blob: 4d1c8eadf3ea9549e2e22a6e64f1e42b4b4d2b62 [file] [edit]
// Benchmarks for matrix logarithm.
// Inverse of matrix exponential, used for Lie group log maps.
#include <benchmark/benchmark.h>
#include <Eigen/Core>
#include <unsupported/Eigen/MatrixFunctions>
using namespace Eigen;
#ifndef SCALAR
#define SCALAR double
#endif
typedef SCALAR Scalar;
static void BM_MatrixLog(benchmark::State& state) {
int n = state.range(0);
typedef Matrix<Scalar, Dynamic, Dynamic> MatrixType;
// Generate a matrix close to identity for stable log computation.
MatrixType A = MatrixType::Identity(n, n) + MatrixType::Random(n, n) / Scalar(n * 2);
// Ensure A is in the principal branch by computing exp(small matrix).
A = (MatrixType::Random(n, n) / Scalar(n * 4)).exp();
MatrixType result(n, n);
for (auto _ : state) {
result = A.log();
benchmark::DoNotOptimize(result.data());
benchmark::ClobberMemory();
}
}
template <int N>
static void BM_MatrixLog_Fixed(benchmark::State& state) {
typedef Matrix<Scalar, N, N> MatrixType;
MatrixType A = (MatrixType::Random() / Scalar(N * 4)).exp();
MatrixType result;
for (auto _ : state) {
result = A.log();
benchmark::DoNotOptimize(result.data());
benchmark::ClobberMemory();
}
}
BENCHMARK(BM_MatrixLog)->Arg(2)->Arg(3)->Arg(4)->Arg(8)->Arg(16)->Arg(32)->Arg(64);
BENCHMARK(BM_MatrixLog_Fixed<2>);
BENCHMARK(BM_MatrixLog_Fixed<3>);
BENCHMARK(BM_MatrixLog_Fixed<4>);