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Update Kokkos library in LAMMPS to v3.6.0

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This commit is contained in:
Stan Gerald Moore
2022-05-05 11:44:47 -06:00
parent bd4bbbddbe
commit b79c0bc7b4
380 changed files with 41928 additions and 8786 deletions
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170
lib/kokkos/algorithms/unit_tests/TestRandom.hpp
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@ -47,6 +47,7 @@
#include <iostream>
#include <cstdlib>
#include <cstdio>
#include <Kokkos_DynRankView.hpp>
#include <Kokkos_Timer.hpp>
#include <Kokkos_Core.hpp>
#include <Kokkos_Random.hpp>
@ -327,10 +328,6 @@ template <class RandomGenerator, class Scalar>
struct test_random_scalar {
using rnd_type = typename RandomGenerator::generator_type;
int pass_mean, pass_var, pass_covar;
int pass_hist1d_mean, pass_hist1d_var, pass_hist1d_covar;
int pass_hist3d_mean, pass_hist3d_var, pass_hist3d_covar;
test_random_scalar(
typename test_random_functor<RandomGenerator, int>::type_1d& density_1d,
typename test_random_functor<RandomGenerator, int>::type_3d& density_3d,
@ -357,18 +354,15 @@ struct test_random_scalar {
variance_expect / (result.variance / num_draws / 3) - 1.0;
double covariance_eps =
result.covariance / num_draws / 2 / variance_expect;
pass_mean = ((-tolerance < mean_eps) && (tolerance > mean_eps)) ? 1 : 0;
pass_var = ((-1.5 * tolerance < variance_eps) &&
(1.5 * tolerance > variance_eps))
? 1
: 0;
pass_covar = ((-2.0 * tolerance < covariance_eps) &&
(2.0 * tolerance > covariance_eps))
? 1
: 0;
cout << "Pass: " << pass_mean << " " << pass_var << " " << mean_eps << " "
<< variance_eps << " " << covariance_eps << " || " << tolerance
<< endl;
#if defined(KOKKOS_BHALF_T_IS_FLOAT) && !KOKKOS_BHALF_T_IS_FLOAT
if (!std::is_same<Scalar, Kokkos::Experimental::bhalf_t>::value) {
#endif
EXPECT_LT(std::abs(mean_eps), tolerance);
EXPECT_LT(std::abs(variance_eps), 1.5 * tolerance);
EXPECT_LT(std::abs(covariance_eps), 2.0 * tolerance);
#if defined(KOKKOS_BHALF_T_IS_FLOAT) && !KOKKOS_BHALF_T_IS_FLOAT
}
#endif
}
{
cout << " -- Testing 1-D histogram" << endl;
@ -399,17 +393,15 @@ struct test_random_scalar {
}
#endif
pass_hist1d_mean =
((-mean_eps_expect < mean_eps) && (mean_eps_expect > mean_eps)) ? 1
: 0;
pass_hist1d_var = ((-variance_eps_expect < variance_eps) &&
(variance_eps_expect > variance_eps))
? 1
: 0;
pass_hist1d_covar = ((-covariance_eps_expect < covariance_eps) &&
(covariance_eps_expect > covariance_eps))
? 1
: 0;
#if defined(KOKKOS_BHALF_T_IS_FLOAT) && !KOKKOS_BHALF_T_IS_FLOAT
if (!std::is_same<Scalar, Kokkos::Experimental::bhalf_t>::value) {
#endif
EXPECT_LT(std::abs(mean_eps), mean_eps_expect);
EXPECT_LT(std::abs(variance_eps), variance_eps_expect);
EXPECT_LT(std::abs(covariance_eps), covariance_eps_expect);
#if defined(KOKKOS_BHALF_T_IS_FLOAT) && !KOKKOS_BHALF_T_IS_FLOAT
}
#endif
cout << "Density 1D: " << mean_eps << " " << variance_eps << " "
<< (result.covariance / HIST_DIM1D / HIST_DIM1D) << " || "
@ -445,16 +437,15 @@ struct test_random_scalar {
}
#endif
pass_hist3d_mean =
((-tolerance < mean_eps) && (tolerance > mean_eps)) ? 1 : 0;
pass_hist3d_var = ((-variance_factor * tolerance < variance_eps) &&
(variance_factor * tolerance > variance_eps))
? 1
: 0;
pass_hist3d_covar = ((-variance_factor * tolerance < covariance_eps) &&
(variance_factor * tolerance > covariance_eps))
? 1
: 0;
#if defined(KOKKOS_BHALF_T_IS_FLOAT) && !KOKKOS_BHALF_T_IS_FLOAT
if (!std::is_same<Scalar, Kokkos::Experimental::bhalf_t>::value) {
#endif
EXPECT_LT(std::abs(mean_eps), tolerance);
EXPECT_LT(std::abs(variance_eps), variance_factor);
EXPECT_LT(std::abs(covariance_eps), variance_factor);
#if defined(KOKKOS_BHALF_T_IS_FLOAT) && !KOKKOS_BHALF_T_IS_FLOAT
}
#endif
cout << "Density 3D: " << mean_eps << " " << variance_eps << " "
<< result.covariance / HIST_DIM1D / HIST_DIM1D << " || " << tolerance
@ -479,106 +470,79 @@ void test_random(unsigned int num_draws) {
cout << "Test Scalar=int" << endl;
test_random_scalar<RandomGenerator, int> test_int(density_1d, density_3d,
pool, num_draws);
ASSERT_EQ(test_int.pass_mean, 1);
ASSERT_EQ(test_int.pass_var, 1);
ASSERT_EQ(test_int.pass_covar, 1);
ASSERT_EQ(test_int.pass_hist1d_mean, 1);
ASSERT_EQ(test_int.pass_hist1d_var, 1);
ASSERT_EQ(test_int.pass_hist1d_covar, 1);
ASSERT_EQ(test_int.pass_hist3d_mean, 1);
ASSERT_EQ(test_int.pass_hist3d_var, 1);
ASSERT_EQ(test_int.pass_hist3d_covar, 1);
deep_copy(density_1d, 0);
deep_copy(density_3d, 0);
cout << "Test Scalar=unsigned int" << endl;
test_random_scalar<RandomGenerator, unsigned int> test_uint(
density_1d, density_3d, pool, num_draws);
ASSERT_EQ(test_uint.pass_mean, 1);
ASSERT_EQ(test_uint.pass_var, 1);
ASSERT_EQ(test_uint.pass_covar, 1);
ASSERT_EQ(test_uint.pass_hist1d_mean, 1);
ASSERT_EQ(test_uint.pass_hist1d_var, 1);
ASSERT_EQ(test_uint.pass_hist1d_covar, 1);
ASSERT_EQ(test_uint.pass_hist3d_mean, 1);
ASSERT_EQ(test_uint.pass_hist3d_var, 1);
ASSERT_EQ(test_uint.pass_hist3d_covar, 1);
deep_copy(density_1d, 0);
deep_copy(density_3d, 0);
cout << "Test Scalar=int64_t" << endl;
test_random_scalar<RandomGenerator, int64_t> test_int64(
density_1d, density_3d, pool, num_draws);
ASSERT_EQ(test_int64.pass_mean, 1);
ASSERT_EQ(test_int64.pass_var, 1);
ASSERT_EQ(test_int64.pass_covar, 1);
ASSERT_EQ(test_int64.pass_hist1d_mean, 1);
ASSERT_EQ(test_int64.pass_hist1d_var, 1);
ASSERT_EQ(test_int64.pass_hist1d_covar, 1);
ASSERT_EQ(test_int64.pass_hist3d_mean, 1);
ASSERT_EQ(test_int64.pass_hist3d_var, 1);
ASSERT_EQ(test_int64.pass_hist3d_covar, 1);
deep_copy(density_1d, 0);
deep_copy(density_3d, 0);
cout << "Test Scalar=uint64_t" << endl;
test_random_scalar<RandomGenerator, uint64_t> test_uint64(
density_1d, density_3d, pool, num_draws);
ASSERT_EQ(test_uint64.pass_mean, 1);
ASSERT_EQ(test_uint64.pass_var, 1);
ASSERT_EQ(test_uint64.pass_covar, 1);
ASSERT_EQ(test_uint64.pass_hist1d_mean, 1);
ASSERT_EQ(test_uint64.pass_hist1d_var, 1);
ASSERT_EQ(test_uint64.pass_hist1d_covar, 1);
ASSERT_EQ(test_uint64.pass_hist3d_mean, 1);
ASSERT_EQ(test_uint64.pass_hist3d_var, 1);
ASSERT_EQ(test_uint64.pass_hist3d_covar, 1);
deep_copy(density_1d, 0);
deep_copy(density_3d, 0);
cout << "Test Scalar=half" << endl;
test_random_scalar<RandomGenerator, Kokkos::Experimental::half_t> test_half(
density_1d, density_3d, pool, num_draws);
ASSERT_EQ(test_half.pass_mean, 1);
ASSERT_EQ(test_half.pass_var, 1);
ASSERT_EQ(test_half.pass_covar, 1);
ASSERT_EQ(test_half.pass_hist1d_mean, 1);
ASSERT_EQ(test_half.pass_hist1d_var, 1);
ASSERT_EQ(test_half.pass_hist1d_covar, 1);
ASSERT_EQ(test_half.pass_hist3d_mean, 1);
ASSERT_EQ(test_half.pass_hist3d_var, 1);
ASSERT_EQ(test_half.pass_hist3d_covar, 1);
deep_copy(density_1d, 0);
deep_copy(density_3d, 0);
cout << "Test Scalar=bhalf" << endl;
test_random_scalar<RandomGenerator, Kokkos::Experimental::bhalf_t> test_bhalf(
density_1d, density_3d, pool, num_draws);
deep_copy(density_1d, 0);
deep_copy(density_3d, 0);
cout << "Test Scalar=float" << endl;
test_random_scalar<RandomGenerator, float> test_float(density_1d, density_3d,
pool, num_draws);
ASSERT_EQ(test_float.pass_mean, 1);
ASSERT_EQ(test_float.pass_var, 1);
ASSERT_EQ(test_float.pass_covar, 1);
ASSERT_EQ(test_float.pass_hist1d_mean, 1);
ASSERT_EQ(test_float.pass_hist1d_var, 1);
ASSERT_EQ(test_float.pass_hist1d_covar, 1);
ASSERT_EQ(test_float.pass_hist3d_mean, 1);
ASSERT_EQ(test_float.pass_hist3d_var, 1);
ASSERT_EQ(test_float.pass_hist3d_covar, 1);
deep_copy(density_1d, 0);
deep_copy(density_3d, 0);
cout << "Test Scalar=double" << endl;
test_random_scalar<RandomGenerator, double> test_double(
density_1d, density_3d, pool, num_draws);
ASSERT_EQ(test_double.pass_mean, 1);
ASSERT_EQ(test_double.pass_var, 1);
ASSERT_EQ(test_double.pass_covar, 1);
ASSERT_EQ(test_double.pass_hist1d_mean, 1);
ASSERT_EQ(test_double.pass_hist1d_var, 1);
ASSERT_EQ(test_double.pass_hist1d_covar, 1);
ASSERT_EQ(test_double.pass_hist3d_mean, 1);
ASSERT_EQ(test_double.pass_hist3d_var, 1);
ASSERT_EQ(test_double.pass_hist3d_covar, 1);
}
template <class ExecutionSpace, class Pool>
struct TestDynRankView {
using ReducerType = Kokkos::MinMax<double, Kokkos::HostSpace>;
using ReducerValueType = typename ReducerType::value_type;
Kokkos::DynRankView<double, ExecutionSpace> A;
TestDynRankView(int n) : A("a", n) {}
KOKKOS_FUNCTION void operator()(int i, ReducerValueType& update) const {
if (A(i) < update.min_val) update.min_val = A(i);
if (A(i) > update.max_val) update.max_val = A(i);
}
void run() {
Pool random(13);
double min = 10.;
double max = 100.;
Kokkos::fill_random(A, random, min, max);
ReducerValueType val;
Kokkos::parallel_reduce(Kokkos::RangePolicy<ExecutionSpace>(0, A.size()),
*this, ReducerType(val));
Kokkos::fence();
ASSERT_GE(val.min_val, min);
ASSERT_LE(val.max_val, max);
}
};
} // namespace Impl
template <typename ExecutionSpace>
@ -593,6 +557,9 @@ void test_random_xorshift64() {
Impl::test_random<Kokkos::Random_XorShift64_Pool<
Kokkos::Device<ExecutionSpace, typename ExecutionSpace::memory_space>>>(
num_draws);
Impl::TestDynRankView<ExecutionSpace,
Kokkos::Random_XorShift64_Pool<ExecutionSpace>>(10000)
.run();
}
template <typename ExecutionSpace>
@ -608,6 +575,9 @@ void test_random_xorshift1024() {
Impl::test_random<Kokkos::Random_XorShift1024_Pool<
Kokkos::Device<ExecutionSpace, typename ExecutionSpace::memory_space>>>(
num_draws);
Impl::TestDynRankView<ExecutionSpace,
Kokkos::Random_XorShift1024_Pool<ExecutionSpace>>(10000)
.run();
}
} // namespace Test