pyFAI-benchmark

Measure the speed for azimuthal integration.

Purpose

Measures the avarage execution time for azimuthal integration with various image sizes and algorithms, can be used to select the most suitable integrator, to evaluate the perfomance of a given computer, debug some hardware problems.

Image are between 1 and 16 Mpixel in size and all the method tested are providing the same results for azimuthal integration (and validated). The bbox pixel splitting schem is used which is also the default one. By default, only the histogram and CSR algorithm (implemented in cython) are measued, but OpenCL devices can be probed with options “-c”, “-g” and “-a”.

The result is a graphic with the number of images integrated per second as function of the image size. All the corresponding timings are also recorded in a JSON file.

Since pyFAI version 0.20, whith the new generation of integrator put in production, both integrate1d_legacy and integrate1d_ng are benchmarked together to validate the absence of performance regression. A factor larger than 2 sould be considered as a bug.

Usage

-h, –help

show this help message and exit

-v, –version

show program’s version number and exit

-d, –debug

switch to verbose/debug mode

–no-proc

do not benchmark using the central processor

-c, –cpu

perform benchmark using OpenCL on the CPU

-g, –gpu

perform benchmark using OpenCL on the GPU

-a, –acc

perform benchmark using OpenCL on the Accelerator (like XeonPhi/MIC)

-s SIZE, –size SIZE

Limit the size of the dataset to X Mpixel images (for computer with limited memory)

-n NUMBER, –number NUMBER

Perform the test for this amount of time, by default 10s/measurment

-2d, –2dimention

Benchmark also algorithm for 2D-regrouping

–no-1dimention

Do not benchmark algorithms for 1D-regrouping

-m, –memprof

Perfrom memory profiling (Linux only)

-r REPEAT, –repeat REPEAT

Repeat each measurement x times to take the best

-ps PIXELSPLIT [PIXELSPLIT …], –pixelsplit PIXELSPLIT [PIXELSPLIT …]

Benchmark using specific pixel splitting protocols: no, bbox, pseudo, full, all

-algo ALGORITHM [ALGORITHM …], –algorithm ALGORITHM [ALGORITHM …]

Benchmark using specific algorithms: histogram, CSR, CSC, all

-i IMPLEMENTATION [IMPLEMENTATION …], –implementation IMPLEMENTATION [IMPLEMENTATION …]

Benchmark using specific algorithm implementations: python, cython, opencl, all

-f FUNCTION, –function FUNCTION

Benchmark legacy (legacy), engine function (ng), or both (all)

–all

Benchmark using all available methods and devices

Results

This tool produces a graphic that looks like: