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Merge pull request #2 from ypodlesov/CG
Add CG method.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,3 +1,38 @@ | ||
| ### A simple version of CG (Conjugate Gradient). | ||
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| ##### Benchmark results in file `bench_results.txt` | ||
| ##### Benchmark results | ||
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| Benchmark CG | ||
| ............................................................................... | ||
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| benchmark name samples iterations est run time | ||
| mean low mean high mean | ||
| std dev low std dev high std dev | ||
| ------------------------------------------------------------------------------- | ||
| Size 256 5 1 158.155 ms | ||
| 30.6362 ms 30.3948 ms 30.8777 ms | ||
| 278.589 us 168.836 us 367.73 us | ||
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| Size 512 5 1 474.875 ms | ||
| 93.5246 ms 93.1857 ms 93.8352 ms | ||
| 384.98 us 251.424 us 502.811 us | ||
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| Size 1024 5 1 1.28954 s | ||
| 254.104 ms 253.491 ms 254.573 ms | ||
| 642.205 us 488.519 us 765.256 us | ||
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| Size 2048 5 1 3.11173 s | ||
| 618.631 ms 616.151 ms 621.485 ms | ||
| 2.99239 ms 2.11292 ms 3.53132 ms | ||
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| Size 4096 5 1 6.72483 s | ||
| 1.33877 s 1.33262 s 1.3448 s | ||
| 7.21186 ms 4.33359 ms 10.6794 ms | ||
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| Size 8192 5 1 17.1783 s | ||
| 3.45489 s 3.44111 s 3.48345 s | ||
| 21.1881 ms 4.29948 ms 29.4589 ms | ||
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| Size 16384 5 1 38.4892 s | ||
| 7.63827 s 7.62766 s 7.65727 s | ||
| 15.5452 ms 5.99529 ms 21.0671 ms |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,5 +1,7 @@ | ||
| #pragma once | ||
| #include <sparse_matrix.h> | ||
| #include <matrix.h> | ||
| #include <vector.h> | ||
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| bool ConjugateGradient(const SparseMatrix<double>& a, const Vector<double>& b, Vector<double>& x); | ||
| bool ConjugateGradient(const SparseMatrix<double>& a, const Vector<double>& b, Vector<double>& x); | ||
| bool ConjugateGradient(const Matrix<double>& a, const Vector<double>& b, Vector<double>& x); |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,42 +1,93 @@ | ||
| #include <filesystem> | ||
| #include <fstream> | ||
| #include <sstream> | ||
| #include "conjugate_gradient.h" | ||
| #include "helpers.h" | ||
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| #include <catch2/catch_test_macros.hpp> | ||
| #include <catch2/benchmark/catch_benchmark.hpp> | ||
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| void Prepare(TMatrix<double>& A, TVector<double>& b, const size_t n) { | ||
| std::srand(std::time(nullptr)); | ||
| A = TMatrix<double>::GenerateRandomSymmetricDefinite(n, EDefiniteness::Positive); | ||
| b = TVector<double>::CreateRandom(n); | ||
| void Prepare(SparseMatrix<double>& a, Vector<double>& b, const size_t n) { | ||
| std::stringstream file_name; | ||
| file_name << std::filesystem::current_path().string() << "/../" << "matrix_examples/sparse_spd/" << n; | ||
| std::ifstream fstream; | ||
| fstream.open(file_name.str()); | ||
| REQUIRE(fstream.is_open()); | ||
| fstream >> a; | ||
| fstream.close(); | ||
| REQUIRE(a.data_); | ||
| NHelpers::GenRandomVector(b, n, true); | ||
| Vector<double> x(n); | ||
| } | ||
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| TEST_CASE("Benchmark CG") { | ||
| TMatrix<double> A; | ||
| TVector<double> b; | ||
| TVector<double> x; | ||
| TVector<double> result; | ||
| { | ||
| Prepare(A, b, 10); | ||
| BENCHMARK("Size 10") { | ||
| ConjugateGradient(A, b, x); | ||
| SparseMatrix<double> a_sparse; | ||
| Matrix<double> a_dense; | ||
| Vector<double> b; | ||
| Vector<double> x; | ||
| Prepare(a_sparse, b, 256); | ||
| BENCHMARK("Size 256") { | ||
| ConjugateGradient(a_sparse, b, x); | ||
| }; | ||
| REQUIRE(TMatrix<double>::MVMultiply(A, x, result)); | ||
| REQUIRE(RoughEq<double, double>(TVector<double>::Norm2(result - b), 0, 0.001)); | ||
| } | ||
| { | ||
| Prepare(A, b, 500); | ||
| BENCHMARK("Size 500") { | ||
| ConjugateGradient(A, b, x); | ||
| SparseMatrix<double> a_sparse; | ||
| Matrix<double> a_dense; | ||
| Vector<double> b; | ||
| Vector<double> x; | ||
| Prepare(a_sparse, b, 512); | ||
| BENCHMARK("Size 512") { | ||
| ConjugateGradient(a_sparse, b, x); | ||
| }; | ||
| REQUIRE(TMatrix<double>::MVMultiply(A, x, result)); | ||
| REQUIRE(RoughEq<double, double>(TVector<double>::Norm2(result - b), 0, 0.001)); | ||
| } | ||
| { | ||
| Prepare(A, b, 1000); | ||
| BENCHMARK("Size 1000") { | ||
| ConjugateGradient(A, b, x); | ||
| SparseMatrix<double> a_sparse; | ||
| Matrix<double> a_dense; | ||
| Vector<double> b; | ||
| Vector<double> x; | ||
| Prepare(a_sparse, b, 1024); | ||
| BENCHMARK("Size 1024") { | ||
| ConjugateGradient(a_sparse, b, x); | ||
| }; | ||
| } | ||
| { | ||
| SparseMatrix<double> a_sparse; | ||
| Matrix<double> a_dense; | ||
| Vector<double> b; | ||
| Vector<double> x; | ||
| Prepare(a_sparse, b, 2048); | ||
| BENCHMARK("Size 2048") { | ||
| ConjugateGradient(a_sparse, b, x); | ||
| }; | ||
| } | ||
| { | ||
| SparseMatrix<double> a_sparse; | ||
| Matrix<double> a_dense; | ||
| Vector<double> b; | ||
| Vector<double> x; | ||
| Prepare(a_sparse, b, 4096); | ||
| BENCHMARK("Size 4096") { | ||
| ConjugateGradient(a_sparse, b, x); | ||
| }; | ||
| } | ||
| { | ||
| SparseMatrix<double> a_sparse; | ||
| Matrix<double> a_dense; | ||
| Vector<double> b; | ||
| Vector<double> x; | ||
| Prepare(a_sparse, b, 8192); | ||
| BENCHMARK("Size 8192") { | ||
| ConjugateGradient(a_sparse, b, x); | ||
| }; | ||
| } | ||
| { | ||
| SparseMatrix<double> a_sparse; | ||
| Matrix<double> a_dense; | ||
| Vector<double> b; | ||
| Vector<double> x; | ||
| Prepare(a_sparse, b, 16384); | ||
| BENCHMARK("Size 16384") { | ||
| ConjugateGradient(a_sparse, b, x); | ||
| }; | ||
| REQUIRE(TMatrix<double>::MVMultiply(A, x, result)); | ||
| REQUIRE(RoughEq<double, double>(TVector<double>::Norm2(result - b), 0, 0.01)); | ||
| } | ||
| } |
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