464 lines
14 KiB
C++
464 lines
14 KiB
C++
/*
|
|
//@HEADER
|
|
// ************************************************************************
|
|
//
|
|
// Kokkos v. 3.0
|
|
// Copyright (2020) 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.
|
|
//
|
|
// Redistribution and use in source and binary forms, with or without
|
|
// modification, are permitted provided that the following conditions are
|
|
// met:
|
|
//
|
|
// 1. Redistributions of source code must retain the above copyright
|
|
// notice, this list of conditions and the following disclaimer.
|
|
//
|
|
// 2. Redistributions in binary form must reproduce the above copyright
|
|
// notice, this list of conditions and the following disclaimer in the
|
|
// documentation and/or other materials provided with the distribution.
|
|
//
|
|
// 3. Neither the name of the Corporation nor the names of the
|
|
// contributors may be used to endorse or promote products derived from
|
|
// this software without specific prior written permission.
|
|
//
|
|
// THIS SOFTWARE IS PROVIDED BY NTESS "AS IS" AND ANY
|
|
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
|
|
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
|
|
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NTESS OR THE
|
|
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
|
|
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
|
|
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
|
|
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
|
|
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
|
|
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
|
|
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
|
//
|
|
// Questions? Contact Christian R. Trott (crtrott@sandia.gov)
|
|
//
|
|
// ************************************************************************
|
|
//@HEADER
|
|
*/
|
|
|
|
#include <stdexcept>
|
|
#include <sstream>
|
|
#include <iostream>
|
|
#include <limits>
|
|
|
|
#include <Kokkos_Core.hpp>
|
|
|
|
namespace Test {
|
|
|
|
template <typename ScalarType, class DeviceType>
|
|
class ReduceFunctor {
|
|
public:
|
|
typedef DeviceType execution_space;
|
|
typedef typename execution_space::size_type size_type;
|
|
|
|
struct value_type {
|
|
ScalarType value[3];
|
|
};
|
|
|
|
const size_type nwork;
|
|
|
|
KOKKOS_INLINE_FUNCTION
|
|
ReduceFunctor(const size_type& arg_nwork) : nwork(arg_nwork) {}
|
|
|
|
KOKKOS_INLINE_FUNCTION
|
|
ReduceFunctor(const ReduceFunctor& rhs) : nwork(rhs.nwork) {}
|
|
|
|
/*
|
|
KOKKOS_INLINE_FUNCTION
|
|
void init( value_type & dst ) const
|
|
{
|
|
dst.value[0] = 0;
|
|
dst.value[1] = 0;
|
|
dst.value[2] = 0;
|
|
}
|
|
*/
|
|
|
|
KOKKOS_INLINE_FUNCTION
|
|
void join(volatile value_type& dst, const volatile value_type& src) const {
|
|
dst.value[0] += src.value[0];
|
|
dst.value[1] += src.value[1];
|
|
dst.value[2] += src.value[2];
|
|
}
|
|
|
|
KOKKOS_INLINE_FUNCTION
|
|
void operator()(size_type iwork, value_type& dst) const {
|
|
dst.value[0] += 1;
|
|
dst.value[1] += iwork + 1;
|
|
dst.value[2] += nwork - iwork;
|
|
}
|
|
};
|
|
|
|
template <class DeviceType>
|
|
class ReduceFunctorFinal : public ReduceFunctor<long, DeviceType> {
|
|
public:
|
|
typedef typename ReduceFunctor<long, DeviceType>::value_type value_type;
|
|
|
|
KOKKOS_INLINE_FUNCTION
|
|
ReduceFunctorFinal(const size_t n) : ReduceFunctor<long, DeviceType>(n) {}
|
|
|
|
KOKKOS_INLINE_FUNCTION
|
|
void final(value_type& dst) const {
|
|
dst.value[0] = -dst.value[0];
|
|
dst.value[1] = -dst.value[1];
|
|
dst.value[2] = -dst.value[2];
|
|
}
|
|
};
|
|
|
|
template <typename ScalarType, class DeviceType>
|
|
class RuntimeReduceFunctor {
|
|
public:
|
|
// Required for functor:
|
|
typedef DeviceType execution_space;
|
|
typedef ScalarType value_type[];
|
|
const unsigned value_count;
|
|
|
|
// Unit test details:
|
|
|
|
typedef typename execution_space::size_type size_type;
|
|
|
|
const size_type nwork;
|
|
|
|
RuntimeReduceFunctor(const size_type arg_nwork, const size_type arg_count)
|
|
: value_count(arg_count), nwork(arg_nwork) {}
|
|
|
|
KOKKOS_INLINE_FUNCTION
|
|
void init(ScalarType dst[]) const {
|
|
for (unsigned i = 0; i < value_count; ++i) dst[i] = 0;
|
|
}
|
|
|
|
KOKKOS_INLINE_FUNCTION
|
|
void join(volatile ScalarType dst[], const volatile ScalarType src[]) const {
|
|
for (unsigned i = 0; i < value_count; ++i) dst[i] += src[i];
|
|
}
|
|
|
|
KOKKOS_INLINE_FUNCTION
|
|
void operator()(size_type iwork, ScalarType dst[]) const {
|
|
const size_type tmp[3] = {1, iwork + 1, nwork - iwork};
|
|
|
|
for (size_type i = 0; i < value_count; ++i) {
|
|
dst[i] += tmp[i % 3];
|
|
}
|
|
}
|
|
};
|
|
|
|
template <typename ScalarType, class DeviceType>
|
|
class RuntimeReduceMinMax {
|
|
public:
|
|
// Required for functor:
|
|
typedef DeviceType execution_space;
|
|
typedef ScalarType value_type[];
|
|
const unsigned value_count;
|
|
|
|
// Unit test details:
|
|
|
|
typedef typename execution_space::size_type size_type;
|
|
|
|
const size_type nwork;
|
|
const ScalarType amin;
|
|
const ScalarType amax;
|
|
|
|
RuntimeReduceMinMax(const size_type arg_nwork, const size_type arg_count)
|
|
: value_count(arg_count),
|
|
nwork(arg_nwork),
|
|
amin(std::numeric_limits<ScalarType>::min()),
|
|
amax(std::numeric_limits<ScalarType>::max()) {}
|
|
|
|
KOKKOS_INLINE_FUNCTION
|
|
void init(ScalarType dst[]) const {
|
|
for (unsigned i = 0; i < value_count; ++i) {
|
|
dst[i] = i % 2 ? amax : amin;
|
|
}
|
|
}
|
|
|
|
KOKKOS_INLINE_FUNCTION
|
|
void join(volatile ScalarType dst[], const volatile ScalarType src[]) const {
|
|
for (unsigned i = 0; i < value_count; ++i) {
|
|
dst[i] = i % 2 ? (dst[i] < src[i] ? dst[i] : src[i]) // min
|
|
: (dst[i] > src[i] ? dst[i] : src[i]); // max
|
|
}
|
|
}
|
|
|
|
KOKKOS_INLINE_FUNCTION
|
|
void operator()(size_type iwork, ScalarType dst[]) const {
|
|
const ScalarType tmp[2] = {ScalarType(iwork + 1),
|
|
ScalarType(nwork - iwork)};
|
|
|
|
for (size_type i = 0; i < value_count; ++i) {
|
|
dst[i] = i % 2 ? (dst[i] < tmp[i % 2] ? dst[i] : tmp[i % 2])
|
|
: (dst[i] > tmp[i % 2] ? dst[i] : tmp[i % 2]);
|
|
}
|
|
}
|
|
};
|
|
|
|
template <class DeviceType>
|
|
class RuntimeReduceFunctorFinal
|
|
: public RuntimeReduceFunctor<long, DeviceType> {
|
|
public:
|
|
typedef RuntimeReduceFunctor<long, DeviceType> base_type;
|
|
typedef typename base_type::value_type value_type;
|
|
typedef long scalar_type;
|
|
|
|
RuntimeReduceFunctorFinal(const size_t theNwork, const size_t count)
|
|
: base_type(theNwork, count) {}
|
|
|
|
KOKKOS_INLINE_FUNCTION
|
|
void final(value_type dst) const {
|
|
for (unsigned i = 0; i < base_type::value_count; ++i) {
|
|
dst[i] = -dst[i];
|
|
}
|
|
}
|
|
};
|
|
|
|
namespace {
|
|
|
|
template <typename ScalarType, class DeviceType>
|
|
class TestReduce {
|
|
public:
|
|
typedef DeviceType execution_space;
|
|
typedef typename execution_space::size_type size_type;
|
|
|
|
TestReduce(const size_type& nwork) {
|
|
run_test(nwork);
|
|
run_test_final(nwork);
|
|
}
|
|
|
|
void run_test(const size_type& nwork) {
|
|
typedef Test::ReduceFunctor<ScalarType, execution_space> functor_type;
|
|
typedef typename functor_type::value_type value_type;
|
|
|
|
enum { Count = 3 };
|
|
enum { Repeat = 100 };
|
|
|
|
value_type result[Repeat];
|
|
|
|
const unsigned long nw = nwork;
|
|
const unsigned long nsum =
|
|
nw % 2 ? nw * ((nw + 1) / 2) : (nw / 2) * (nw + 1);
|
|
|
|
for (unsigned i = 0; i < Repeat; ++i) {
|
|
Kokkos::parallel_reduce(nwork, functor_type(nwork), result[i]);
|
|
}
|
|
|
|
for (unsigned i = 0; i < Repeat; ++i) {
|
|
for (unsigned j = 0; j < Count; ++j) {
|
|
const unsigned long correct = 0 == j % 3 ? nw : nsum;
|
|
ASSERT_EQ((ScalarType)correct, result[i].value[j]);
|
|
}
|
|
}
|
|
}
|
|
|
|
void run_test_final(const size_type& nwork) {
|
|
typedef Test::ReduceFunctorFinal<execution_space> functor_type;
|
|
typedef typename functor_type::value_type value_type;
|
|
|
|
enum { Count = 3 };
|
|
enum { Repeat = 100 };
|
|
|
|
value_type result[Repeat];
|
|
|
|
const unsigned long nw = nwork;
|
|
const unsigned long nsum =
|
|
nw % 2 ? nw * ((nw + 1) / 2) : (nw / 2) * (nw + 1);
|
|
|
|
for (unsigned i = 0; i < Repeat; ++i) {
|
|
if (i % 2 == 0) {
|
|
Kokkos::parallel_reduce(nwork, functor_type(nwork), result[i]);
|
|
} else {
|
|
Kokkos::parallel_reduce("Reduce", nwork, functor_type(nwork),
|
|
result[i]);
|
|
}
|
|
}
|
|
|
|
for (unsigned i = 0; i < Repeat; ++i) {
|
|
for (unsigned j = 0; j < Count; ++j) {
|
|
const unsigned long correct = 0 == j % 3 ? nw : nsum;
|
|
ASSERT_EQ((ScalarType)correct, -result[i].value[j]);
|
|
}
|
|
}
|
|
}
|
|
};
|
|
|
|
template <typename ScalarType, class DeviceType>
|
|
class TestReduceDynamic {
|
|
public:
|
|
typedef DeviceType execution_space;
|
|
typedef typename execution_space::size_type size_type;
|
|
|
|
TestReduceDynamic(const size_type nwork) {
|
|
run_test_dynamic(nwork);
|
|
run_test_dynamic_minmax(nwork);
|
|
run_test_dynamic_final(nwork);
|
|
}
|
|
|
|
void run_test_dynamic(const size_type nwork) {
|
|
typedef Test::RuntimeReduceFunctor<ScalarType, execution_space>
|
|
functor_type;
|
|
|
|
enum { Count = 3 };
|
|
enum { Repeat = 100 };
|
|
|
|
ScalarType result[Repeat][Count];
|
|
|
|
const unsigned long nw = nwork;
|
|
const unsigned long nsum =
|
|
nw % 2 ? nw * ((nw + 1) / 2) : (nw / 2) * (nw + 1);
|
|
|
|
for (unsigned i = 0; i < Repeat; ++i) {
|
|
if (i % 2 == 0) {
|
|
Kokkos::parallel_reduce(nwork, functor_type(nwork, Count), result[i]);
|
|
} else {
|
|
Kokkos::parallel_reduce("Reduce", nwork, functor_type(nwork, Count),
|
|
result[i]);
|
|
}
|
|
}
|
|
|
|
for (unsigned i = 0; i < Repeat; ++i) {
|
|
for (unsigned j = 0; j < Count; ++j) {
|
|
const unsigned long correct = 0 == j % 3 ? nw : nsum;
|
|
ASSERT_EQ((ScalarType)correct, result[i][j]);
|
|
}
|
|
}
|
|
}
|
|
|
|
void run_test_dynamic_minmax(const size_type nwork) {
|
|
typedef Test::RuntimeReduceMinMax<ScalarType, execution_space> functor_type;
|
|
|
|
enum { Count = 2 };
|
|
enum { Repeat = 100 };
|
|
|
|
ScalarType result[Repeat][Count];
|
|
|
|
for (unsigned i = 0; i < Repeat; ++i) {
|
|
if (i % 2 == 0) {
|
|
Kokkos::parallel_reduce(nwork, functor_type(nwork, Count), result[i]);
|
|
} else {
|
|
Kokkos::parallel_reduce("Reduce", nwork, functor_type(nwork, Count),
|
|
result[i]);
|
|
}
|
|
}
|
|
|
|
for (unsigned i = 0; i < Repeat; ++i) {
|
|
for (unsigned j = 0; j < Count; ++j) {
|
|
if (nwork == 0) {
|
|
ScalarType amin(std::numeric_limits<ScalarType>::min());
|
|
ScalarType amax(std::numeric_limits<ScalarType>::max());
|
|
const ScalarType correct = (j % 2) ? amax : amin;
|
|
ASSERT_EQ((ScalarType)correct, result[i][j]);
|
|
} else {
|
|
const unsigned long correct = j % 2 ? 1 : nwork;
|
|
ASSERT_EQ((ScalarType)correct, result[i][j]);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
void run_test_dynamic_final(const size_type nwork) {
|
|
typedef Test::RuntimeReduceFunctorFinal<execution_space> functor_type;
|
|
|
|
enum { Count = 3 };
|
|
enum { Repeat = 100 };
|
|
|
|
typename functor_type::scalar_type result[Repeat][Count];
|
|
|
|
const unsigned long nw = nwork;
|
|
const unsigned long nsum =
|
|
nw % 2 ? nw * ((nw + 1) / 2) : (nw / 2) * (nw + 1);
|
|
|
|
for (unsigned i = 0; i < Repeat; ++i) {
|
|
if (i % 2 == 0) {
|
|
Kokkos::parallel_reduce(nwork, functor_type(nwork, Count), result[i]);
|
|
} else {
|
|
Kokkos::parallel_reduce("TestKernelReduce", nwork,
|
|
functor_type(nwork, Count), result[i]);
|
|
}
|
|
}
|
|
|
|
for (unsigned i = 0; i < Repeat; ++i) {
|
|
for (unsigned j = 0; j < Count; ++j) {
|
|
const unsigned long correct = 0 == j % 3 ? nw : nsum;
|
|
ASSERT_EQ((ScalarType)correct, -result[i][j]);
|
|
}
|
|
}
|
|
}
|
|
};
|
|
|
|
template <typename ScalarType, class DeviceType>
|
|
class TestReduceDynamicView {
|
|
public:
|
|
typedef DeviceType execution_space;
|
|
typedef typename execution_space::size_type size_type;
|
|
|
|
TestReduceDynamicView(const size_type nwork) { run_test_dynamic_view(nwork); }
|
|
|
|
void run_test_dynamic_view(const size_type nwork) {
|
|
typedef Test::RuntimeReduceFunctor<ScalarType, execution_space>
|
|
functor_type;
|
|
|
|
typedef Kokkos::View<ScalarType*, DeviceType> result_type;
|
|
typedef typename result_type::HostMirror result_host_type;
|
|
|
|
const unsigned CountLimit = 23;
|
|
|
|
const unsigned long nw = nwork;
|
|
const unsigned long nsum =
|
|
nw % 2 ? nw * ((nw + 1) / 2) : (nw / 2) * (nw + 1);
|
|
|
|
for (unsigned count = 0; count < CountLimit; ++count) {
|
|
result_type result("result", count);
|
|
result_host_type host_result = Kokkos::create_mirror(result);
|
|
|
|
// Test result to host pointer:
|
|
|
|
std::string str("TestKernelReduce");
|
|
if (count % 2 == 0) {
|
|
Kokkos::parallel_reduce(nw, functor_type(nw, count),
|
|
host_result.data());
|
|
} else {
|
|
Kokkos::parallel_reduce(str, nw, functor_type(nw, count),
|
|
host_result.data());
|
|
}
|
|
|
|
for (unsigned j = 0; j < count; ++j) {
|
|
const unsigned long correct = 0 == j % 3 ? nw : nsum;
|
|
ASSERT_EQ(host_result(j), (ScalarType)correct);
|
|
host_result(j) = 0;
|
|
}
|
|
}
|
|
}
|
|
};
|
|
|
|
} // namespace
|
|
|
|
TEST(TEST_CATEGORY, long_reduce) {
|
|
TestReduce<long, TEST_EXECSPACE>(0);
|
|
TestReduce<long, TEST_EXECSPACE>(1000000);
|
|
}
|
|
|
|
TEST(TEST_CATEGORY, double_reduce) {
|
|
TestReduce<double, TEST_EXECSPACE>(0);
|
|
TestReduce<double, TEST_EXECSPACE>(1000000);
|
|
}
|
|
|
|
TEST(TEST_CATEGORY, long_reduce_dynamic) {
|
|
TestReduceDynamic<long, TEST_EXECSPACE>(0);
|
|
TestReduceDynamic<long, TEST_EXECSPACE>(1000000);
|
|
}
|
|
|
|
TEST(TEST_CATEGORY, double_reduce_dynamic) {
|
|
TestReduceDynamic<double, TEST_EXECSPACE>(0);
|
|
TestReduceDynamic<double, TEST_EXECSPACE>(1000000);
|
|
}
|
|
|
|
TEST(TEST_CATEGORY, long_reduce_dynamic_view) {
|
|
TestReduceDynamicView<long, TEST_EXECSPACE>(0);
|
|
TestReduceDynamicView<long, TEST_EXECSPACE>(1000000);
|
|
}
|
|
|
|
} // namespace Test
|