mirror/eigen
2
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2025-03-07 18:27:40 +08:00
Code Issues Packages Projects Releases Wiki Activity

Update bench_norm utility

Browse Source
This commit is contained in:
Gael Guennebaud 2014-09-11 10:27:46 +02:00
parent 5e890d3ad7
commit 57f71a5552
1 changed files with 22 additions and 11 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

33
bench/bench_norm.cpp
View File

@ -6,19 +6,25 @@ using namespace Eigen;
using namespace std;
template<typename T>
EIGEN_DONT_INLINE typename T::Scalar sqsumNorm(const T& v)
EIGEN_DONT_INLINE typename T::Scalar sqsumNorm(T& v)
{
return v.norm();
}
template<typename T>
EIGEN_DONT_INLINE typename T::Scalar hypotNorm(const T& v)
EIGEN_DONT_INLINE typename T::Scalar stableNorm(T& v)
{
return v.stableNorm();
}
template<typename T>
EIGEN_DONT_INLINE typename T::Scalar hypotNorm(T& v)
{
return v.hypotNorm();
}
template<typename T>
EIGEN_DONT_INLINE typename T::Scalar blueNorm(const T& v)
EIGEN_DONT_INLINE typename T::Scalar blueNorm(T& v)
{
return v.blueNorm();
}
@ -217,20 +223,21 @@ EIGEN_DONT_INLINE typename T::Scalar pblueNorm(const T& v)
}
#define BENCH_PERF(NRM) { \
float af = 0; double ad = 0; std::complex<float> ac = 0; \
Eigen::BenchTimer tf, td, tcf; tf.reset(); td.reset(); tcf.reset();\
for (int k=0; k<tries; ++k) { \
tf.start(); \
for (int i=0; i<iters; ++i) NRM(vf); \
for (int i=0; i<iters; ++i) { af += NRM(vf); } \
tf.stop(); \
} \
for (int k=0; k<tries; ++k) { \
td.start(); \
for (int i=0; i<iters; ++i) NRM(vd); \
for (int i=0; i<iters; ++i) { ad += NRM(vd); } \
td.stop(); \
} \
/*for (int k=0; k<std::max(1,tries/3); ++k) { \
tcf.start(); \
for (int i=0; i<iters; ++i) NRM(vcf); \
for (int i=0; i<iters; ++i) { ac += NRM(vcf); } \
tcf.stop(); \
} */\
std::cout << #NRM << "\t" << tf.value() << " " << td.value() << " " << tcf.value() << "\n"; \
@ -316,14 +323,17 @@ int main(int argc, char** argv)
std::cout << "\n";
}
y = 1;
std::cout.precision(4);
std::cerr << "Performance (out of cache):\n";
int s1 = 1024*1024*32;
std::cerr << "Performance (out of cache, " << s1 << "):\n";
{
int iters = 1;
VectorXf vf = VectorXf::Random(1024*1024*32) * y;
VectorXd vd = VectorXd::Random(1024*1024*32) * y;
VectorXcf vcf = VectorXcf::Random(1024*1024*32) * y;
VectorXf vf = VectorXf::Random(s1) * y;
VectorXd vd = VectorXd::Random(s1) * y;
VectorXcf vcf = VectorXcf::Random(s1) * y;
BENCH_PERF(sqsumNorm);
BENCH_PERF(stableNorm);
BENCH_PERF(blueNorm);
BENCH_PERF(pblueNorm);
BENCH_PERF(lapackNorm);
@ -332,13 +342,14 @@ int main(int argc, char** argv)
BENCH_PERF(bl2passNorm);
}
std::cerr << "\nPerformance (in cache):\n";
std::cerr << "\nPerformance (in cache, " << 512 << "):\n";
{
int iters = 100000;
VectorXf vf = VectorXf::Random(512) * y;
VectorXd vd = VectorXd::Random(512) * y;
VectorXcf vcf = VectorXcf::Random(512) * y;
BENCH_PERF(sqsumNorm);
BENCH_PERF(stableNorm);
BENCH_PERF(blueNorm);
BENCH_PERF(pblueNorm);
BENCH_PERF(lapackNorm);