Numpy Benchmarks

A collection of scientific kernels that use the numpy package, for benchmarking purpose.

Each kernel holds a #setup: ... code ... and a #run: ... code ... comment line to be passed to the timeit module for easy benchmarking, as automated by the run.py script. To run a specific set of benchmarks on a specific set of compilers, use the ad hoc arguments , as in:

python run.py -t python -t pythran benchmarks/harris.py benchmarks/evolve.py

A small utility, provided with the benchmark, fmt-bench can be used to pretty-print the result in various format (see fmt-bench --help:

python run.py | ./fmt-bench

Example

$ python run.py -t python benchmarks/harris.py harris Python 5431 5454 14

What does it mean? The code from benchmarks/harris.py was run through timeit using the #setup and #run code. It outputs (in that order and in nanoseconds):

1. the best execution time among all runs;
2. the average execution time of the runs;
3. the standard deviation of the runs.