comparison_norm_frob

Benchmark Report

Frobenius norm with 100 elements and size = 1,000

name | rank | runs |      mean |     stdev | baseline

---------|------|------|-----------|-----------|--------- cysparse | 1 | 100 | 1.915e-06 | 5.573e-07 | 1 pysparse | 2 | 100 | 2.244e-06 | 7.81e-07 | 1.172

Frobenius norm with 1,000 elements and size = 10,000

name | rank | runs |      mean |     stdev | baseline

---------|------|------|-----------|-----------|--------- cysparse | 1 | 100 | 1.251e-05 | 1.452e-06 | 1 pysparse | 2 | 100 | 1.279e-05 | 5.053e-07 | 1.023

Frobenius norm with 10,000 elements and size = 100,000

name | rank | runs |      mean |     stdev | baseline

---------|------|------|-----------|-----------|--------- cysparse | 1 | 100 | 0.0001089 | 1.872e-05 | 1 pysparse | 2 | 100 | 0.0001142 | 1.514e-05 | 1.049

Frobenius norm with 80,000 elements and size = 100,000

name | rank | runs |      mean |     stdev | baseline

---------|------|------|-----------|-----------|--------- cysparse | 1 | 100 | 0.0001211 | 6.031e-06 | 1 pysparse | 2 | 100 | 0.000122 | 8.838e-06 | 1.008

Total runs: 800 run in arbitrary order Python version: 2.7.5+ System: x86_64 Linux 3.11.0-12-generic Version: benchmark v0.1.5 Date: 2015-05-28 21:13:37