = (0 < result) ? 1.0 / result : 0;
}
};
template <class VectorView, class ValueView>
inline void invnorm2(const VectorView& x, const ValueView& r,
const ValueView& r_inv) {
Kokkos::parallel_reduce(x.extent(0),
InvNorm2<VectorView, ValueView>(x, r, r_inv));
}
// PostProcess : tmp = - ( R(j,k) = result );
template <class VectorView, class ValueView>
struct DotM : public Kokkos::Dot<VectorView> {
using value_type = typename Kokkos::Dot<VectorView>::value_type;
ValueView Rjk;
ValueView tmp;
DotM(const VectorView& argX, const VectorView& argY, const ValueView& argR,
const ValueView& argTmp)
: Kokkos::Dot<VectorView>(argX, argY), Rjk(argR), tmp(argTmp) {}
KOKKOS_INLINE_FUNCTION
void final(value_type& result) const {
Rjk() = result;
tmp() = -result;
}
};
template <class VectorView, class ValueView>
inline void dot_neg(const VectorView& x, const VectorView& y,
const ValueView& r, const ValueView& r_neg) {
Kokkos::parallel_reduce(x.extent(0),
DotM<VectorView, ValueView>(x, y, r, r_neg));
}
template <typename Scalar, class DeviceType>
struct ModifiedGramSchmidt {
using execution_space = DeviceType;
using size_type = typename execution_space::size_type;
using multivector_type =
Kokkos::View<Scalar**, Kokkos::LayoutLeft, execution_space>;
using vector_type =
Kokkos::View<Scalar*, Kokkos::LayoutLeft, execution_space>;
using value_view = Kokkos::View<Scalar, Kokkos::LayoutLeft, execution_space>;
multivector_type Q;
multivector_type R;
static double factorization(const multivector_type Q_,
const multivector_type R_) {
const size_type count = Q_.extent(1);
value_view tmp("tmp");
value_view one("one");
Kokkos::deep_copy(one, (Scalar)1);
Kokkos::Timer timer;
for (size_type j = 0; j < count; ++j) {
// Reduction : tmp = dot( Q(:,j) , Q(:,j) );
// PostProcess : tmp = std::sqrt( tmp ); R(j,j) = tmp ; tmp = 1 / tmp ;
const vector_type Qj = Kokkos::subview(Q_, Kokkos::ALL(), j);
const value_view Rjj = Kokkos::subview(R_, j, j);
invnorm2(Qj, Rjj, tmp);
// Q(:,j) *= ( 1 / R(j,j) ); => Q(:,j) *= tmp ;
Kokkos::scale(tmp, Qj);
for (size_type k = j + 1; k < count; ++k) {
const vector_type Qk = Kokkos::subview(Q_, Kokkos::ALL(), k);
const value_view Rjk = Kokkos::subview(R_, j, k);
// Reduction : R(j,k) = dot( Q(:,j) , Q(:,k) );
// PostProcess : tmp = - R(j,k);
dot_neg(Qj, Qk, Rjk, tmp);
// Q(:,k) -= R(j,k) * Q(:,j); => Q(:,k) += tmp * Q(:,j)
Kokkos::axpby(tmp, Qj, one, Qk);
}
}
execution_space().fence();
return timer.seconds();
}
//--------------------------------------------------------------------------
static double test(const size_type length, const size_type count) {
multivector_type Q_("Q", length, count);
multivector_type R_("R", count, count);
typename multivector_type::HostMirror A = Kokkos::create_mirror(Q_);
// Create and fill A on the host
for (size_type j = 0; j < count; ++j) {
for (size_type i = 0; i < length; ++i) {
A(i, j) = (i + 1) * (j + 1);
}
}
Kokkos::deep_copy(Q_, A);
// A = Q * R
const double dt = factorization(Q_, R_);
return dt;
}
};
template <class Scalar>
static void GramSchmidt(benchmark::State& state) {
const int parallel_work_length = state.range(0);
for (auto _ : state) {
const double seconds =
ModifiedGramSchmidt<Scalar, Kokkos::DefaultExecutionSpace>::test(
parallel_work_length, 32);
state.SetIterationTime(seconds);
state.counters["Count"] = benchmark::Counter(parallel_work_length);
state.counters["Time normalized"] =
benchmark::Counter(seconds / parallel_work_length);
}
}
// FIXME_SYCL SYCL+Cuda reports "an illegal memory access was encountered"
#if defined(KOKKOS_ENABLE_SYCL) && defined(KOKKOS_IMPL_ARCH_NVIDIA_GPU)
BENCHMARK(GramSchmidt<double>)
->ArgName("Count")
->ArgsProduct({
benchmark::CreateRange(1 << 10, 1 << 18, 2),
})
->UseManualTime()
->Iterations(5);
#else
BENCHMARK(GramSchmidt<double>)
->ArgName("Count")
->ArgsProduct({
benchmark::CreateRange(1 << 10, 1 << 19, 2),
})
->UseManualTime()
->Iterations(5);
#endif
} // namespace Test
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