|  |  | 
|  | #include <iostream> | 
|  | #include <Eigen/Core> | 
|  | #include <bench/BenchUtil.h> | 
|  | using namespace Eigen; | 
|  |  | 
|  | #ifndef REPEAT | 
|  | #define REPEAT 100000 | 
|  | #endif | 
|  |  | 
|  | #ifndef TRIES | 
|  | #define TRIES 20 | 
|  | #endif | 
|  |  | 
|  | typedef double Scalar; | 
|  |  | 
|  | template <typename MatrixType> | 
|  | __attribute__((noinline)) void bench_reverse(const MatrixType& m) { | 
|  | int rows = m.rows(); | 
|  | int cols = m.cols(); | 
|  | int size = m.size(); | 
|  |  | 
|  | int repeats = (REPEAT * 1000) / size; | 
|  | MatrixType a = MatrixType::Random(rows, cols); | 
|  | MatrixType b = MatrixType::Random(rows, cols); | 
|  |  | 
|  | BenchTimer timerB, timerH, timerV; | 
|  |  | 
|  | Scalar acc = 0; | 
|  | int r = internal::random<int>(0, rows - 1); | 
|  | int c = internal::random<int>(0, cols - 1); | 
|  | for (int t = 0; t < TRIES; ++t) { | 
|  | timerB.start(); | 
|  | for (int k = 0; k < repeats; ++k) { | 
|  | asm("#begin foo"); | 
|  | b = a.reverse(); | 
|  | asm("#end foo"); | 
|  | acc += b.coeff(r, c); | 
|  | } | 
|  | timerB.stop(); | 
|  | } | 
|  |  | 
|  | if (MatrixType::RowsAtCompileTime == Dynamic) | 
|  | std::cout << "dyn   "; | 
|  | else | 
|  | std::cout << "fixed "; | 
|  | std::cout << rows << " x " << cols << " \t" << (timerB.value() * REPEAT) / repeats << "s " | 
|  | << "(" << 1e-6 * size * repeats / timerB.value() << " MFLOPS)\t"; | 
|  |  | 
|  | std::cout << "\n"; | 
|  | // make sure the compiler does not optimize too much | 
|  | if (acc == 123) std::cout << acc; | 
|  | } | 
|  |  | 
|  | int main(int argc, char* argv[]) { | 
|  | const int dynsizes[] = {4, 6, 8, 16, 24, 32, 49, 64, 128, 256, 512, 900, 0}; | 
|  | std::cout << "size            no sqrt                           standard"; | 
|  | //   #ifdef BENCH_GSL | 
|  | //   std::cout << "       GSL (standard + double + ATLAS)  "; | 
|  | //   #endif | 
|  | std::cout << "\n"; | 
|  | for (uint i = 0; dynsizes[i] > 0; ++i) { | 
|  | bench_reverse(Matrix<Scalar, Dynamic, Dynamic>(dynsizes[i], dynsizes[i])); | 
|  | bench_reverse(Matrix<Scalar, Dynamic, 1>(dynsizes[i] * dynsizes[i])); | 
|  | } | 
|  | //   bench_reverse(Matrix<Scalar,2,2>()); | 
|  | //   bench_reverse(Matrix<Scalar,3,3>()); | 
|  | //   bench_reverse(Matrix<Scalar,4,4>()); | 
|  | //   bench_reverse(Matrix<Scalar,5,5>()); | 
|  | //   bench_reverse(Matrix<Scalar,6,6>()); | 
|  | //   bench_reverse(Matrix<Scalar,7,7>()); | 
|  | //   bench_reverse(Matrix<Scalar,8,8>()); | 
|  | //   bench_reverse(Matrix<Scalar,12,12>()); | 
|  | //   bench_reverse(Matrix<Scalar,16,16>()); | 
|  | return 0; | 
|  | } |