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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 <TestCuda_Category.hpp>
#include <Kokkos_Core.hpp>
namespace Test {
using ValueType = double;
using MemSpace = Kokkos::CudaSpace;
using Matrix2D = Kokkos::View<ValueType**, MemSpace>;
using Matrix3D = Kokkos::View<ValueType***, MemSpace>;
using Vector = Kokkos::View<ValueType*, MemSpace>;
namespace Impl {
struct ArrayReduceFunctor {
using value_type = ValueType[];
int value_count;
Matrix2D m;
ArrayReduceFunctor(const Matrix2D& m_) : value_count(m_.extent(1)), m(m_) {}
KOKKOS_INLINE_FUNCTION void operator()(const int i, value_type sum) const {
const int numVecs = value_count;
for (int j = 0; j < numVecs; ++j) {
sum[j] += m(i, j);
}
}
KOKKOS_INLINE_FUNCTION void init(value_type update) const {
const int numVecs = value_count;
for (int j = 0; j < numVecs; ++j) {
update[j] = 0.0;
}
}
KOKKOS_INLINE_FUNCTION void join(value_type update,
const value_type source) const {
const int numVecs = value_count;
for (int j = 0; j < numVecs; ++j) {
update[j] += source[j];
}
}
KOKKOS_INLINE_FUNCTION void final(value_type) const {}
};
struct MDArrayReduceFunctor {
using value_type = ValueType[];
int value_count;
Matrix3D m;
MDArrayReduceFunctor(const Matrix3D& m_) : value_count(m_.extent(2)), m(m_) {}
KOKKOS_INLINE_FUNCTION void operator()(const int i, const int j,
value_type sum) const {
const int numVecs = value_count;
for (int k = 0; k < numVecs; ++k) {
sum[k] += m(i, j, k);
}
}
KOKKOS_INLINE_FUNCTION void init(value_type update) const {
const int numVecs = value_count;
for (int j = 0; j < numVecs; ++j) {
update[j] = 0.0;
}
}
KOKKOS_INLINE_FUNCTION void final(value_type) const {}
};
struct ReduceViewSizeLimitTester {
const ValueType initValue = 3;
const size_t nGlobalEntries = 100;
const int testViewSize = 200;
const size_t expectedInitShmemLimit = 373584;
const unsigned initBlockSize = Kokkos::Impl::CudaTraits::WarpSize * 8;
void run_test_range() {
Matrix2D matrix;
Vector sum;
for (int i = 0; i < testViewSize; ++i) {
size_t sumInitShmemSize = (initBlockSize + 2) * sizeof(ValueType) * i;
Kokkos::resize(Kokkos::WithoutInitializing, sum, i);
Kokkos::resize(Kokkos::WithoutInitializing, matrix, nGlobalEntries, i);
Kokkos::deep_copy(matrix, initValue);
auto policy = Kokkos::RangePolicy<TEST_EXECSPACE>(0, nGlobalEntries);
auto functor = ArrayReduceFunctor(matrix);
if (sumInitShmemSize < expectedInitShmemLimit) {
EXPECT_NO_THROW(Kokkos::parallel_reduce(policy, functor, sum));
} else {
EXPECT_THROW(Kokkos::parallel_reduce(policy, functor, sum),
std::runtime_error);
}
}
}
void run_test_md_range_2D() {
Matrix3D matrix;
Vector sum;
for (int i = 0; i < testViewSize; ++i) {
size_t sumInitShmemSize = (initBlockSize + 2) * sizeof(ValueType) * i;
Kokkos::resize(Kokkos::WithoutInitializing, sum, i);
Kokkos::resize(Kokkos::WithoutInitializing, matrix, nGlobalEntries,
nGlobalEntries, i);
Kokkos::deep_copy(matrix, initValue);
auto policy = Kokkos::MDRangePolicy<Kokkos::Rank<2>>(
{0, 0}, {nGlobalEntries, nGlobalEntries});
auto functor = MDArrayReduceFunctor(matrix);
if (sumInitShmemSize < expectedInitShmemLimit) {
EXPECT_NO_THROW(Kokkos::parallel_reduce(policy, functor, sum));
} else {
EXPECT_THROW(Kokkos::parallel_reduce(policy, functor, sum),
std::runtime_error);
}
}
}
};
} // namespace Impl
TEST(cuda, reduceRangePolicyViewSizeLimit) {
Impl::ReduceViewSizeLimitTester reduceViewSizeLimitTester;
reduceViewSizeLimitTester.run_test_range();
}
TEST(cuda, reduceMDRangePolicyViewSizeLimit) {
Impl::ReduceViewSizeLimitTester reduceViewSizeLimitTester;
reduceViewSizeLimitTester.run_test_md_range_2D();
}
} // namespace Test
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