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/*
* Copyright 2020 Patrick Stotko
* 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 <iostream>
#include <thrust/copy.h>
#include <thrust/reduce.h>
#include <thrust/sequence.h>
#include <stdgpu/iterator.h> // device_begin, device_end
#include <stdgpu/memory.h> // createDeviceArray, destroyDeviceArray
#include <stdgpu/platform.h> // STDGPU_HOST_DEVICE
#include <stdgpu/unordered_map.cuh> // stdgpu::unordered_map
struct is_odd
{
STDGPU_HOST_DEVICE bool
operator()(const int x) const
{
return x % 2 == 1;
}
};
struct square
{
STDGPU_HOST_DEVICE int
operator()(const int x) const
{
return x * x;
}
};
struct int_pair_plus
{
STDGPU_HOST_DEVICE stdgpu::pair<int, int>
operator()(const stdgpu::pair<int, int>& lhs, const stdgpu::pair<int, int>& rhs) const
{
return { lhs.first + rhs.first, lhs.second + rhs.second };
}
};
__global__ void
insert_neighbors(const int* d_result, const stdgpu::index_t n, stdgpu::unordered_map<int, int> map)
{
stdgpu::index_t i = static_cast<stdgpu::index_t>(blockIdx.x * blockDim.x + threadIdx.x);
if (i >= n)
return;
int num = d_result[i];
int num_neighborhood[3] = { num - 1, num, num + 1 };
for (int num_neighbor : num_neighborhood)
{
map.emplace(num_neighbor, square()(num_neighbor));
}
}
int
main()
{
//
// EXAMPLE DESCRIPTION
// -------------------
// This example demonstrates how stdgpu::unordered_map is used to compute a duplicate-free set of numbers.
//
const stdgpu::index_t n = 100;
int* d_input = createDeviceArray<int>(n);
int* d_result = createDeviceArray<int>(n / 2);
stdgpu::unordered_map<int, int> map = stdgpu::unordered_map<int, int>::createDeviceObject(n);
thrust::sequence(stdgpu::device_begin(d_input), stdgpu::device_end(d_input), 1);
// d_input : 1, 2, 3, ..., 100
thrust::copy_if(stdgpu::device_cbegin(d_input),
stdgpu::device_cend(d_input),
stdgpu::device_begin(d_result),
is_odd());
// d_result : 1, 3, 5, ..., 99
stdgpu::index_t threads = 32;
stdgpu::index_t blocks = (n / 2 + threads - 1) / threads;
insert_neighbors<<<static_cast<unsigned int>(blocks), static_cast<unsigned int>(threads)>>>(d_result, n / 2, map);
cudaDeviceSynchronize();
// map : 0, 1, 2, 3, ..., 100
auto range_map = map.device_range();
stdgpu::pair<int, int> sum =
thrust::reduce(range_map.begin(), range_map.end(), stdgpu::pair<int, int>(0, 0), int_pair_plus());
const stdgpu::pair<int, int> sum_closed_form = { n * (n + 1) / 2, n * (n + 1) * (2 * n + 1) / 6 };
std::cout << "The duplicate-free map of numbers contains " << map.size() << " elements (" << n + 1
<< " expected) and the computed sums are (" << sum.first << ", " << sum.second << ") (("
<< sum_closed_form.first << ", " << sum_closed_form.second << ") expected)" << std::endl;
destroyDeviceArray<int>(d_input);
destroyDeviceArray<int>(d_result);
stdgpu::unordered_map<int, int>::destroyDeviceObject(map);
}
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