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authorGravatar Gael Guennebaud <g.gael@free.fr>2009-07-16 11:33:56 +0200
committerGravatar Gael Guennebaud <g.gael@free.fr>2009-07-16 11:33:56 +0200
commit65fc70b75039a5cdfc5df67f62d38b317196293b (patch)
tree207707860af346f48e0bc728d6aca50c4ded4727 /bench/bench_norm.cpp
parent1578421ed14c23fa5c7ab3c818a069f1c1cefb8a (diff)
add a benchmark for the different norms
Diffstat (limited to 'bench/bench_norm.cpp')
-rw-r--r--bench/bench_norm.cpp259
1 files changed, 259 insertions, 0 deletions
diff --git a/bench/bench_norm.cpp b/bench/bench_norm.cpp
new file mode 100644
index 000000000..76c8c574d
--- /dev/null
+++ b/bench/bench_norm.cpp
@@ -0,0 +1,259 @@
+#include <Eigen/Core>
+#include "BenchTimer.h"
+using namespace Eigen;
+using namespace std;
+
+template<typename T>
+EIGEN_DONT_INLINE typename T::Scalar sqsumNorm(const T& v)
+{
+ return v.norm();
+}
+
+template<typename T>
+EIGEN_DONT_INLINE typename T::Scalar hypotNorm(const T& v)
+{
+ return v.stableNorm();
+}
+
+template<typename T>
+EIGEN_DONT_INLINE typename T::Scalar blueNorm(const T& v)
+{
+ return v.blueNorm();
+}
+
+template<typename T>
+EIGEN_DONT_INLINE typename T::Scalar lapackNorm(T& v)
+{
+ typedef typename T::Scalar Scalar;
+ int n = v.size();
+ Scalar scale = 1;
+ Scalar ssq = 0;
+ for (int i=0;i<n;++i)
+ {
+ Scalar ax = ei_abs(v.coeff(i));
+ if (scale < ax)
+ {
+ ssq = Scalar(1) + ssq * ei_abs2(scale/ax);
+ scale = ax;
+ }
+ else
+ ssq += ei_abs2(ax/scale);
+ }
+ return scale * ei_sqrt(ssq);
+}
+
+template<typename T>
+EIGEN_DONT_INLINE typename T::Scalar divacNorm(T& v)
+{
+ int n =v.size() / 2;
+ for (int i=0;i<n;++i)
+ v(i) = v(2*i)*v(2*i) + v(2*i+1)*v(2*i+1);
+ n = n/2;
+ while (n>0)
+ {
+ for (int i=0;i<n;++i)
+ v(i) = v(2*i) + v(2*i+1);
+ n = n/2;
+ }
+ return ei_sqrt(v(0));
+}
+
+Packet4f ei_plt(const Packet4f& a, Packet4f& b) { return _mm_cmplt_ps(a,b); }
+Packet2d ei_plt(const Packet2d& a, Packet2d& b) { return _mm_cmplt_pd(a,b); }
+
+Packet4f ei_pandnot(const Packet4f& a, Packet4f& b) { return _mm_andnot_ps(a,b); }
+Packet2d ei_pandnot(const Packet2d& a, Packet2d& b) { return _mm_andnot_pd(a,b); }
+
+template<typename T>
+EIGEN_DONT_INLINE typename T::Scalar pblueNorm(const T& v)
+{
+ typedef typename T::Scalar Scalar;
+
+ static int nmax;
+ static Scalar b1, b2, s1m, s2m, overfl, rbig, relerr;
+ int n;
+
+ if(nmax <= 0)
+ {
+ int nbig, ibeta, it, iemin, iemax, iexp;
+ Scalar abig, eps;
+
+ nbig = std::numeric_limits<int>::max(); // largest integer
+ ibeta = NumTraits<Scalar>::Base; // base for floating-point numbers
+ it = NumTraits<Scalar>::Mantissa; // number of base-beta digits in mantissa
+ iemin = std::numeric_limits<Scalar>::min_exponent; // minimum exponent
+ iemax = std::numeric_limits<Scalar>::max_exponent; // maximum exponent
+ rbig = std::numeric_limits<Scalar>::max(); // largest floating-point number
+
+ // Check the basic machine-dependent constants.
+ if(iemin > 1 - 2*it || 1+it>iemax || (it==2 && ibeta<5)
+ || (it<=4 && ibeta <= 3 ) || it<2)
+ {
+ ei_assert(false && "the algorithm cannot be guaranteed on this computer");
+ }
+ iexp = -((1-iemin)/2);
+ b1 = bexp<Scalar>(ibeta, iexp); // lower boundary of midrange
+ iexp = (iemax + 1 - it)/2;
+ b2 = bexp<Scalar>(ibeta,iexp); // upper boundary of midrange
+
+ iexp = (2-iemin)/2;
+ s1m = bexp<Scalar>(ibeta,iexp); // scaling factor for lower range
+ iexp = - ((iemax+it)/2);
+ s2m = bexp<Scalar>(ibeta,iexp); // scaling factor for upper range
+
+ overfl = rbig*s2m; // overfow boundary for abig
+ eps = bexp<Scalar>(ibeta, 1-it);
+ relerr = ei_sqrt(eps); // tolerance for neglecting asml
+ abig = 1.0/eps - 1.0;
+ if (Scalar(nbig)>abig) nmax = abig; // largest safe n
+ else nmax = nbig;
+ }
+
+ typedef typename ei_packet_traits<Scalar>::type Packet;
+ const int ps = ei_packet_traits<Scalar>::size;
+ Packet pasml = ei_pset1(Scalar(0));
+ Packet pamed = ei_pset1(Scalar(0));
+ Packet pabig = ei_pset1(Scalar(0));
+ Packet ps2m = ei_pset1(s2m);
+ Packet ps1m = ei_pset1(s1m);
+ Packet pb2 = ei_pset1(b2);
+ Packet pb1 = ei_pset1(b1);
+ for(int j=0; j<v.size(); j+=ps)
+ {
+ Packet ax = ei_pabs(v.template packet<Aligned>(j));
+ Packet ax_s2m = ei_pmul(ax,ps2m);
+ Packet ax_s1m = ei_pmul(ax,ps1m);
+ Packet maskBig = ei_plt(pb2,ax);
+ Packet maskSml = ei_plt(ax,pb1);
+ pabig = ei_padd(pabig, ei_pand(maskBig, ei_pmul(ax_s2m,ax_s2m)));
+ pasml = ei_padd(pasml, ei_pand(maskSml, ei_pmul(ax_s1m,ax_s1m)));
+ pamed = ei_padd(pamed, ei_pandnot(ei_pmul(ax,ax),ei_pand(maskSml,maskBig)));
+ }
+ Scalar abig = ei_predux(pabig);
+ Scalar asml = ei_predux(pasml);
+ Scalar amed = ei_predux(pamed);
+ if(abig > Scalar(0))
+ {
+ abig = ei_sqrt(abig);
+ if(abig > overfl)
+ {
+ ei_assert(false && "overflow");
+ return rbig;
+ }
+ if(amed > Scalar(0))
+ {
+ abig = abig/s2m;
+ amed = ei_sqrt(amed);
+ }
+ else
+ {
+ return abig/s2m;
+ }
+
+ }
+ else if(asml > Scalar(0))
+ {
+ if (amed > Scalar(0))
+ {
+ abig = ei_sqrt(amed);
+ amed = ei_sqrt(asml) / s1m;
+ }
+ else
+ {
+ return ei_sqrt(asml)/s1m;
+ }
+ }
+ else
+ {
+ return ei_sqrt(amed);
+ }
+ asml = std::min(abig, amed);
+ abig = std::max(abig, amed);
+ if(asml <= abig*relerr)
+ return abig;
+ else
+ return abig * ei_sqrt(Scalar(1) + ei_abs2(asml/abig));
+}
+
+#define BENCH_PERF(NRM) { \
+ Eigen::BenchTimer tf, td; tf.reset(); td.reset();\
+ for (int k=0; k<tries; ++k) { \
+ tf.start(); \
+ for (int i=0; i<iters; ++i) NRM(vf); \
+ tf.stop(); \
+ } \
+ for (int k=0; k<tries; ++k) { \
+ td.start(); \
+ for (int i=0; i<iters; ++i) NRM(vd); \
+ td.stop(); \
+ } \
+ std::cout << #NRM << "\t" << tf.value() << " " << td.value() << "\n"; \
+}
+
+void check_accuracy(double basef, double based, int s)
+{
+ double yf = basef * ei_abs(ei_random<double>());
+ double yd = based * ei_abs(ei_random<double>());
+ VectorXf vf = VectorXf::Ones(s) * yf;
+ VectorXd vd = VectorXd::Ones(s) * yd;
+
+ std::cout << "reference\t" << ei_sqrt(double(s))*yf << "\t" << ei_sqrt(double(s))*yd << "\n";
+ std::cout << "sqsumNorm\t" << sqsumNorm(vf) << "\t" << sqsumNorm(vd) << "\n";
+ std::cout << "hypotNorm\t" << hypotNorm(vf) << "\t" << hypotNorm(vd) << "\n";
+ std::cout << "blueNorm\t" << blueNorm(vf) << "\t" << blueNorm(vd) << "\n";
+ std::cout << "pblueNorm\t" << pblueNorm(vf) << "\t" << pblueNorm(vd) << "\n";
+ std::cout << "lapackNorm\t" << lapackNorm(vf) << "\t" << lapackNorm(vd) << "\n";
+}
+
+int main(int argc, char** argv)
+{
+ int tries = 5;
+ int iters = 100000;
+ double y = 1.1345743233455785456788e12 * ei_random<double>();
+ VectorXf v = VectorXf::Ones(1024) * y;
+
+// std::cerr << "Performance (out of cache):\n";
+// {
+// int iters = 1;
+// VectorXf vf = VectorXf::Ones(1024*1024*32) * y;
+// VectorXd vd = VectorXd::Ones(1024*1024*32) * y;
+// BENCH_PERF(sqsumNorm);
+// BENCH_PERF(blueNorm);
+// BENCH_PERF(pblueNorm);
+// BENCH_PERF(lapackNorm);
+// BENCH_PERF(hypotNorm);
+// }
+//
+// std::cerr << "\nPerformance (in cache):\n";
+// {
+// int iters = 100000;
+// VectorXf vf = VectorXf::Ones(512) * y;
+// VectorXd vd = VectorXd::Ones(512) * y;
+// BENCH_PERF(sqsumNorm);
+// BENCH_PERF(blueNorm);
+// BENCH_PERF(pblueNorm);
+// BENCH_PERF(lapackNorm);
+// BENCH_PERF(hypotNorm);
+// }
+
+ int s = 10000;
+ double basef_ok = 1.1345743233455785456788e12;
+ double based_ok = 1.1345743233455785456788e32;
+
+ double basef_under = 1.1345743233455785456788e-23;
+ double based_under = 1.1345743233455785456788e-180;
+
+ double basef_over = 1.1345743233455785456788e+27;
+ double based_over = 1.1345743233455785456788e+185;
+
+ std::cout.precision(20);
+
+ std::cerr << "\nNo under/overflow:\n";
+ check_accuracy(basef_ok, based_ok, s);
+
+ std::cerr << "\nUnderflow:\n";
+ check_accuracy(basef_under, based_under, 1);
+
+ std::cerr << "\nOverflow:\n";
+ check_accuracy(basef_over, based_over, s);
+}