forked from MassiveAtoms/hashmap-bench
done
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@ -2,7 +2,7 @@ cmake_minimum_required(VERSION 3.15)
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project(another_studproject)
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set(CMAKE_CXX_STANDARD 17)
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set(CMAKE_CXX_FLAGS "-O3 -flto=thin")
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set(CMAKE_CXX_FLAGS "-O3 -flto=thin -march=native")
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add_executable(another_studproject
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./src/includes/generator.h
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./src/generator.cpp
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34
main.cpp
34
main.cpp
@ -12,8 +12,36 @@
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// we can use ^ to switch the map implementations to that
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// we can add some cli handling so we can specify which maps to tests (or all)
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int main() {
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string_test(std::unordered_map<std::string, std::string>{}, 10);
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int_test(std::unordered_map<int, int>{}, 10);
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time_point<steady_clock> start_test = steady_clock::now();
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string_test(std::unordered_map<std::string, std::string>{}, 1); // process gets killed for sizes >35000
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int_test(std::unordered_map<int, int>{}, 1);
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time_point<steady_clock> end_test = steady_clock::now();
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std::cout << "1 run all tests 1 map: " << duration_cast<minutes>(end_test-start_test).count() << " minutes";
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// test takes 52 mins for 10 runs for one hashmap
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// so it'll take ~3 hours per map if we want 30 runs per test
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/* if the other maps have about the same operation times ************
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// maps to benchmark:
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1. Google dense_hash_map
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2. Google sparse_hash_map
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3. folly F14ValueMap
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4. folly F14NodeMap
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5. Tessil/ordered-map
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6. Tessil/array-hash
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7. Tessil/hopscotch-map
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8. Tessil/sparse-map/
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9. abseil node_hash_map
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10. abseil flat_hash_map
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11. Glib GHashTable
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12. Boost unordered_map
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13. Qt QHash
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14. skarupke/flat_hash_map
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15. greg7mdp/sparsepp
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16. greg7mdp /parallel-hashmap (phmap::flat_hash_map and phmap::node_hash_map)
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17. emilk/emilib emilib::hashmap
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18. martinus robin_hood::unordered_node_map
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19. martinus/robin-hood-hashing/
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20. skarupke /flat_hash_map
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*/
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// test takes 52 mins for 10 runs for 1 dict
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}
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@ -10,7 +10,8 @@ std::vector<int> sizes = {
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50000, 100000, 150000, 200000, 250000, 300000, 350000, 400000, 500000,
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600000, 700000, 800000, 900000, 1000000,
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2000000, 3000000, 4000000, 5000000, 6000000, 7000000, 8000000, 9000000, 10000000,
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// 15000000, 20000000, 25000000, 30000000, 35000000, 40000000, 45000000, 50000000
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15000000, 20000000, 25000000, 30000000, 35000000,
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40000000, 45000000, 50000000
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};
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