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Piglit

  1. About
  2. Setup
  3. How to run tests
  4. Available test sets
  5. How to write tests
  6. Integration

1. About

Piglit is a collection of automated tests for OpenGL and OpenCL implementations.

The goal of Piglit is to help improve the quality of open source OpenGL and OpenCL drivers by providing developers with a simple means to perform regression tests.

The original tests have been taken from

2. Setup

First of all, you need to make sure that the following are installed:

Optionally, you can install the following:

For testing the python framework using py.test unittests/framework

Now configure the build system:

$ ccmake .

This will start cmake's configuration tool, just follow the onscreen instructions. The default settings should be fine, but I recommend you:

2.1 Cross Compiling

On Linux, if cross-compiling a 32-bit build on a 64-bit host, first make sure you didn't have CMakeCache.txt file left from 64-bit build (it would retain old flags), then you must invoke cmake with options -DCMAKE_SYSTEM_PROCESSOR=x86 -DCMAKE_C_FLAGS=-m32 -DCMAKE_CXX_FLAGS=-m32.

2.2 Ubuntu

Install development packages.

$ sudo apt-get install cmake g++ mesa-common-dev libgl1-mesa-dev python-numpy python-mako freeglut3-dev x11proto-gl-dev libxrender-dev libwaffle-dev

Configure and build.

$ cmake .
$ make

2.3 Mac OS X

Install CMake. http://cmake.org/cmake/resources/software.html Download and install 'Mac OSX Universal' platform.

Install Xcode. http://developer.apple.com/xcode

Configure and build.

$ cmake .
$ make

2.4 Cygwin

Install development packages.

Configure and build.

$ cmake .
$ make

2.5 Windows

Install Python 3. http://www.python.org/download

Install CMake. http://cmake.org/cmake/resources/software.html Download and install 'Windows' platform.

Download and install Ninja https://github.com/ninja-build/ninja/releases

Install MinGW-w64 https://mingw-w64.org/

Download OpenGL Core API and Extension Header Files. http://www.opengl.org/registry/#headers Pass -DGLEXT_INCLUDE_DIR=/path/to/headers

Install python mako.

pip install mako

Install NumPy.

pip install numpy

2.5.1 GLUT

Download freeglut for Mingw. http://www.transmissionzero.co.uk/software/freeglut-devel/

cmake -H. -Bbuild -G "Ninja" -DGLEXT_INCLUDE_DIR=\path\to\glext -DGLUT_INCLUDE_DIR=\path\to\freeglut\include -DGLUT_glut_LIBRARY=\path\to\freeglut\lib\x64\libfreeglut.a -DGLEXT_INCLUDE_DIR=\path\to\glext
ninja -C build

2.5.2 Waffle

Download and build waffle for MinGW. http://www.waffle-gl.org/

Open the Command Prompt. CD to piglit directory.

cmake -H. -Bbuild -G "Ninja" -DGLEXT_INCLUDE_DIR=\path\to\glext -DPIGLIT_USE_WAFFLE=TRUE -DWAFFLE_INCLUDE_DIRS=\path\to\waffle\include\waffle WAFFLE_LDFLAGS=\path\to\waffle\lib\libwaffle-1.a

3. How to run tests

Make sure that everything is set up correctly:

$ ./piglit run sanity results/sanity

You may include '.py' on the profile, or you may exclude it (sanity vs sanity.py), both are equally valid.

You may also preface test profiles with tests/ (or any other path you like), which may be useful for shell tab completion.

You may provide multiple profiles to be run at the same time:

$ ./piglit run quick_cl gpu deqp_gles3 results/gl-cl-combined

Use

$ ./piglit run

or

$ ./piglit run -h

To learn more about the command's syntax.

Have a look into the tests/ directory to see what test profiles are available:

$ ls tests/*.py

See also section 4.

To create some nice formatted test summaries, run

$ ./piglit summary html summary/sanity results/sanity

Hint: You can combine multiple test results into a single summary. During development, you can use this to watch for regressions:

$ ./piglit summary html summary/compare results/baseline results/current

You can combine as many testruns as you want this way (in theory; the HTML layout becomes awkward when the number of testruns increases)

Have a look at the results with a browser:

$ xdg-open summary/sanity/index.html

The summary shows the 'status' of a test:

There are also dmesg-* statuses. These have the same meaning as above, but are triggered by dmesg related messages.

3.1 Environment Variables

There are a number of environment variables that control the way piglit behaves.

3.2 Note

The way piglit run and piglit summary count tests are different, piglit run counts the number of Test derived instance in the profile(s) selected, while piglit summary counts the number of subtests a result contains, or it's result if there are no subtests. This means that the number shown by piglit run will be less than or equal to the number calculated by piglit summary.

3.3 Shell Completions

Piglit has completions for bash, located in completions/bash/piglit. Once this file is sourced into bash piglit and ./piglit will have tab completion available. For global availability place the file somewhere that bash will source the file on startup. If piglit is installed and bash-completions are available, then this completion file will be installed system-wide.

4. Available test sets

Test sets are specified as Python scripts in the tests directory. The following test sets are currently available:

4.1 OpenGL Tests

4.2 OpenCL Tests

4.3 Vulkan tests

4.4 Replay tests

4.5 External Integration

5. How to write tests

Every test is run as a separate process. This minimizes the impact that severe bugs like memory corruption have on the testing process.

Therefore, tests can be implemented in an arbitrary standalone language. C is the preferred language for compiled tests, piglit also supports its own simple formats for test shaders and glsl parser input.

All new tests must be added to the appropriate profile, all.py profile for OpenGL and cl.py for OpenCL. There are a few basic test classes supported by the python framework:

6. Integration

Piglit provides integration for other test suites as well. The rational for this is that it provides piglit's one process per test protections (one test crashing does not crash the whole suite), and access to piglit's reporting tools.

Most integration is done through the use of piglit.conf, or through environment variables, with piglit.conf being the preferred method.

6.1 dEQP

Piglit provides a generic layer for dEQP based test suites, and specific integration for several suites.

I suggest using Chad Versace's repo of dEQP, which contains a gbm target. https://github.com/chadversary/deqp

It should be built as follows:

cmake . -DDEQP_TARGET=gbm -GNinja

Additional targets are available in the targets directory. gbm isn't compatible for most (any?) blob driver, so another target might be necessary if that is a requirement. One of the x11_* targets or drm is probably a good choice.

The use of ninja is optional.

Once dEQP is built add the following information to piglit.conf, which can either be located in the root of the piglit repo, or in $XDG_CONFIG_HOME (usually $HOME/.config).

[deqp-gles2]
bin=<deqp source dir>/modules/gles2/deqp-gles2

[deqp-gles3]
bin=<deqp source dir>/modules/gles3/deqp-gles3

[deqp-gles31]
bin=<deqp source dir>/modules/gles31/deqp-gles31

These platforms can be run using deqp_gles*.py as a suite in piglit. For example:

./piglit run deqp_gles31 my_results -c

It is also possible to mix integrated suites and piglit profiles together:

./piglit run deqp_gles31 quick cl my_results

dEQP profiles generally contain all of the tests from the previous profile, so gles31 covers gles3 and gles2.

6.2 Khronos CTS

Add the following to your piglit.conf file:

[cts]
bin=<cts source dir>/cts/glcts