1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
|
:Author: Jérôme Kieffer
:Date: 22/01/2021
:Keywords: Performance analysis
:Target: user
.. _pyfaibenchmark:
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
-----
pyFAI-bencmark [options]
optional arguments:
-h, --help show the 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
Number of repetition of the test (or time used for each test), by default 10 (sec)
-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
Result
------
The typical result looks like this:
.. figure:: ../img/benchmark.svg
:align: center
:alt: benchmark performed on a 2016 single-socket workstation and a gaming graphics card.
For the detailed explaination on how to read this plot, please refer to :ref:`performances`.
|
