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Optimize SYMV, SYR, SYR2, and TRMV product kernels

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libeigen/eigen!2228

Co-authored-by: Rasmus Munk Larsen <rmlarsen@gmail.com>
This commit is contained in:
Rasmus Munk Larsen
2026-03-01 19:40:11 -08:00
parent c66fc52868
commit 662d5c21ff
9 changed files with 866 additions and 151 deletions
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62
benchmarks/Core/bench_symv.cpp Normal file
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// Benchmarks for selfadjoint matrix-vector product (SYMV/HEMV).
//
// Tests y += selfadjointView(A) * x for various sizes and scalar types.
// Exercises SelfadjointMatrixVector.h kernel.
#include <benchmark/benchmark.h>
#include <Eigen/Core>
using namespace Eigen;
template <typename Scalar>
double symvFlops(Index n) {
// SYMV uses n^2 multiply-adds (exploiting symmetry)
return (NumTraits<Scalar>::IsComplex ? 8.0 : 2.0) * n * n;
}
// y += selfadjointView<Lower>(A) * x
template <typename Scalar>
static void BM_SYMV_Lower(benchmark::State& state) {
const Index n = state.range(0);
using Mat = Matrix<Scalar, Dynamic, Dynamic>;
using Vec = Matrix<Scalar, Dynamic, 1>;
Mat A = Mat::Random(n, n);
A = (A + A.transpose().eval()) / Scalar(2);
Vec x = Vec::Random(n);
Vec y = Vec::Random(n);
for (auto _ : state) {
y.noalias() += A.template selfadjointView<Lower>() * x;
benchmark::DoNotOptimize(y.data());
benchmark::ClobberMemory();
}
state.counters["GFLOPS"] = benchmark::Counter(symvFlops<Scalar>(n), benchmark::Counter::kIsIterationInvariantRate,
benchmark::Counter::kIs1000);
}
// y += selfadjointView<Upper>(A) * x
template <typename Scalar>
static void BM_SYMV_Upper(benchmark::State& state) {
const Index n = state.range(0);
using Mat = Matrix<Scalar, Dynamic, Dynamic>;
using Vec = Matrix<Scalar, Dynamic, 1>;
Mat A = Mat::Random(n, n);
A = (A + A.transpose().eval()) / Scalar(2);
Vec x = Vec::Random(n);
Vec y = Vec::Random(n);
for (auto _ : state) {
y.noalias() += A.template selfadjointView<Upper>() * x;
benchmark::DoNotOptimize(y.data());
benchmark::ClobberMemory();
}
state.counters["GFLOPS"] = benchmark::Counter(symvFlops<Scalar>(n), benchmark::Counter::kIsIterationInvariantRate,
benchmark::Counter::kIs1000);
}
static void SymvSizes(::benchmark::Benchmark* b) {
for (int n : {8, 16, 32, 64, 128, 256, 512, 1024, 2048}) b->Arg(n);
}
BENCHMARK(BM_SYMV_Lower<float>)->Apply(SymvSizes)->Name("SYMV_Lower_float");
BENCHMARK(BM_SYMV_Lower<double>)->Apply(SymvSizes)->Name("SYMV_Lower_double");
BENCHMARK(BM_SYMV_Upper<float>)->Apply(SymvSizes)->Name("SYMV_Upper_float");
BENCHMARK(BM_SYMV_Upper<double>)->Apply(SymvSizes)->Name("SYMV_Upper_double");