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63 lines
2.3 KiB
C++
63 lines
2.3 KiB
C++
// Benchmarks for selfadjoint matrix-vector product (SYMV/HEMV).
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//
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// Tests y += selfadjointView(A) * x for various sizes and scalar types.
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// Exercises SelfadjointMatrixVector.h kernel.
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#include <benchmark/benchmark.h>
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#include <Eigen/Core>
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using namespace Eigen;
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template <typename Scalar>
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double symvFlops(Index n) {
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// SYMV uses n^2 multiply-adds (exploiting symmetry)
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return (NumTraits<Scalar>::IsComplex ? 8.0 : 2.0) * n * n;
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}
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// y += selfadjointView<Lower>(A) * x
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template <typename Scalar>
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static void BM_SYMV_Lower(benchmark::State& state) {
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const Index n = state.range(0);
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using Mat = Matrix<Scalar, Dynamic, Dynamic>;
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using Vec = Matrix<Scalar, Dynamic, 1>;
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Mat A = Mat::Random(n, n);
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A = (A + A.transpose().eval()) / Scalar(2);
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Vec x = Vec::Random(n);
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Vec y = Vec::Random(n);
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for (auto _ : state) {
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y.noalias() += A.template selfadjointView<Lower>() * x;
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benchmark::DoNotOptimize(y.data());
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benchmark::ClobberMemory();
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}
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state.counters["GFLOPS"] = benchmark::Counter(symvFlops<Scalar>(n), benchmark::Counter::kIsIterationInvariantRate,
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benchmark::Counter::kIs1000);
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}
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// y += selfadjointView<Upper>(A) * x
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template <typename Scalar>
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static void BM_SYMV_Upper(benchmark::State& state) {
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const Index n = state.range(0);
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using Mat = Matrix<Scalar, Dynamic, Dynamic>;
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using Vec = Matrix<Scalar, Dynamic, 1>;
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Mat A = Mat::Random(n, n);
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A = (A + A.transpose().eval()) / Scalar(2);
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Vec x = Vec::Random(n);
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Vec y = Vec::Random(n);
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for (auto _ : state) {
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y.noalias() += A.template selfadjointView<Upper>() * x;
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benchmark::DoNotOptimize(y.data());
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benchmark::ClobberMemory();
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}
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state.counters["GFLOPS"] = benchmark::Counter(symvFlops<Scalar>(n), benchmark::Counter::kIsIterationInvariantRate,
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benchmark::Counter::kIs1000);
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}
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static void SymvSizes(::benchmark::Benchmark* b) {
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for (int n : {8, 16, 32, 64, 128, 256, 512, 1024, 2048}) b->Arg(n);
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}
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BENCHMARK(BM_SYMV_Lower<float>)->Apply(SymvSizes)->Name("SYMV_Lower_float");
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BENCHMARK(BM_SYMV_Lower<double>)->Apply(SymvSizes)->Name("SYMV_Lower_double");
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BENCHMARK(BM_SYMV_Upper<float>)->Apply(SymvSizes)->Name("SYMV_Upper_float");
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BENCHMARK(BM_SYMV_Upper<double>)->Apply(SymvSizes)->Name("SYMV_Upper_double");
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