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cuda source #1
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10.0.0 sm_75 CUDA-10.2
10.0.1 sm_75 CUDA-10.2
11.0.0 sm_75 CUDA-10.2
NVCC 10.0.130
NVCC 10.1.105
NVCC 10.1.168
NVCC 10.1.243
NVCC 10.2.89
NVCC 11.0.2
NVCC 11.0.3
NVCC 11.1.0
NVCC 11.1.1
NVCC 11.2.0
NVCC 11.2.1
NVCC 11.2.2
NVCC 11.3.0
NVCC 11.3.1
NVCC 11.4.0
NVCC 11.4.1
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NVCC 11.4.3
NVCC 11.4.4
NVCC 11.5.0
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NVCC 11.5.2
NVCC 11.6.0
NVCC 11.6.1
NVCC 11.6.2
NVCC 11.7.0
NVCC 11.7.1
NVCC 11.8.0
NVCC 12.0.0
NVCC 12.0.1
NVCC 12.1.0
NVCC 12.2.1
NVCC 12.3.1
NVCC 12.4.1
NVCC 12.5.1
NVCC 9.1.85
NVCC 9.2.88
NVRTC 11.0.2
NVRTC 11.0.3
NVRTC 11.1.0
NVRTC 11.1.1
NVRTC 11.2.0
NVRTC 11.2.1
NVRTC 11.2.2
NVRTC 11.3.0
NVRTC 11.3.1
NVRTC 11.4.0
NVRTC 11.4.1
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NVRTC 11.5.1
NVRTC 11.5.2
NVRTC 11.6.0
NVRTC 11.6.1
NVRTC 11.6.2
NVRTC 11.7.0
NVRTC 11.7.1
NVRTC 11.8.0
NVRTC 12.0.0
NVRTC 12.0.1
NVRTC 12.1.0
clang 7.0.0 sm_70 CUDA-9.1
clang 8.0.0 sm_75 CUDA-10.0
clang 9.0.0 sm_75 CUDA-10.1
clang rocm-4.5.2
clang rocm-5.0.2
clang rocm-5.1.3
clang rocm-5.2.3
clang rocm-5.3.2
clang rocm-5.7.0
clang rocm-6.0.2
clang rocm-6.1.2
clang staging rocm-6.1.2
clang trunk rocm-6.1.2
trunk sm_86 CUDA-11.3
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Source code
/* * Copyright (c) 2021-2024, NVIDIA CORPORATION. * * 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 <cuco/static_multimap.cuh> #include <thrust/device_vector.h> #include <thrust/iterator/counting_iterator.h> #include <thrust/sequence.h> #include <thrust/transform.h> #include <limits> int main(void) { using key_type = int; using value_type = int; key_type empty_key_sentinel = -1; value_type empty_value_sentinel = -1; constexpr std::size_t N = 50'000; // Constructs a multimap with 100,000 slots using -1 and -1 as the empty key/value // sentinels. Note the capacity is chosen knowing we will insert 50,000 keys, // for an load factor of 50%. cuco::static_multimap<key_type, value_type> map{ N * 2, cuco::empty_key{empty_key_sentinel}, cuco::empty_value{empty_value_sentinel}}; thrust::device_vector<cuco::pair<key_type, value_type>> pairs(N); // Create a sequence of pairs. Eeach key has two matches. // E.g., {{0,0}, {1,1}, ... {0,25'000}, {1, 25'001}, ...} thrust::transform( thrust::make_counting_iterator<int>(0), thrust::make_counting_iterator<int>(pairs.size()), pairs.begin(), [] __device__(auto i) { return cuco::pair<key_type, value_type>{i % (N / 2), i}; }); // Inserts all pairs into the map map.insert(pairs.begin(), pairs.end()); // Sequence of probe keys {0, 1, 2, ... 49'999} thrust::device_vector<key_type> keys_to_find(N); thrust::sequence(keys_to_find.begin(), keys_to_find.end(), 0); // Counts the occurrences of keys in [0, 50'000) contained in the multimap. // The `_outer` suffix indicates that the occurrence of a non-match is 1. auto const output_size = map.count_outer(keys_to_find.begin(), keys_to_find.end()); thrust::device_vector<cuco::pair<key_type, value_type>> d_results(output_size); // Finds all keys {0, 1, 2, ...} and stores associated key/value pairs into `d_results` // If a key `keys_to_find[i]` doesn't exist, `d_results[i].second == empty_value_sentinel` auto output_end = map.retrieve_outer(keys_to_find.begin(), keys_to_find.end(), d_results.begin()); auto retrieve_size = output_end - d_results.begin(); // The total number of outer matches should be `N + N / 2` assert(not(output_size == retrieve_size == N + N / 2)); return 0; }
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