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/*
* Copyright 2008-2013 NVIDIA Corporation
* Modifications Copyright© 2019 Advanced Micro Devices, Inc. All rights reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <thrust/iterator/zip_iterator.h>
#include <thrust/reduce.h>
#if THRUST_DEVICE_SYSTEM == THRUST_DEVICE_SYSTEM_CUDA
#include <unittest/cuda/testframework.h>
#endif
#include "test_header.hpp"
typedef ::testing::Types<Params<unsigned short>,
Params<unsigned int>,
Params<unsigned long>,
Params<unsigned long long>>
UnsignedIntegralTypesParams;
TESTS_DEFINE(ZipIteratorReduceByKeyTests, UnsignedIntegralTypesParams);
template <typename Tuple>
struct TuplePlus
{
__host__ __device__ Tuple operator()(Tuple x, Tuple y) const
{
using namespace thrust;
return make_tuple(get<0>(x) + get<0>(y), get<1>(x) + get<1>(y));
}
}; // end TuplePlus
TYPED_TEST(ZipIteratorReduceByKeyTests, TestZipIteratorReduceByKey)
{
using T = typename TestFixture::input_type;
SCOPED_TRACE(testing::Message() << "with device_id= " << test::set_device_from_ctest());
for(auto size : get_sizes())
{
SCOPED_TRACE(testing::Message() << "with size= " << size);
for(auto seed : get_seeds())
{
SCOPED_TRACE(testing::Message() << "with seed= " << seed);
thrust::host_vector<T> h_data0 = get_random_data<T>(
size, std::numeric_limits<T>::min(), std::numeric_limits<T>::max(), seed);
thrust::host_vector<T> h_data1 = get_random_data<T>(
size,
std::numeric_limits<T>::min(),
std::numeric_limits<T>::max(),
seed + seed_value_addition
);
thrust::host_vector<T> h_data2 = get_random_data<T>(
size,
std::numeric_limits<T>::min(),
std::numeric_limits<T>::max(),
seed + 2 * seed_value_addition
);
thrust::device_vector<T> d_data0 = h_data0;
thrust::device_vector<T> d_data1 = h_data1;
thrust::device_vector<T> d_data2 = h_data2;
typedef thrust::tuple<T, T> Tuple;
// integer key, tuple value
{
thrust::host_vector<T> h_data3(size, 0);
thrust::host_vector<T> h_data4(size, 0);
thrust::host_vector<T> h_data5(size, 0);
thrust::device_vector<T> d_data3(size, 0);
thrust::device_vector<T> d_data4(size, 0);
thrust::device_vector<T> d_data5(size, 0);
// run on host
thrust::reduce_by_key(
h_data0.begin(), h_data0.end(),
thrust::make_zip_iterator(thrust::make_tuple(h_data1.begin(), h_data2.begin())),
h_data3.begin(),
thrust::make_zip_iterator(thrust::make_tuple(h_data4.begin(), h_data5.begin())),
thrust::equal_to<T>(),
TuplePlus<Tuple>());
// run on device
thrust::reduce_by_key(
d_data0.begin(), d_data0.end(),
thrust::make_zip_iterator(thrust::make_tuple(d_data1.begin(), d_data2.begin())),
d_data3.begin(),
thrust::make_zip_iterator(thrust::make_tuple(d_data4.begin(), d_data5.begin())),
thrust::equal_to<T>(),
TuplePlus<Tuple>());
ASSERT_EQ(h_data3, d_data3);
ASSERT_EQ(h_data4, d_data4);
ASSERT_EQ(h_data5, d_data5);
}
// The tests below get miscompiled on Tesla hw for 8b types
#if THRUST_DEVICE_SYSTEM == THRUST_DEVICE_SYSTEM_CUDA
if(const CUDATestDriver* driver
= dynamic_cast<const CUDATestDriver*>(&UnitTestDriver::s_driver()))
{
if(typeid(T) == typeid(unittest::uint8_t)
&& driver->current_device_architecture() < 200)
{
KNOWN_FAILURE;
} // end if
} // end if
#endif
// tuple key, tuple value
{
thrust::host_vector<T> h_data3(size, 0);
thrust::host_vector<T> h_data4(size, 0);
thrust::host_vector<T> h_data5(size, 0);
thrust::host_vector<T> h_data6(size, 0);
thrust::device_vector<T> d_data3(size, 0);
thrust::device_vector<T> d_data4(size, 0);
thrust::device_vector<T> d_data5(size, 0);
thrust::device_vector<T> d_data6(size, 0);
// run on host
reduce_by_key(thrust::make_zip_iterator(thrust::make_tuple(h_data0.begin(), h_data0.begin())),
thrust::make_zip_iterator(thrust::make_tuple(h_data0.end(), h_data0.end())),
thrust::make_zip_iterator(thrust::make_tuple(h_data1.begin(), h_data2.begin())),
thrust::make_zip_iterator(thrust::make_tuple(h_data3.begin(), h_data4.begin())),
thrust::make_zip_iterator(thrust::make_tuple(h_data5.begin(), h_data6.begin())),
thrust::equal_to<Tuple>(),
TuplePlus<Tuple>());
// run on device
reduce_by_key(thrust::make_zip_iterator(thrust::make_tuple(d_data0.begin(), d_data0.begin())),
thrust::make_zip_iterator(thrust::make_tuple(d_data0.end(), d_data0.end())),
thrust::make_zip_iterator(thrust::make_tuple(d_data1.begin(), d_data2.begin())),
thrust::make_zip_iterator(thrust::make_tuple(d_data3.begin(), d_data4.begin())),
thrust::make_zip_iterator(thrust::make_tuple(d_data5.begin(), d_data6.begin())),
thrust::equal_to<Tuple>(),
TuplePlus<Tuple>());
ASSERT_EQ(h_data3, d_data3);
ASSERT_EQ(h_data4, d_data4);
ASSERT_EQ(h_data5, d_data5);
ASSERT_EQ(h_data6, d_data6);
}
}
}
}
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