| |
| #ifndef EIGEN_BENCH_BASICBENCH_H |
| #define EIGEN_BENCH_BASICBENCH_H |
| |
| enum { LazyEval, EarlyEval, OmpEval }; |
| |
| template <int Mode, typename MatrixType> |
| void benchBasic_loop(const MatrixType& I, MatrixType& m, int iterations) __attribute__((noinline)); |
| |
| template <int Mode, typename MatrixType> |
| void benchBasic_loop(const MatrixType& I, MatrixType& m, int iterations) { |
| for (int a = 0; a < iterations; a++) { |
| if (Mode == LazyEval) { |
| asm("#begin_bench_loop LazyEval"); |
| if (MatrixType::SizeAtCompileTime != Eigen::Dynamic) asm("#fixedsize"); |
| m = (I + 0.00005 * (m + m.lazyProduct(m))).eval(); |
| } else if (Mode == OmpEval) { |
| asm("#begin_bench_loop OmpEval"); |
| if (MatrixType::SizeAtCompileTime != Eigen::Dynamic) asm("#fixedsize"); |
| m = (I + 0.00005 * (m + m.lazyProduct(m))).eval(); |
| } else { |
| asm("#begin_bench_loop EarlyEval"); |
| if (MatrixType::SizeAtCompileTime != Eigen::Dynamic) asm("#fixedsize"); |
| m = I + 0.00005 * (m + m * m); |
| } |
| asm("#end_bench_loop"); |
| } |
| } |
| |
| template <int Mode, typename MatrixType> |
| double benchBasic(const MatrixType& mat, int size, int tries) __attribute__((noinline)); |
| |
| template <int Mode, typename MatrixType> |
| double benchBasic(const MatrixType& mat, int iterations, int tries) { |
| const int rows = mat.rows(); |
| const int cols = mat.cols(); |
| |
| MatrixType I(rows, cols); |
| MatrixType m(rows, cols); |
| |
| initMatrix_identity(I); |
| |
| Eigen::BenchTimer timer; |
| for (uint t = 0; t < tries; ++t) { |
| initMatrix_random(m); |
| timer.start(); |
| benchBasic_loop<Mode>(I, m, iterations); |
| timer.stop(); |
| cerr << m; |
| } |
| return timer.value(); |
| }; |
| |
| #endif // EIGEN_BENCH_BASICBENCH_H |