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
- -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
Runtime for each test, in seconds, by default 10
- -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 benchmark x times to take the best, by default only run once
Results
This tool produces a graphic that looks like:
