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.flake8

+4 −4
Original line number Original line Diff line number Diff line 
[flake8]

[flake8]

max-line-length=120

max-line-length=120

exclude=pystencils/jupyter.py,

exclude=src/pystencils/jupyter.py,

        pystencils/plot.py

        src/pystencils/plot.py

        pystencils/session.py

        src/pystencils/session.py

ignore = W293 W503 W291 C901
 
ignore = W293 W503 W291 C901 E741

.gitattributes

0 → 100644
+1 −0
Original line number Original line Diff line number Diff line 
src/pystencils/_version.py export-subst

.gitignore

+17 −2
Original line number Original line Diff line number Diff line 
__pycache__

__pycache__

.ipynb_checkpoints

.ipynb_checkpoints

.coverage

.coverage*

*.pyc

*.pyc

*.vti

*.vti

/build

/build

/dist

/dist

/*.egg-info

*.egg-info

.cache

.cache

_build

_build

/html_doc

/.idea

/.idea

.vscode

.cache

.cache

_local_tmp

_local_tmp

RELEASE-VERSION

RELEASE-VERSION

test-report

test-report

src/pystencils/boundaries/createindexlistcython.c

src/pystencils/boundaries/createindexlistcython.*.so

tests/tmp

tests/var

tests/kerncraft_inputs/.2d-5pt.c_kerncraft/

tests/kerncraft_inputs/.3d-7pt.c_kerncraft/

report.xml

coverage_report/





# macOS

**/.DS_Store

*.uuid

.gitlab-ci.yml

+241 −63
Original line number Original line Diff line number Diff line 
stages:

stages:

  - pretest

  - test

  - test

  - nightly

  - docs

  - deploy

  - deploy









# --------------------------  Templates ------------------------------------------------------------------------------------



# Base configuration for jobs meant to run at every commit

.every-commit:

  rules:

    - if: $CI_PIPELINE_SOURCE != "schedule"



# Configuration for jobs meant to run on each commit to pycodegen/pystencils/master

.every-commit-master:

  rules:

    - if: '$CI_PIPELINE_SOURCE != "schedule" && $CI_PROJECT_PATH == "pycodegen/pystencils" && $CI_COMMIT_BRANCH == "master"'



# Base configuration for jobs meant to run at a schedule

.scheduled:

  rules:

    - if: $CI_PIPELINE_SOURCE == "schedule"



# --------------------------  Tests ------------------------------------------------------------------------------------

# --------------------------  Tests ------------------------------------------------------------------------------------





# Normal test - runs on every commit all but "long run" tests

# Normal test - runs on every commit all but "long run" tests

tests-and-coverage:

tests-and-coverage:

  stage: test

  stage: pretest

  except:

  extends: .every-commit

    variables:

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/full:cupy12.3

      - $ENABLE_NIGHTLY_BUILDS

  before_script:

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/full

    - pip install -e .

  script:

  script:

    - env

    - pip list

    - export NUM_CORES=$(nproc --all)

    - export NUM_CORES=$(nproc --all)

    - mkdir -p ~/.config/matplotlib

    - mkdir -p ~/.config/matplotlib

    - echo "backend:template" > ~/.config/matplotlib/matplotlibrc

    - echo "backend:template" > ~/.config/matplotlib/matplotlibrc

    - mkdir public

    - mkdir public

    - py.test -v -n $NUM_CORES --cov-report html --cov-report term --cov=. -m "not longrun" --html test-report/index.html

    - pytest -v -n $NUM_CORES --cov-report html --cov-report xml --cov-report term --cov=. -m "not longrun" --html test-report/index.html --junitxml=report.xml

    - python -m coverage xml

  tags:

  tags:

    - docker

    - docker

    - cuda

    - cuda11

    - AVX

    - AVX

  coverage: /Total coverage:\s\d+.\d+\%/

  artifacts:

  artifacts:

    when: always

    when: always

    paths:

    paths:

      - coverage_report

      - coverage_report

      - test-report

      - test-report

    reports:

      coverage_report:

        coverage_format: cobertura

        path: coverage.xml

      junit: report.xml





# Nightly test  - runs "long run" jobs only

# Normal test with longruns

test-longrun:

tests-and-coverage-with-longrun:

  stage: test

  stage: test

  only:

  when: manual

    variables:

  allow_failure: true

      - $ENABLE_NIGHTLY_BUILDS

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/full:cupy12.3

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/full

  before_script:

    - pip install sympy --upgrade

    - pip install -e .

  script:

  script:

    - env

    - pip list

    - export NUM_CORES=$(nproc --all)

    - export NUM_CORES=$(nproc --all)

    - mkdir -p ~/.config/matplotlib

    - mkdir -p ~/.config/matplotlib

    - echo "backend:template" > ~/.config/matplotlib/matplotlibrc

    - echo "backend:template" > ~/.config/matplotlib/matplotlibrc

    - py.test -v -n $NUM_CORES --cov-report html --cov-report term --cov=. --html test-report/index.html

    - mkdir public

    - py.test -v -n $NUM_CORES

  tags:

    - docker

    - cuda11

    - AVX



# pipeline with latest python version

latest-python:

  stage: test

  extends: .every-commit

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/latest_python

  before_script:

    - pip install -e .

  script:

    - env

    - pip list

    - pip install -e .

    - export NUM_CORES=$(nproc --all)

    - mkdir -p ~/.config/matplotlib

    - echo "backend:template" > ~/.config/matplotlib/matplotlibrc

    - mkdir public

    - py.test -v -n $NUM_CORES -m "not longrun" --junitxml=report.xml

  tags:

  tags:

    - docker

    - docker

    - cuda

    - AVX

    - AVX

  artifacts:

  artifacts:

    paths:

    when: always

      - coverage_report

    reports:

      - test-report

      junit: report.xml







# Minimal tests in windows environment

# Minimal tests in windows environment

minimal-windows:

#minimal-windows:

#  stage: test

#  tags:

#    - win

#  script:

#    - export NUM_CORES=$(nproc --all)

#    - source /cygdrive/c/Users/build/Miniconda3/Scripts/activate

#    - source activate pystencils

#    - pip install joblib

#    - pip list

#    - python -c "import numpy"

#    - py.test -v -m "not (notebook or longrun)"



ubuntu:

  stage: test

  stage: test

  except:

  extends: .every-commit

    variables:

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/ubuntu

      - $ENABLE_NIGHTLY_BUILDS

  before_script:

  tags:

    - ln -s /usr/include/locale.h /usr/include/xlocale.h

    - win

    - pip3 install -e .

  script:

  script:

    - source /cygdrive/c/Users/build/Miniconda3/Scripts/activate

    - export NUM_CORES=$(nproc --all)

    - source activate pystencils_dev

    - mkdir -p ~/.config/matplotlib

    - echo "backend:template" > ~/.config/matplotlib/matplotlibrc

    - sed -i 's/--doctest-modules //g' pytest.ini

    - env

    - env

    - conda env list

    - pip list

    - python -c "import numpy"

    - pytest -v -n $NUM_CORES -m "not longrun" --junitxml=report.xml

    - python setup.py quicktest

  tags:

    - docker

    - cuda11

    - AVX

  artifacts:

    when: always

    reports:

      junit: report.xml





minimal-ubuntu:

.multiarch_template:

  stage: test

  stage: test

  except:

  extends: .every-commit

    variables:

  allow_failure: true

      - $ENABLE_NIGHTLY_BUILDS

  before_script: &multiarch_before_script

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/minimal_ubuntu

    # - pip3 install -v .

    - export PYTHONPATH=src

    - python3 -c "import pystencils as ps; ps.cpu.cpujit.read_config()"

    - sed -i '/^fail_under.*/d' pytest.ini

  script:

  script:

    - python3 setup.py quicktest

    - export NUM_CORES=$(nproc --all)

    - mkdir -p ~/.config/matplotlib

    - echo "backend:template" > ~/.config/matplotlib/matplotlibrc

    - sed -i 's/--doctest-modules //g' pytest.ini

    - env

    - pip3 list

    - python3 -m pytest -v -n $NUM_CORES --reruns 2 --cov-report html --cov-report xml --cov=. --junitxml=report.xml tests/test_*vec*.py tests/test_random.py tests/test_half_precision.py

    - python3 -m coverage xml

  tags:

  tags:

    - docker

    - docker

    - multiarch

  artifacts:

    when: always

    paths:

      - coverage_report

    reports:

      coverage_report:

        coverage_format: cobertura

        path: coverage.xml

      junit: report.xml





minimal-conda:

arm64v8:

  stage: test

  extends: .multiarch_template

  except:

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/arm64

  variables:

    QEMU_CPU: "cortex-a76"

  before_script:

    - *multiarch_before_script



ppc64le:

  extends: .multiarch_template

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/ppc64le

  before_script:

    - *multiarch_before_script



arm64v9:

  # SVE support is still unreliable in GCC 13 (incorrect code for fixed-width vectors, internal compiler errors).

  # For half precision Clang is necessary

  extends: .multiarch_template

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/arm64

  variables:

  variables:

      - $ENABLE_NIGHTLY_BUILDS

    # disable pointer authentication to speed up emulation by 3x

    QEMU_CPU: "max,pauth-impdef=on"

  before_script:

    - *multiarch_before_script

    - sed -i s/g\+\+/clang++/g ~/.config/pystencils/config.json



riscv64:

  # RISC-V vector extension support is incomplete in GCC 13.

  extends: .multiarch_template

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/riscv64

  variables:

    # explicitly set SIMD as detection requires QEMU >= 8.1

    PYSTENCILS_SIMD: "rvv"

    QEMU_CPU: "rv64,v=true,zicboz=true"

  before_script:

    - *multiarch_before_script

    - sed -i 's/march=native/march=rv64imfdvzicboz/g' ~/.config/pystencils/config.json

    - sed -i s/g\+\+/clang++/g ~/.config/pystencils/config.json



minimal-conda:

  stage: pretest

  extends: .every-commit

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/minimal_conda

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/minimal_conda

  before_script:

    - pip install -e .

  script:

  script:

    - python setup.py quicktest

    - python quicktest.py

  tags:

  tags:

    - docker

    - docker

    - cuda









minimal-sympy-master:

minimal-sympy-master:

  stage: test

  stage: test

  except:

  extends: .every-commit

    variables:

      - $ENABLE_NIGHTLY_BUILDS

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/minimal_conda

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/minimal_conda

  before_script:

    - pip install -e .

  script:

  script:

    - python -m pip install --upgrade git+https://github.com/sympy/sympy.git

    - python -m pip install --upgrade git+https://github.com/sympy/sympy.git

    - python setup.py quicktest

    - python quicktest.py

  allow_failure: true

  allow_failure: true

  tags:

  tags:

    - docker

    - docker

    - cuda









pycodegen-integration:

pycodegen-integration:

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/full

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/full

  stage: test

  stage: test

  when: manual

  when: manual

  allow_failure: true

  script:

  script:

    - git clone https://gitlab-ci-token:${CI_JOB_TOKEN}@i10git.cs.fau.de/pycodegen/pycodegen.git

    - git clone https://gitlab-ci-token:${CI_JOB_TOKEN}@i10git.cs.fau.de/pycodegen/pycodegen.git

    - cd pycodegen

    - cd pycodegen
@@ -118,50 +257,89 @@ pycodegen-integration: 
    - git fetch test

    - git fetch test

    - git reset --hard $CI_COMMIT_SHA

    - git reset --hard $CI_COMMIT_SHA

    - cd ..

    - cd ..

    - export PYTHONPATH=`pwd`/pystencils:`pwd`/lbmpy:`pwd`/pygrandchem:`pwd`/pystencils_walberla:`pwd`/lbmpy_walberla

    - pip install -e pystencils/

    - pip install -e lbmpy/

    - cmake --version

    - ./install_walberla.sh

    - ./install_walberla.sh

    - export NUM_CORES=$(nproc --all)

    - export NUM_CORES=$(nproc --all)

    - mkdir -p ~/.config/matplotlib

    - mkdir -p ~/.config/matplotlib

    - echo "backend:template" > ~/.config/matplotlib/matplotlibrc

    - echo "backend:template" > ~/.config/matplotlib/matplotlibrc

    - cd pystencils

    - cd pystencils

    - py.test -v -n $NUM_CORES .

    - py.test -v -n $NUM_CORES --junitxml=report.xml .

    - cd ../lbmpy

    - cd ../lbmpy

    - py.test -v -n $NUM_CORES .

    - py.test -v -n $NUM_CORES --junitxml=report.xml .

    - cd ../pygrandchem

    - py.test -v -n $NUM_CORES .

    - cd ../walberla/build/

    - cd ../walberla/build/

    - make CodegenJacobiCPU CodegenJacobiGPU MicroBenchmarkGpuLbm LbCodeGenerationExample

    - make -j $NUM_CORES CodegenJacobiCPU CodegenJacobiGPU CodegenPoissonCPU CodegenPoissonGPU MicroBenchmarkGpuLbm LbCodeGenerationExample

    - make -j $NUM_CORES multiphaseCPU multiphaseGPU FluctuatingMRT FlowAroundSphereCodeGen FieldLayoutAndVectorizationTest GeneratedOutflowBC

    - cd apps/benchmarks/UniformGridGPU

    - make -j $NUM_CORES

    - cd ../UniformGridCPU

    - make -j $NUM_CORES

  tags:

  tags:

    - docker

    - docker

    - cuda

    - cuda11

    - AVX

    - AVX

  artifacts:

    when: always

    reports:

      junit: pycodegen/*/report.xml





# -------------------- Scheduled Tasks --------------------------------------------------------------------------





# Nightly test against the latest (pre-release) version of SymPy published on PyPI

nightly-sympy:

  stage: nightly

  needs: []

  extends: .scheduled

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/latest_python

  before_script:

    - pip install -e .

    - pip install --upgrade --pre sympy

  script:

    - env

    - pip list

    - export NUM_CORES=$(nproc --all)

    - mkdir -p ~/.config/matplotlib

    - echo "backend:template" > ~/.config/matplotlib/matplotlibrc

    - mkdir public

    - pytest -v -n $NUM_CORES -m "not longrun" --junitxml=report.xml

  tags:

    - docker

    - AVX

    - cuda

  artifacts:

    when: always

    reports:

      junit: report.xml





# -------------------- Linter & Documentation --------------------------------------------------------------------------

# -------------------- Linter & Documentation --------------------------------------------------------------------------









flake8-lint:

flake8-lint:

  stage: test

  stage: pretest

  except:

  extends: .every-commit

    variables:

      - $ENABLE_NIGHTLY_BUILDS

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/full

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/full

  script:

  script:

    - flake8 pystencils

    - flake8 src/pystencils

  tags:

  tags:

    - docker

    - docker

    - cuda









build-documentation:

build-documentation:

  stage: test

  stage: docs

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/full

  extends: .every-commit

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/documentation

  needs: []

  before_script:

    - pip install -e .

  script:

  script:

    - export PYTHONPATH=`pwd`

    - mkdir html_doc

    - mkdir html_doc

    - sphinx-build -b html doc  html_doc

    - sphinx-build -W -b html doc  html_doc

    - sphinx-build -W -b html doc  html_doc

  tags:

  tags:

    - docker

    - docker

    - cuda

  artifacts:

  artifacts:

    paths:

    paths:

      - html_doc

      - html_doc
@@ -169,7 +347,9 @@ build-documentation: 




pages:

pages:

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/full

  image: i10git.cs.fau.de:5005/pycodegen/pycodegen/full

  extends: .every-commit-master

  stage: deploy

  stage: deploy

  needs: ["tests-and-coverage", "build-documentation"]

  script:

  script:

    - ls -l

    - ls -l

    - mv coverage_report html_doc

    - mv coverage_report html_doc
@@ -179,5 +359,3 @@ pages: 
      - public

      - public

  tags:

  tags:

    - docker
 
    - docker
 
  only:

    - master@pycodegen/pystencils

AUTHORS.txt

+6 −5
Original line number Original line Diff line number Diff line
@@ -3,12 +3,13 @@ Contributors: 
-------------

-------------





  - Martin Bauer <martin.bauer@fau.de>

  - Martin Bauer <martin.bauer@fau.de>

  - Markus Holzer <markus.holzer@fau.de>

  - Stephan Seitz <stephan.seitz@fau.de>

  - Stephan Seitz <stephan.seitz@fau.de>

  - Michael Kuron <mkuron@icp.uni-stuttgart.de>

  - Jan Hönig <jan.hoenig@fau.de>

  - Jan Hönig <jan.hoenig@fau.de>

  - Nils Kohl <nils.kohl@fau.de>

  - Julian Hammer <julian.hammer@fau.de>

  - Julian Hammer <julian.hammer@fau.de>

  - Christian Godenschwager <christian.godenschwager@fau.de>

  - Nils Kohl <nils.kohl@fau.de>

  - Markus Holzer <markus.holzer@fau.de>

  - Frederik Hennig <frederik.hennig@fau.de>

  - Michael Kuron <mkuron@icp.uni-stuttgart.de>

  - Dominik Ernst <dominik.ernst@fau.de>

  - Dominik Ernst <dominik.ernst@fau.de>

  - João Victor Tozatti Risso <joaovictortr@protonmail.com>
 
  - Christian Godenschwager <christian.godenschwager@fau.de>

  - Dominik Thoennes <dominik.thoennes@fau.de>

CHANGELOG.md

0 → 100644
+7 −0
Original line number Original line Diff line number Diff line 
# Change Log



## Unreleased



### Removed

* LLVM backend because it was not used much and not good integrated in pystencils.

* OpenCL backend because it was not used much and not good integrated in pystencils.

CONTRIBUTING.md

0 → 100644
+87 −0
Original line number Original line Diff line number Diff line 
# Contributing



Contributions to pystencils are always welcome, and they are greatly appreciated!

A list of open problems can be found [here]( https://i10git.cs.fau.de/pycodegen/pystencils/-/issues).

Of course, it is also always appreciated to bring own ideas and problems to the community!





Please submit all contributions to the official [GitLab repository](https://i10git.cs.fau.de/pycodegen/pystencils) in the form of a Merge Request. Please do not submit git diffs or files containing the changes.

There also exists a GitHub repository, which is only a mirror to the GitLab repository. Contributions to the GitHub repository are not considered.



`pystencils` is an open-source python package under the license of  AGPL3. Thus we consider the act of contributing to the code by submitting a Merge Request as the "Sign off" or agreement to the AGPL3 license.



You can contribute in many different ways:



## Types of Contributions



### Report Bugs



Report bugs at [https://i10git.cs.fau.de/pycodegen/pystencils/-/issues](https://i10git.cs.fau.de/pycodegen/pystencils/-/issues).



For pystencils, it is often necessary to provide the python and [SymPy](https://www.sympy.org/en/index.html) versions used and hardware information like the

processor architecture and the compiler version used to compile the generated kernels.



### Fix Issues



Look through the GitLab issues. Different tags are indicating the status of the issues.

The "bug" tag indicates problems with pystencils, while the "feature" tag shows ideas that should be added in the future.



### Write Documentation



The documentation of pystencils can be found [here](https://pycodegen.pages.i10git.cs.fau.de/pystencils/). Jupyter notebooks are used to provide an

interactive start to pystencils. It is always appreciated if new document notebooks are provided

since this helps others a lot.



## Get Started!



Ready to contribute? Here is how to set up `pystencils` for local development.



1. Fork the `pystencils` repo on GitLab.

2. Clone your fork locally:

```bash

    $ git clone https://i10git.cs.fau.de/your-name/pystencils

```

3. Install your local copy into a virtualenv. It is also recommended to use anaconda or miniconda to manage the python environments.

```bash

    $ mkvirtualenv pystencils

    $ cd pystencils/

    $ pip install -e .

```

4. Create a branch for local development:

```bash

    $ git checkout -b name-of-your-bugfix-or-feature

```

   Now you can make your changes locally.



5. When you're done making changes, check that your changes pass flake8 and the

   tests

```bash

    $ flake8 pystencils

    $ py.test -v -n $NUM_CORES -m "not longrun" .

   

```



   To get all packages needed for development, a requirements list can be found [here](https://i10git.cs.fau.de/pycodegen/pycodegen/-/blob/master/conda_environment_dev.yml). This includes flake8 and pytest.



6. Commit your changes and push your branch to GitHub::

```bash

    $ git add .

    $ git commit -m "Your detailed description of your changes."

    $ git push origin name-of-your-bugfix-or-feature

```

7. Submit a Merge Request on GitLab.



## Merge Request Guidelines



Before you submit a Merge Request, check that it meets these guidelines:



1. All functionality that is implemented through this Merge Request should be covered by unit tests. These are implemented in `pystencil_tests`

2. If the Merge Request adds functionality, the docs should be updated. Put your new functionality into a function with a docstring.

3. If you have a maintainer status for `pystencils`, you can merge Merge Requests to the master branch. However, every Merge Request needs to be reviewed by another developer. Thus it is not allowed to merge a Merge Request, which is submitted by oneself.



## Tips



To run a subset of tests:

```bash

$ py.test my_test.py

```
 
 No newline at end of file

MANIFEST.in

+3 −3
Original line number Original line Diff line number Diff line 
include README.md

include AUTHORS.txt

include COPYING.txt

include CONTRIBUTING.md

include RELEASE-VERSION
 
include CHANGELOG.md

README.md

+28 −14
Original line number Original line Diff line number Diff line
@@ -2,16 +2,16 @@ pystencils 
==========

==========





[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/mabau/pystencils/master?filepath=doc%2Fnotebooks)

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/mabau/pystencils/master?filepath=doc%2Fnotebooks)

[![Docs](https://img.shields.io/badge/read-the_docs-brightgreen.svg)](http://pycodegen.pages.walberla.net/pystencils)

[![Docs](https://img.shields.io/badge/read-the_docs-brightgreen.svg)](https://pycodegen.pages.i10git.cs.fau.de/pystencils)

[![pypi-package](https://badge.fury.io/py/pystencils.svg)](https://badge.fury.io/py/pystencils)

[![pypi-package](https://badge.fury.io/py/pystencils.svg)](https://badge.fury.io/py/pystencils)

[![pipeline status](https://i10git.cs.fau.de/pycodegen/pystencils/badges/master/pipeline.svg)](https://i10git.cs.fau.de/pycodegen/pystencils/commits/master)

[![pipeline status](https://i10git.cs.fau.de/pycodegen/pystencils/badges/master/pipeline.svg)](https://i10git.cs.fau.de/pycodegen/pystencils/commits/master)

[![coverage report](https://i10git.cs.fau.de/pycodegen/pystencils/badges/master/coverage.svg)](http://pycodegen.pages.walberla.net/pystencils/coverage_report)

[![coverage report](https://i10git.cs.fau.de/pycodegen/pystencils/badges/master/coverage.svg)](http://pycodegen.pages.i10git.cs.fau.de/pystencils/coverage_report)





Run blazingly fast stencil codes on numpy arrays.

Run blazingly fast stencil codes on numpy arrays.





*pystencils* uses sympy to define stencil operations, that can be executed on numpy arrays.

*pystencils* uses sympy to define stencil operations, that can be executed on numpy arrays.

Exploiting the stencil structure makes *pystencils* run faster than normal numpy code and even as Cython and numba,

Exploiting the stencil structure makes *pystencils* run faster than normal numpy code and even as Cython and numba,

[as demonstrated in this notebook](http://pycodegen.pages.walberla.net/pystencils/notebooks/demo_benchmark.html).

[as demonstrated in this notebook](https://pycodegen.pages.i10git.cs.fau.de/pystencils/notebooks/demo_benchmark.html).









Here is a code snippet that computes the average of neighboring cells:

Here is a code snippet that computes the average of neighboring cells:
@@ -33,15 +33,15 @@ kernel(f=f_arr, g=g_arr) 
It comes with automatic finite difference discretization for PDEs:

It comes with automatic finite difference discretization for PDEs:





```python

```python

import pystencils as ps

import sympy as sp



c, v = ps.fields("c, v(2): [2D]")

c, v = ps.fields("c, v(2): [2D]")

adv_diff_pde = ps.fd.transient(c) - ps.fd.diffusion(c, sp.symbols("D")) + ps.fd.advection(c, v)

adv_diff_pde = ps.fd.transient(c) - ps.fd.diffusion(c, sp.symbols("D")) + ps.fd.advection(c, v)

discretize = ps.fd.Discretization2ndOrder(dx=1, dt=0.01)

discretize = ps.fd.Discretization2ndOrder(dx=1, dt=0.01)

discretization = discretize(adv_diff_pde)

discretization = discretize(adv_diff_pde)

```

```





Look at the [documentation](http://pycodegen.pages.walberla.net/pystencils) to learn more.





Installation

Installation

------------

------------
@@ -52,12 +52,10 @@ pip install pystencils[interactive] 
Without `[interactive]` you get a minimal version with very little dependencies.

Without `[interactive]` you get a minimal version with very little dependencies.





All options:

All options:

-  `gpu`: use this if an Nvidia GPU is available and CUDA is installed

- `gpu`: use this if an NVIDIA or AMD GPU is available and CUDA or ROCm is installed

-  `opencl`: basic OpenCL support (experimental)

- `alltrafos`: pulls in additional dependencies for loop simplification e.g. libisl

- `alltrafos`: pulls in additional dependencies for loop simplification e.g. libisl

- `bench_db`: functionality to store benchmark result in object databases

- `bench_db`: functionality to store benchmark result in object databases

- `interactive`: installs dependencies to work in Jupyter including image I/O, plotting etc.

- `interactive`: installs dependencies to work in Jupyter including image I/O, plotting etc.

- `autodiff`: enable derivation of adjoint kernels and generation of Torch/Tensorflow operations

- `doc`: packages to build documentation

- `doc`: packages to build documentation





Options can be combined e.g.

Options can be combined e.g.
@@ -65,9 +63,25 @@ Options can be combined e.g. 
pip install pystencils[interactive, gpu, doc]

pip install pystencils[interactive, gpu, doc]

```

```





pystencils is also fully compatible with Windows machines. If working with visual studio and cupy makes sure to run example files first to ensure that cupy can find the compiler's executable.





Documentation

Documentation

-------------

-------------





Read the docs [here](http://pycodegen.pages.walberla.net/pystencils) and

Read the docs [here](https://pycodegen.pages.i10git.cs.fau.de/pystencils) and

check out the Jupyter notebooks in `doc/notebooks`.
 
check out the Jupyter notebooks in `doc/notebooks`. The **Changelog** of pystencils can be found [here](https://i10git.cs.fau.de/pycodegen/pystencils/-/blob/master/CHANGELOG.md).



Authors

-------



Many thanks go to the [contributors](https://i10git.cs.fau.de/pycodegen/pystencils/-/blob/master/AUTHORS.txt) of pystencils.



### Please cite us



If you use pystencils in a publication, please cite the following articles:



Overview:

  - M. Bauer et al, Code Generation for Massively Parallel Phase-Field Simulations. Association for Computing Machinery, 2019. https://doi.org/10.1145/3295500.3356186



Performance Modelling:

  - D. Ernst et al, Analytical performance estimation during code generation on modern GPUs. Journal of Parallel and Distributed Computing, 2023. https://doi.org/10.1016/j.jpdc.2022.11.003

binder/environment.yml

+3 −3
Original line number Original line Diff line number Diff line
@@ -7,14 +7,14 @@ 
#     conda env create -f conda_environment_user.yml

#     conda env create -f conda_environment_user.yml

#     . activate pystencils

#     . activate pystencils

#

#

# If you have CUDA installed and want to use your GPU, uncomment the last line to install pycuda

# If you have CUDA or ROCm installed and want to use your GPU, uncomment the last line to install cupy

#

#

# ----------------------------------------------------------------------------------------------------------------------

# ----------------------------------------------------------------------------------------------------------------------





name: pystencils

name: pystencils

dependencies:

dependencies:

  # Basic dependencies:

  # Basic dependencies:

  - python >= 3.6

  - python >= 3.8

  - numpy

  - numpy

  - sympy >= 1.1

  - sympy >= 1.1

  - appdirs # to find default cache directory on each platform

  - appdirs # to find default cache directory on each platform
@@ -32,4 +32,4 @@ dependencies: 
      - ipy_table  # HTML tables for jupyter notebooks

      - ipy_table  # HTML tables for jupyter notebooks

      - pyevtk # VTK output for serial simulations

      - pyevtk # VTK output for serial simulations

      - blitzdb # file-based No-SQL database to store simulation results

      - blitzdb # file-based No-SQL database to store simulation results

      #- pycuda # add this if you have CUDA installed
 
      #- cupy # add this if you have CUDA or ROCm installed

conftest.py

+47 −32
Original line number Original line Diff line number Diff line 
import os

import os

import pytest

import tempfile

import runpy

import runpy

import sys

import sys

import tempfile

import warnings

import warnings



import nbformat

import pytest

from nbconvert import PythonExporter



from pystencils.boundaries.createindexlist import *  # NOQA

# Trigger config file reading / creation once - to avoid race conditions when multiple instances are creating it

# Trigger config file reading / creation once - to avoid race conditions when multiple instances are creating it

# at the same time

# at the same time

from pystencils.cpu import cpujit

from pystencils.cpu import cpujit
@@ -15,12 +20,17 @@ try: 
    pyximport.install(language_level=3)

    pyximport.install(language_level=3)

except ImportError:

except ImportError:

    pass

    pass

from pystencils.boundaries.createindexlistcython import *  # NOQA









SCRIPT_FOLDER = os.path.dirname(os.path.realpath(__file__))

SCRIPT_FOLDER = os.path.dirname(os.path.realpath(__file__))

sys.path.insert(0, os.path.abspath('pystencils'))

sys.path.insert(0, os.path.abspath('pystencils'))





# the Ubuntu pipeline uses an older version of pytest which uses deprecated functionality.

# This leads to many warinings in the test and coverage pipeline.

pytest_numeric_version = [int(x, 10) for x in pytest.__version__.split('.')]

pytest_numeric_version.reverse()

pytest_version = sum(x * (100 ** i) for i, x in enumerate(pytest_numeric_version))







def add_path_to_ignore(path):

def add_path_to_ignore(path):

    if not os.path.exists(path):

    if not os.path.exists(path):
@@ -29,46 +39,49 @@ def add_path_to_ignore(path): 
    collect_ignore += [os.path.join(SCRIPT_FOLDER, path, f) for f in os.listdir(os.path.join(SCRIPT_FOLDER, path))]

    collect_ignore += [os.path.join(SCRIPT_FOLDER, path, f) for f in os.listdir(os.path.join(SCRIPT_FOLDER, path))]









collect_ignore = [os.path.join(SCRIPT_FOLDER, "doc", "conf.py")]

collect_ignore = [os.path.join(SCRIPT_FOLDER, "doc", "conf.py"),

add_path_to_ignore('pystencils_tests/benchmark')

                  os.path.join(SCRIPT_FOLDER, "src", "pystencils", "opencl", "opencl.autoinit")]

add_path_to_ignore('tests/benchmark')

add_path_to_ignore('_local_tmp')

add_path_to_ignore('_local_tmp')









collect_ignore += [os.path.join(SCRIPT_FOLDER, "pystencils/autodiff.py")]



try:

try:

    import pycuda

    import cupy

except ImportError:

except ImportError:

    collect_ignore += [os.path.join(SCRIPT_FOLDER, "pystencils/pystencils_tests/test_cudagpu.py")]

    collect_ignore += [os.path.join(SCRIPT_FOLDER, "tests/test_gpu.py")]

    add_path_to_ignore('pystencils/gpucuda')

    add_path_to_ignore('src/pystencils/gpu')





try:

try:

    import llvmlite

    import waLBerla

except ImportError:

except ImportError:

    collect_ignore += [os.path.join(SCRIPT_FOLDER, 'pystencils_tests/backends/llvm.py')]

    collect_ignore += [os.path.join(SCRIPT_FOLDER, "tests/test_aligned_array.py"),

    add_path_to_ignore('pystencils/llvm')

                       os.path.join(SCRIPT_FOLDER, "tests/test_datahandling_parallel.py"),

                       os.path.join(SCRIPT_FOLDER, "doc/notebooks/03_tutorial_datahandling.ipynb"),

                       os.path.join(SCRIPT_FOLDER, "src/pystencils/datahandling/parallel_datahandling.py"),

                       os.path.join(SCRIPT_FOLDER, "tests/test_small_block_benchmark.ipynb")]





try:

try:

    import kerncraft

    import blitzdb

except ImportError:

except ImportError:

    collect_ignore += [os.path.join(SCRIPT_FOLDER, "pystencils_tests/test_kerncraft_coupling.py"),

    add_path_to_ignore('src/pystencils/runhelper')

                       os.path.join(SCRIPT_FOLDER, "pystencils_tests/benchmark/benchmark.py")]

    collect_ignore += [os.path.join(SCRIPT_FOLDER, "tests/test_parameterstudy.py")]

    add_path_to_ignore('pystencils/kerncraft_coupling')

    collect_ignore += [os.path.join(SCRIPT_FOLDER, "tests/test_json_serializer.py")]





try:

try:

    import waLBerla

    import islpy

except ImportError:

except ImportError:

    collect_ignore += [os.path.join(SCRIPT_FOLDER, "pystencils_tests/test_aligned_array.py"),

    collect_ignore += [os.path.join(SCRIPT_FOLDER, "src/pystencils/integer_set_analysis.py")]

                       os.path.join(SCRIPT_FOLDER, "pystencils_tests/test_datahandling_parallel.py"),

                       os.path.join(SCRIPT_FOLDER, "doc/notebooks/03_tutorial_datahandling.ipynb"),

                       os.path.join(SCRIPT_FOLDER, "pystencils/datahandling/parallel_datahandling.py"),

                       os.path.join(SCRIPT_FOLDER, "pystencils_tests/test_small_block_benchmark.ipynb")]





try:

try:

    import blitzdb

    import graphviz

except ImportError:

except ImportError:

    add_path_to_ignore('pystencils/runhelper')

    collect_ignore += [os.path.join(SCRIPT_FOLDER, "src/pystencils/backends/dot.py")]

    collect_ignore += [os.path.join(SCRIPT_FOLDER, "doc/notebooks/01_tutorial_getting_started.ipynb")]





try:

    import pyevtk

except ImportError:

    collect_ignore += [os.path.join(SCRIPT_FOLDER, "src/pystencils/datahandling/vtk.py")]





collect_ignore += [os.path.join(SCRIPT_FOLDER, 'setup.py')]

collect_ignore += [os.path.join(SCRIPT_FOLDER, 'setup.py')]
@@ -78,10 +91,6 @@ for root, sub_dirs, files in os.walk('.'): 
            collect_ignore.append(f)

            collect_ignore.append(f)









import nbformat

from nbconvert import PythonExporter





class IPythonMockup:

class IPythonMockup:

    def run_line_magic(self, *args, **kwargs):

    def run_line_magic(self, *args, **kwargs):

        pass

        pass
@@ -128,12 +137,15 @@ class IPyNbFile(pytest.File): 
        exporter.exclude_markdown = True

        exporter.exclude_markdown = True

        exporter.exclude_input_prompt = True

        exporter.exclude_input_prompt = True





        notebook_contents = self.fspath.open()

        notebook_contents = self.fspath.open(encoding='utf-8')





        with warnings.catch_warnings():

        with warnings.catch_warnings():

            warnings.filterwarnings("ignore", "IPython.core.inputsplitter is deprecated")

            warnings.filterwarnings("ignore", "IPython.core.inputsplitter is deprecated")

            notebook = nbformat.read(notebook_contents, 4)

            notebook = nbformat.read(notebook_contents, 4)

            code, _ = exporter.from_notebook_node(notebook)

            code, _ = exporter.from_notebook_node(notebook)

        if pytest_version >= 50403:

            yield IPyNbTest.from_parent(name=self.name, parent=self, code=code)

        else:

            yield IPyNbTest(self.name, self, code)

            yield IPyNbTest(self.name, self, code)





    def teardown(self):

    def teardown(self):
@@ -143,4 +155,7 @@ class IPyNbFile(pytest.File): 
def pytest_collect_file(path, parent):

def pytest_collect_file(path, parent):

    glob_exprs = ["*demo*.ipynb", "*tutorial*.ipynb", "test_*.ipynb"]

    glob_exprs = ["*demo*.ipynb", "*tutorial*.ipynb", "test_*.ipynb"]

    if any(path.fnmatch(g) for g in glob_exprs):

    if any(path.fnmatch(g) for g in glob_exprs):

        if pytest_version >= 50403:

            return IPyNbFile.from_parent(fspath=path, parent=parent)

        else:

            return IPyNbFile(path, parent)
 
            return IPyNbFile(path, parent)

doc/conf.py

100644 → 100755
+13 −8
Original line number Original line Diff line number Diff line
@@ -4,10 +4,11 @@ 
import datetime

import datetime

import sphinx_rtd_theme

import sphinx_rtd_theme

import os

import os

import re

import sys

import sys





sys.path.insert(0, os.path.abspath('.'))

sys.path.insert(0, os.path.abspath('.'))

from version_from_git import version_number_from_git

import pystencils





extensions = [

extensions = [

    'sphinx.ext.autodoc',

    'sphinx.ext.autodoc',
@@ -25,11 +26,14 @@ templates_path = ['_templates'] 
source_suffix = '.rst'

source_suffix = '.rst'

master_doc = 'index'

master_doc = 'index'





copyright = '{}, Martin Bauer'.format(datetime.datetime.now().year)

copyright = f'{datetime.datetime.now().year}, Martin Bauer, Markus Holzer, Frederik Hennig'

author = 'Martin Bauer'

author = 'Martin Bauer, Markus Holzer, Frederik Hennig'

version = version_number_from_git()

# The short X.Y version (including .devXXXX, rcX, b1 suffixes if present)

release = version_number_from_git()

version = re.sub(r'(\d+\.\d+)\.\d+(.*)', r'\1\2', pystencils.__version__)

language = None

version = re.sub(r'(\.dev\d+).*?$', r'\1', version)

# The full version, including alpha/beta/rc tags.

release = pystencils.__version__

language = 'en'

exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store', '**.ipynb_checkpoints']

exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store', '**.ipynb_checkpoints']

default_role = 'any'

default_role = 'any'

pygments_style = 'sphinx'

pygments_style = 'sphinx'
@@ -47,13 +51,14 @@ nbsphinx_execute = 'never' 
nbsphinx_codecell_lexer = 'python3'

nbsphinx_codecell_lexer = 'python3'





# Example configuration for intersphinx: refer to the Python standard library.

# Example configuration for intersphinx: refer to the Python standard library.

intersphinx_mapping = {'python': ('https://docs.python.org/3.6', None),

intersphinx_mapping = {'python': ('https://docs.python.org/3.8', None),

                       'numpy': ('https://docs.scipy.org/doc/numpy/', None),

                       'numpy': ('https://docs.scipy.org/doc/numpy/', None),

                       'matplotlib': ('https://matplotlib.org/', None),

                       'matplotlib': ('https://matplotlib.org/', None),

                       'sympy': ('https://docs.sympy.org/latest/', None),

                       'sympy': ('https://docs.sympy.org/latest/', None),

                       }

                       }





autodoc_member_order = 'bysource'

autodoc_member_order = 'bysource'

bibtex_bibfiles = ['sphinx/pystencils.bib']





project = 'pystencils'

project = 'pystencils'

html_logo = "img/logo.png"
 
html_logo = 'img/logo.png'

doc/index.rst

+1 −0
Original line number Original line Diff line number Diff line
@@ -14,5 +14,6 @@ pystencils can help you to generate blazingly fast code for image processing, nu 




.. image:: /img/pystencils_arch_block_diagram.svg

.. image:: /img/pystencils_arch_block_diagram.svg

    :height: 450px

    :height: 450px

    :align: center

doc/sphinx/api.rst

+1 −0
Original line number Original line Diff line number Diff line
@@ -5,6 +5,7 @@ API Reference 
   :maxdepth: 3

   :maxdepth: 3





   kernel_compile_and_call.rst

   kernel_compile_and_call.rst

   enums.rst

   simplifications.rst

   simplifications.rst

   datahandling.rst

   datahandling.rst

   configuration.rst

   configuration.rst

doc/sphinx/enums.rst

0 → 100644
+6 −0
Original line number Original line Diff line number Diff line 
************

Enumerations

************



.. automodule:: pystencils.enums

   :members:

doc/sphinx/kernel_compile_and_call.rst

+10 −5
Original line number Original line Diff line number Diff line
@@ -8,9 +8,14 @@ Creating kernels 




.. autofunction:: pystencils.create_kernel

.. autofunction:: pystencils.create_kernel





.. autofunction:: pystencils.create_indexed_kernel

.. autoclass:: pystencils.CreateKernelConfig

    :members:



.. autofunction:: pystencils.kernelcreation.create_domain_kernel



.. autofunction:: pystencils.kernelcreation.create_indexed_kernel





.. autofunction:: pystencils.create_staggered_kernel

.. autofunction:: pystencils.kernelcreation.create_staggered_kernel









Code printing

Code printing
@@ -22,11 +27,11 @@ Code printing 
GPU Indexing

GPU Indexing

-------------

-------------





.. autoclass:: pystencils.gpucuda.AbstractIndexing

.. autoclass:: pystencils.gpu.AbstractIndexing

   :members:

   :members:





.. autoclass:: pystencils.gpucuda.BlockIndexing

.. autoclass:: pystencils.gpu.BlockIndexing

   :members:

   :members:





.. autoclass:: pystencils.gpucuda.LineIndexing

.. autoclass:: pystencils.gpu.LineIndexing

   :members:
 
   :members:

doc/sphinx/simplifications.rst

+16 −2
Original line number Original line Diff line number Diff line
@@ -10,13 +10,27 @@ AssignmentCollection 
   :members:

   :members:









SimplificationStrategy

======================



.. autoclass:: pystencils.simp.SimplificationStrategy

    :members:



Simplifications

Simplifications

===============

===============





.. automodule:: pystencils.simp

.. automodule:: pystencils.simp.simplifications

    :members:

    :members:





Subexpression insertion

=======================





The subexpression insertions have the goal to insert subexpressions which will not reduce the number of FLOPs.

For example a constant value kept as subexpression will lead to a new variable in the code which will occupy

a register slot. On the other side a single variable could just be inserted in all assignments.



.. automodule:: pystencils.simp.subexpression_insertion

    :members:

doc/version_from_git.py

deleted100644 → 0
+0 −31
Original line number Original line Diff line number Diff line 
import subprocess



def version_number_from_git(tag_prefix='release/', sha_length=10, version_format="{version}.dev{commits}+{sha}"):



    def get_released_versions():

        tags = sorted(subprocess.getoutput('git tag').split('\n'))

        versions = [t[len(tag_prefix):] for t in tags if t.startswith(tag_prefix)]

        return versions



    def tag_from_version(v):

        return tag_prefix + v



    def increment_version(v):

        parsed_version = [int(i) for i in v.split('.')]

        parsed_version[-1] += 1

        return '.'.join(str(i) for i in parsed_version)



    latest_release = get_released_versions()[-1]

    commits_since_tag = subprocess.getoutput('git rev-list {}..HEAD --count'.format(tag_from_version(latest_release)))

    sha = subprocess.getoutput('git rev-parse HEAD')[:sha_length]

    is_dirty = len(subprocess.getoutput("git status --untracked-files=no -s")) > 0



    if int(commits_since_tag) == 0:

        version_string = latest_release

    else:

        next_version = increment_version(latest_release)

        version_string = version_format.format(version=next_version, commits=commits_since_tag, sha=sha)



    if is_dirty:

        version_string += ".dirty"

    return version_string

pre-push

deleted100755 → 0
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Original line number Original line Diff line number Diff line 
#!/usr/bin/env bash



# Checks run before every push

# has to be copied to .git/hooks



echo "Running pre-push hook"

echo "Running flake8 check"

flake8 --append-config=.flake8 pystencils



# $? stores exit value of the last command

if [ $? -ne 0 ]; then

 echo "flake8 failed"

 exit 1

fi



python3 setup.py quicktest



# $? stores exit value of the last command

if [ $? -ne 0 ]; then

 echo "quicktest failed"

 exit 1

fi

pyproject.toml

0 → 100644
+98 −0
Original line number Original line Diff line number Diff line 
[project]

name = "pystencils"

description = "Speeding up stencil computations on CPUs and GPUs"

dynamic = ["version"]

readme = "README.md"

authors = [

    { name = "Martin Bauer" },

    { name = "Jan Hönig " },

    { name = "Markus Holzer" },

    { name = "Frederik Hennig" },

    { email = "cs10-codegen@fau.de" },

]

license = { file = "COPYING.txt" }

requires-python = ">=3.10"

dependencies = ["sympy>=1.9,<=1.12.1", "numpy>=1.8.0", "appdirs", "joblib", "pyyaml", "fasteners"]

classifiers = [

    "Development Status :: 4 - Beta",

    "Framework :: Jupyter",

    "Topic :: Software Development :: Code Generators",

    "Topic :: Scientific/Engineering :: Physics",

    "Intended Audience :: Developers",

    "Intended Audience :: Science/Research",

    "License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)",

]



[project.urls]

"Bug Tracker" = "https://i10git.cs.fau.de/pycodegen/pystencils/-/issues"

"Documentation" = "https://pycodegen.pages.i10git.cs.fau.de/pystencils/"

"Source Code" = "https://i10git.cs.fau.de/pycodegen/pystencils"



[project.optional-dependencies]

gpu = ['cupy']

alltrafos = ['islpy', 'py-cpuinfo']

bench_db = ['blitzdb', 'pymongo', 'pandas']

interactive = [

    'matplotlib',

    'ipy_table',

    'imageio',

    'jupyter',

    'pyevtk',

    'rich',

    'graphviz',

]

use_cython = [

    'Cython'

]

doc = [

    'sphinx',

    'sphinx_rtd_theme',

    'nbsphinx',

    'sphinxcontrib-bibtex',

    'sphinx_autodoc_typehints',

    'pandoc',

]

tests = [

    'pytest',

    'pytest-cov',

    'pytest-html',

    'ansi2html',

    'pytest-xdist',

    'flake8',

    'nbformat',

    'nbconvert',

    'ipython',

    'matplotlib',

    'py-cpuinfo',

    'randomgen>=1.18',

]



[build-system]

requires = [

    "setuptools>=61",

    "versioneer[toml]>=0.29",

    # 'Cython'

]

build-backend = "setuptools.build_meta"



[tool.setuptools.package-data]

pystencils = [

    "include/*.h",

    "boundaries/createindexlistcython.pyx"

]



[tool.setuptools.packages.find]

where = ["src"]

include = ["pystencils", "pystencils.*"]

namespaces = false



[tool.versioneer]

# See the docstring in versioneer.py for instructions. Note that you must

# re-run 'versioneer.py setup' after changing this section, and commit the

# resulting files.

VCS = "git"

style = "pep440"

versionfile_source = "src/pystencils/_version.py"

versionfile_build = "pystencils/_version.py"

tag_prefix = "release/"

parentdir_prefix = "pystencils-"

pystencils/autodiff.py

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Original line number Original line Diff line number Diff line 
"""

Provides tools for generation of auto-differentiable operations.



See https://github.com/theHamsta/pystencils_autodiff



Installation:



.. code-block:: bash

    pip install pystencils-autodiff

"""



raise NotImplementedError('pystencils-autodiff is not installed. Run `pip install pystencils-autodiff`')

pystencils/backends/cuda_backend.py

deleted100644 → 0
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Original line number Original line Diff line number Diff line 
from os.path import dirname, join



from pystencils.astnodes import Node

from pystencils.backends.cbackend import CBackend, CustomSympyPrinter, generate_c

from pystencils.fast_approximation import fast_division, fast_inv_sqrt, fast_sqrt

from pystencils.interpolation_astnodes import InterpolationMode



with open(join(dirname(__file__), 'cuda_known_functions.txt')) as f:

    lines = f.readlines()

    CUDA_KNOWN_FUNCTIONS = {l.strip(): l.strip() for l in lines if l}





def generate_cuda(astnode: Node, signature_only: bool = False) -> str:

    """Prints an abstract syntax tree node as CUDA code.



    Args:

        astnode: KernelFunction node to generate code for

        signature_only: if True only the signature is printed



    Returns:

        C-like code for the ast node and its descendants

    """

    return generate_c(astnode, signature_only, dialect='cuda')





class CudaBackend(CBackend):



    def __init__(self, sympy_printer=None,

                 signature_only=False):

        if not sympy_printer:

            sympy_printer = CudaSympyPrinter()



        super().__init__(sympy_printer, signature_only, dialect='cuda')



    def _print_SharedMemoryAllocation(self, node):

        code = "__shared__ {dtype} {name}[{num_elements}];"

        return code.format(dtype=node.symbol.dtype,

                           name=self.sympy_printer.doprint(node.symbol.name),

                           num_elements='*'.join([str(s) for s in node.shared_mem.shape]))



    @staticmethod

    def _print_ThreadBlockSynchronization(node):

        code = "__synchtreads();"

        return code



    def _print_TextureDeclaration(self, node):



        if node.texture.field.dtype.numpy_dtype.itemsize > 4:

            code = "texture<fp_tex_%s, cudaTextureType%iD, cudaReadModeElementType> %s;" % (

                str(node.texture.field.dtype),

                node.texture.field.spatial_dimensions,

                node.texture

            )

        else:

            code = "texture<%s, cudaTextureType%iD, cudaReadModeElementType> %s;" % (

                str(node.texture.field.dtype),

                node.texture.field.spatial_dimensions,

                node.texture

            )

        return code



    def _print_SkipIteration(self, _):

        return "return;"





class CudaSympyPrinter(CustomSympyPrinter):

    language = "CUDA"



    def __init__(self):

        super(CudaSympyPrinter, self).__init__()

        self.known_functions.update(CUDA_KNOWN_FUNCTIONS)



    def _print_TextureAccess(self, node):

        dtype = node.texture.field.dtype.numpy_dtype



        if node.texture.interpolation_mode == InterpolationMode.CUBIC_SPLINE:

            template = "cubicTex%iDSimple(%s, %s)"

        else:

            if dtype.itemsize > 4:

                # Use PyCuda hack!

                # https://github.com/inducer/pycuda/blob/master/pycuda/cuda/pycuda-helpers.hpp

                template = "fp_tex%iD(%s, %s)"

            else:

                template = "tex%iD(%s, %s)"



        code = template % (

            node.texture.field.spatial_dimensions,

            str(node.texture),

            # + 0.5 comes from Nvidia's staggered indexing

            ', '.join(self._print(o + 0.5) for o in reversed(node.offsets))

        )

        return code



    def _print_Function(self, expr):

        if isinstance(expr, fast_division):

            return "__fdividef(%s, %s)" % tuple(self._print(a) for a in expr.args)

        elif isinstance(expr, fast_sqrt):

            return "__fsqrt_rn(%s)" % tuple(self._print(a) for a in expr.args)

        elif isinstance(expr, fast_inv_sqrt):

            return "__frsqrt_rn(%s)" % tuple(self._print(a) for a in expr.args)

        return super()._print_Function(expr)

pystencils/backends/cuda_known_functions.txt

deleted100644 → 0
+0 −294
Original line number Original line Diff line number Diff line 
__prof_trigger

printf



__syncthreads

__syncthreads_count

__syncthreads_and

__syncthreads_or

__syncwarp

__threadfence

__threadfence_block

__threadfence_system



atomicAdd

atomicSub

atomicExch

atomicMin

atomicMax

atomicInc

atomicDec

atomicAnd

atomicOr

atomicXor

atomicCAS



__all_sync

__any_sync

__ballot_sync

__active_mask



__shfl_sync

__shfl_up_sync

__shfl_down_sync

__shfl_xor_sync



__match_any_sync

__match_all_sync



__isGlobal

__isShared

__isConstant

__isLocal



tex1Dfetch

tex1D

tex2D

tex3D



sqrtf

rsqrtf

cbrtf

rcbrtf

hypotf

rhypotf

norm3df

rnorm3df

norm4df

rnorm4df

normf

rnormf

expf

exp2f

exp10f

expm1f

logf

log2f

log10f

log1pf

sinf

cosf

tanf

sincosf

sinpif

cospif

sincospif

asinf

acosf

atanf

atan2f

sinhf

coshf

tanhf

asinhf

acoshf

atanhf

powf

erff

erfcf

erfinvf

erfcinvf

erfcxf

normcdff

normcdfinvf

lgammaf

tgammaf

fmaf

frexpf

ldexpf

scalbnf

scalblnf

logbf

ilogbf

j0f

j1f

jnf

y0f

y1f

ynf

cyl_bessel_i0f

cyl_bessel_i1f

fmodf

remainderf

remquof

modff

fdimf

truncf

roundf

rintf

nearbyintf

ceilf

floorf

lrintf

lroundf

llrintf

llroundf



sqrt

rsqrt

cbrt

rcbrt

hypot

rhypot

norm3d

rnorm3d

norm4d

rnorm4d

norm

rnorm

exp

exp2

exp10

expm1

log

log2

log10

log1p

sin

cos

tan

sincos

sinpi

cospi

sincospi

asin

acos

atan

atan2

sinh

cosh

tanh

asinh

acosh

atanh

pow

erf

erfc

erfinv

erfcinv

erfcx

normcdf

normcdfinv

lgamma

tgamma

fma

frexp

ldexp

scalbn

scalbln

logb

ilogb

j0

j1

jn

y0

y1

yn

cyl_bessel_i0

cyl_bessel_i1

fmod

remainder

remquo

mod

fdim

trunc

round

rint

nearbyint

ceil

floor

lrint

lround

llrint

llround



__fdividef

__sinf

__cosf

__tanf

__sincosf

__logf

__log2f

__log10f

__expf

__exp10f

__powf



__fadd_rn

__fsub_rn

__fmul_rn

__fmaf_rn

__frcp_rn

__fsqrt_rn

__frsqrt_rn

__fdiv_rn



__fadd_rz

__fsub_rz

__fmul_rz

__fmaf_rz

__frcp_rz

__fsqrt_rz

__frsqrt_rz

__fdiv_rz



__fadd_ru

__fsub_ru

__fmul_ru

__fmaf_ru

__frcp_ru

__fsqrt_ru

__frsqrt_ru

__fdiv_ru



__fadd_rd

__fsub_rd

__fmul_rd

__fmaf_rd

__frcp_rd

__fsqrt_rd

__frsqrt_rd

__fdiv_rd



__fdividef

__expf

__exp10f

__logf

__log2f

__log10f

__sinf

__cosf

__sincosf

__tanf

__powf



__dadd_rn

__dsub_rn

__dmul_rn

__fma_rn

__ddiv_rn

__drcp_rn

__dsqrt_rn



__dadd_rz

__dsub_rz

__dmul_rz

__fma_rz

__ddiv_rz

__drcp_rz

__dsqrt_rz



__dadd_ru

__dsub_ru

__dmul_ru

__fma_ru

__ddiv_ru

__drcp_ru

__dsqrt_ru



__dadd_rd

__dsub_rd

__dmul_rd

__fma_rd

__ddiv_rd

__drcp_rd

__dsqrt_rd

pystencils/backends/opencl1.1_known_functions.txt

deleted100644 → 0
+0 −100
Original line number Original line Diff line number Diff line 
acos

acosh

acospi

asin

asinh

asinpi

atan

atan2

atanh

atanpi

atan2pi

cbrt

ceil

copysign

cos

cosh

cospi

erfc

erf

exp

exp2

exp10

expm1

fabs

fdim

floor

fma

fmax

fmax

fmin45

fmin

fmod

fract

frexp

hypot

ilogb

ldexp

lgamma

lgamma_r

log

log2

log10

log1p

logb

mad 

maxmag 

minmag 

modf 

nextafter

pow 

pown

powr

remquo 

intn

remquo

rint

rootn

rootn

round

rsqrt

sin

sincos

sinh

sinpi

sqrt

tan

tanh

tanpi

tgamma

trunc





half_cos 

half_divide

half_exp 

half_exp2 

half_exp10 

half_log 

half_log2 

half_log10 

half_powr 

half_recip 

half_rsqrt 

half_sin 

half_sqrt 

half_tan 

native_cos 

native_divide

native_exp 

native_exp2 

native_exp10 

native_log 

native_log2 

native_log10 

native_powr 

native_recip 

native_rsqrt 

native_sin 

native_sqrt 

native_tan

pystencils/backends/opencl_backend.py

deleted100644 → 0
+0 −97
Original line number Original line Diff line number Diff line 
from os.path import dirname, join



import pystencils.data_types

from pystencils.astnodes import Node

from pystencils.backends.cbackend import CustomSympyPrinter, generate_c

from pystencils.backends.cuda_backend import CudaBackend, CudaSympyPrinter

from pystencils.fast_approximation import fast_division, fast_inv_sqrt, fast_sqrt



with open(join(dirname(__file__), 'opencl1.1_known_functions.txt')) as f:

    lines = f.readlines()

    OPENCL_KNOWN_FUNCTIONS = {l.strip(): l.strip() for l in lines if l}





def generate_opencl(astnode: Node, signature_only: bool = False) -> str:

    """Prints an abstract syntax tree node (made for target 'gpu') as OpenCL code.



    Args:

        astnode: KernelFunction node to generate code for

        signature_only: if True only the signature is printed



    Returns:

        C-like code for the ast node and its descendants

    """

    return generate_c(astnode, signature_only, dialect='opencl')





class OpenClBackend(CudaBackend):



    def __init__(self,

                 sympy_printer=None,

                 signature_only=False):

        if not sympy_printer:

            sympy_printer = OpenClSympyPrinter()



        super().__init__(sympy_printer, signature_only)

        self._dialect = 'opencl'



    def _print_Type(self, node):

        code = super()._print_Type(node)

        if isinstance(node, pystencils.data_types.PointerType):

            return "__global " + code

        else:

            return code



    def _print_ThreadBlockSynchronization(self, node):

        raise NotImplementedError()



    def _print_TextureDeclaration(self, node):

        raise NotImplementedError()





class OpenClSympyPrinter(CudaSympyPrinter):

    language = "OpenCL"



    DIMENSION_MAPPING = {

        'x': '0',

        'y': '1',

        'z': '2'

    }

    INDEXING_FUNCTION_MAPPING = {

        'blockIdx': 'get_group_id',

        'threadIdx': 'get_local_id',

        'blockDim': 'get_local_size',

        'gridDim': 'get_global_size'

    }



    def __init__(self):

        CustomSympyPrinter.__init__(self)

        self.known_functions = OPENCL_KNOWN_FUNCTIONS



    def _print_ThreadIndexingSymbol(self, node):

        symbol_name: str = node.name

        function_name, dimension = tuple(symbol_name.split("."))

        dimension = self.DIMENSION_MAPPING[dimension]

        function_name = self.INDEXING_FUNCTION_MAPPING[function_name]

        return f"(int) {function_name}({dimension})"



    def _print_TextureAccess(self, node):

        raise NotImplementedError()



    # For math functions, OpenCL is more similar to the C++ printer CustomSympyPrinter

    # since built-in math functions are generic.

    # In CUDA, you have to differentiate between `sin` and `sinf`

    try:

        _print_math_func = CustomSympyPrinter._print_math_func

    except AttributeError:

        pass

    _print_Pow = CustomSympyPrinter._print_Pow



    def _print_Function(self, expr):

        if isinstance(expr, fast_division):

            return "native_divide(%s, %s)" % tuple(self._print(a) for a in expr.args)

        elif isinstance(expr, fast_sqrt):

            return "native_sqrt(%s)" % tuple(self._print(a) for a in expr.args)

        elif isinstance(expr, fast_inv_sqrt):

            return "native_rsqrt(%s)" % tuple(self._print(a) for a in expr.args)

        return CustomSympyPrinter._print_Function(self, expr)

pystencils/cache.py

deleted100644 → 0
+0 −45
Original line number Original line Diff line number Diff line 
import os

from collections.abc import Hashable

from functools import partial

from itertools import chain



try:

    from functools import lru_cache as memorycache

except ImportError:

    from backports.functools_lru_cache import lru_cache as memorycache





try:

    from joblib import Memory

    from appdirs import user_cache_dir

    if 'PYSTENCILS_CACHE_DIR' in os.environ:

        cache_dir = os.environ['PYSTENCILS_CACHE_DIR']

    else:

        cache_dir = user_cache_dir('pystencils')

    disk_cache = Memory(cache_dir, verbose=False).cache

    disk_cache_no_fallback = disk_cache

except ImportError:

    # fallback to in-memory caching if joblib is not available

    disk_cache = memorycache(maxsize=64)



    def disk_cache_no_fallback(o):

        return o





def _wrapper(wrapped_func, cached_func, *args, **kwargs):

    if all(isinstance(a, Hashable) for a in chain(args, kwargs.values())):

        return cached_func(*args, **kwargs)

    else:

        return wrapped_func(*args, **kwargs)





def memorycache_if_hashable(maxsize=128, typed=False):



    def wrapper(func):

        return partial(_wrapper, func, memorycache(maxsize, typed)(func))



    return wrapper



# Disable memory cache:

# disk_cache = lambda o: o

# disk_cache_no_fallback = lambda o: o

pystencils/data_types.py

deleted100644 → 0
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File deleted.

Preview size limit exceeded, changes collapsed.

pystencils/gpucuda/texture_utils.py

deleted100644 → 0
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Original line number Original line Diff line number Diff line 
# -*- coding: utf-8 -*-

#

# Copyright © 2019 Stephan Seitz <stephan.seitz@fau.de>

#

# Distributed under terms of the GPLv3 license.



"""



"""



from os.path import dirname, isdir, join



import numpy as np



try:

    import pycuda.driver as cuda

    from pycuda import gpuarray

except Exception:

    pass





def pow_two_divider(n):

    if n == 0:

        return 0

    divider = 1

    while (n & divider) == 0:

        divider <<= 1

    return divider





def ndarray_to_tex(tex_ref,

                   ndarray,

                   address_mode=None,

                   filter_mode=None,

                   use_normalized_coordinates=False,

                   read_as_integer=False):



    if address_mode is None:

        address_mode = cuda.address_mode.BORDER

    if filter_mode is None:

        filter_mode = cuda.filter_mode.LINEAR



    if isinstance(ndarray, np.ndarray):

        cu_array = cuda.np_to_array(ndarray, 'C')

    elif isinstance(ndarray, gpuarray.GPUArray):

        cu_array = cuda.gpuarray_to_array(ndarray, 'C')

    else:

        raise TypeError(

            'ndarray must be numpy.ndarray or pycuda.gpuarray.GPUArray')



    cuda.TextureReference.set_array(tex_ref, cu_array)



    tex_ref.set_address_mode(0, address_mode)

    if ndarray.ndim >= 2:

        tex_ref.set_address_mode(1, address_mode)

    if ndarray.ndim >= 3:

        tex_ref.set_address_mode(2, address_mode)

    tex_ref.set_filter_mode(filter_mode)



    if not use_normalized_coordinates:

        tex_ref.set_flags(tex_ref.get_flags() & ~cuda.TRSF_NORMALIZED_COORDINATES)



    if not read_as_integer:

        tex_ref.set_flags(tex_ref.get_flags() & ~cuda.TRSF_READ_AS_INTEGER)





def prefilter_for_cubic_bspline(gpuarray):

    import pycuda.autoinit  # NOQA

    from pycuda.compiler import SourceModule



    ndim = gpuarray.ndim

    assert ndim == 2 or ndim == 3, "Only 2d or 3d supported"

    assert isdir(join(dirname(__file__), "CubicInterpolationCUDA", "code")), \

        "Submodule CubicInterpolationCUDA does not exist"

    nvcc_options = ["-w", "-std=c++11", "-Wno-deprecated-gpu-targets"]

    nvcc_options += ["-I" + join(dirname(__file__), "CubicInterpolationCUDA", "code")]

    nvcc_options += ["-I" + join(dirname(__file__), "CubicInterpolationCUDA", "code", "internal")]



    file_name = join(dirname(__file__), "CubicInterpolationCUDA", "code", "cubicPrefilter%iD.cu" % ndim)

    with open(file_name) as file:

        code = file.read()



    mod = SourceModule(code, options=nvcc_options)



    if ndim == 2:

        height, width = gpuarray.shape

        block = min(pow_two_divider(height), 64)

        grid = height // block

        func = mod.get_function('SamplesToCoefficients2DXf')

        func(gpuarray, np.uint32(gpuarray.strides[-2]), *(np.uint32(r)

                                                          for r in reversed(gpuarray.shape)),

             block=(block, 1, 1),

             grid=(grid, 1, 1))



        block = min(pow_two_divider(width), 64)

        grid = width // block

        func = mod.get_function('SamplesToCoefficients2DYf')

        func(gpuarray, np.uint32(gpuarray.strides[-2]), *(np.uint32(r)

                                                          for r in reversed(gpuarray.shape)),

             block=(block, 1, 1),

             grid=(grid, 1, 1))

    elif ndim == 3:

        depth, height, width = gpuarray.shape

        dimX = min(min(pow_two_divider(width), pow_two_divider(height)), 64)

        dimY = min(min(pow_two_divider(depth), pow_two_divider(height)), 512 / dimX)

        block = (dimX, dimY, 1)



        dimGridX = (height // block[0], depth // block[1], 1)

        dimGridY = (width // block[0], depth // block[1], 1)

        dimGridZ = (width // block[0], height // block[1], 1)



        func = mod.get_function("SamplesToCoefficients3DXf")

        func(gpuarray, np.uint32(gpuarray.strides[-2]), *(np.uint32(r)

                                                          for r in reversed(gpuarray.shape)),

             block=block,

             grid=dimGridX)

        func = mod.get_function("SamplesToCoefficients3DYf")

        func(gpuarray, np.uint32(gpuarray.strides[-2]), *(np.uint32(r)

                                                          for r in reversed(gpuarray.shape)),

             block=block,

             grid=dimGridY)

        func = mod.get_function("SamplesToCoefficients3DZf")

        func(gpuarray, np.uint32(gpuarray.strides[-2]), *(np.uint32(r)

                                                          for r in reversed(gpuarray.shape)),

             block=block,

             grid=dimGridZ)

pystencils/include/PyStencilsField.h

deleted100644 → 0
+0 −19
Original line number Original line Diff line number Diff line 
#pragma once



extern "C++" {

#ifdef __CUDA_ARCH__

template <typename DTYPE_T, std::size_t DIMENSION> struct PyStencilsField {

  DTYPE_T *data;

  DTYPE_T shape[DIMENSION];

  DTYPE_T stride[DIMENSION];

};

#else

#include <array>



template <typename DTYPE_T, std::size_t DIMENSION> struct PyStencilsField {

  DTYPE_T *data;

  std::array<DTYPE_T, DIMENSION> shape;

  std::array<DTYPE_T, DIMENSION> stride;

};

#endif

}

pystencils/include/aesni_rand.h

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#if !defined(__AES__) || !defined(__SSE4_1__)

#error AES-NI and SSE4.1 need to be enabled

#endif



#include <emmintrin.h> // SSE2

#include <wmmintrin.h> // AES

#ifdef __AVX512VL__

#include <immintrin.h> // AVX*

#else

#include <smmintrin.h>  // SSE4

#ifdef __FMA__

#include <immintrin.h> // FMA

#endif

#endif

#include <cstdint>



#define QUALIFIERS inline

#define TWOPOW53_INV_DOUBLE (1.1102230246251565e-16)

#define TWOPOW32_INV_FLOAT (2.3283064e-10f)



typedef std::uint32_t uint32;

typedef std::uint64_t uint64;



QUALIFIERS __m128i aesni1xm128i(const __m128i & in, const __m128i & k) {

    __m128i x = _mm_xor_si128(k, in);

    x = _mm_aesenc_si128(x, k);     // 1

    x = _mm_aesenc_si128(x, k);     // 2

    x = _mm_aesenc_si128(x, k);     // 3

    x = _mm_aesenc_si128(x, k);     // 4

    x = _mm_aesenc_si128(x, k);     // 5

    x = _mm_aesenc_si128(x, k);     // 6

    x = _mm_aesenc_si128(x, k);     // 7

    x = _mm_aesenc_si128(x, k);     // 8

    x = _mm_aesenc_si128(x, k);     // 9

    x = _mm_aesenclast_si128(x, k); // 10

    return x;

}



QUALIFIERS __m128 _my_cvtepu32_ps(const __m128i v)

{

#ifdef __AVX512VL__

    return _mm_cvtepu32_ps(v);

#else

    __m128i v2 = _mm_srli_epi32(v, 1);

    __m128i v1 = _mm_and_si128(v, _mm_set1_epi32(1));

    __m128 v2f = _mm_cvtepi32_ps(v2);

    __m128 v1f = _mm_cvtepi32_ps(v1);

    return _mm_add_ps(_mm_add_ps(v2f, v2f), v1f);

#endif

}



#if !defined(__AVX512VL__) && defined(__GNUC__) && __GNUC__ >= 5

__attribute__((optimize("no-associative-math")))

#endif

QUALIFIERS __m128d _my_cvtepu64_pd(const __m128i x)

{

#ifdef __AVX512VL__

    return _mm_cvtepu64_pd(x);

#else

    __m128i xH = _mm_srli_epi64(x, 32);

    xH = _mm_or_si128(xH, _mm_castpd_si128(_mm_set1_pd(19342813113834066795298816.)));          //  2^84

    __m128i xL = _mm_blend_epi16(x, _mm_castpd_si128(_mm_set1_pd(0x0010000000000000)), 0xcc);   //  2^52

    __m128d f = _mm_sub_pd(_mm_castsi128_pd(xH), _mm_set1_pd(19342813118337666422669312.));     //  2^84 + 2^52

    return _mm_add_pd(f, _mm_castsi128_pd(xL));

#endif

}





QUALIFIERS void aesni_double2(uint32 ctr0, uint32 ctr1, uint32 ctr2, uint32 ctr3,

                              uint32 key0, uint32 key1, uint32 key2, uint32 key3,

                              double & rnd1, double & rnd2)

{

    // pack input and call AES

    __m128i c128 = _mm_set_epi32(ctr3, ctr2, ctr1, ctr0);

    __m128i k128 = _mm_set_epi32(key3, key2, key1, key0);

    c128 = aesni1xm128i(c128, k128);



    // convert 32 to 64 bit and put 0th and 2nd element into x, 1st and 3rd element into y

    __m128i x = _mm_and_si128(c128, _mm_set_epi32(0, 0xffffffff, 0, 0xffffffff));

    __m128i y = _mm_and_si128(c128, _mm_set_epi32(0xffffffff, 0, 0xffffffff, 0));

    y = _mm_srli_si128(y, 4);



    // calculate z = x ^ y << (53 - 32))

    __m128i z = _mm_sll_epi64(y, _mm_set1_epi64x(53 - 32));

    z = _mm_xor_si128(x, z);



    // convert uint64 to double

    __m128d rs = _my_cvtepu64_pd(z);

    // calculate rs * TWOPOW53_INV_DOUBLE + (TWOPOW53_INV_DOUBLE/2.0)

#ifdef __FMA__

    rs = _mm_fmadd_pd(rs, _mm_set1_pd(TWOPOW53_INV_DOUBLE), _mm_set1_pd(TWOPOW53_INV_DOUBLE/2.0));

#else

    rs = _mm_mul_pd(rs, _mm_set1_pd(TWOPOW53_INV_DOUBLE));

    rs = _mm_add_pd(rs, _mm_set1_pd(TWOPOW53_INV_DOUBLE/2.0));

#endif



    // store result

    alignas(16) double rr[2];

    _mm_store_pd(rr, rs);

    rnd1 = rr[0];

    rnd2 = rr[1];

}





QUALIFIERS void aesni_float4(uint32 ctr0, uint32 ctr1, uint32 ctr2, uint32 ctr3,

                             uint32 key0, uint32 key1, uint32 key2, uint32 key3,

                             float & rnd1, float & rnd2, float & rnd3, float & rnd4)

{

    // pack input and call AES

    __m128i c128 = _mm_set_epi32(ctr3, ctr2, ctr1, ctr0);

    __m128i k128 = _mm_set_epi32(key3, key2, key1, key0);

    c128 = aesni1xm128i(c128, k128);



    // convert uint32 to float

    __m128 rs = _my_cvtepu32_ps(c128);

    // calculate rs * TWOPOW32_INV_FLOAT + (TWOPOW32_INV_FLOAT/2.0f)

#ifdef __FMA__

    rs = _mm_fmadd_ps(rs, _mm_set1_ps(TWOPOW32_INV_FLOAT), _mm_set1_ps(TWOPOW32_INV_FLOAT/2.0f));

#else

    rs = _mm_mul_ps(rs, _mm_set1_ps(TWOPOW32_INV_FLOAT));

    rs = _mm_add_ps(rs, _mm_set1_ps(TWOPOW32_INV_FLOAT/2.0f));

#endif



    // store result

    alignas(16) float r[4];

    _mm_store_ps(r, rs);

    rnd1 = r[0];

    rnd2 = r[1];

    rnd3 = r[2];

    rnd4 = r[3];

}

pystencils/include/opencl_stdint.h

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#ifndef OPENCL_STDINT

#define OPENCL_STDINT



typedef unsigned int      uint_t;



typedef signed char       int8_t;

typedef signed short      int16_t;

typedef signed int        int32_t;

typedef signed long int   int64_t;

typedef unsigned char     uint8_t;

typedef unsigned short    uint16_t;

typedef unsigned int      uint32_t;

typedef unsigned long int uint64_t;



#endif

pystencils/include/philox_rand.h

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#include <cstdint>



#ifndef __CUDA_ARCH__

#define QUALIFIERS inline

#else

#define QUALIFIERS static __forceinline__ __device__

#endif



#define PHILOX_W32_0   (0x9E3779B9)

#define PHILOX_W32_1   (0xBB67AE85)

#define PHILOX_M4x32_0 (0xD2511F53)

#define PHILOX_M4x32_1 (0xCD9E8D57)

#define TWOPOW53_INV_DOUBLE (1.1102230246251565e-16)

#define TWOPOW32_INV_FLOAT (2.3283064e-10f)



typedef std::uint32_t uint32;

typedef std::uint64_t uint64;





QUALIFIERS uint32 mulhilo32(uint32 a, uint32 b, uint32* hip)

{

#ifndef __CUDA_ARCH__

    // host code

    uint64 product = ((uint64)a) * ((uint64)b);

    *hip = product >> 32;

    return (uint32)product;

#else

    // device code

    *hip = __umulhi(a,b);

    return a*b;

#endif

}



QUALIFIERS void _philox4x32round(uint32* ctr, uint32* key)

{

    uint32 hi0;

    uint32 hi1;

    uint32 lo0 = mulhilo32(PHILOX_M4x32_0, ctr[0], &hi0);

    uint32 lo1 = mulhilo32(PHILOX_M4x32_1, ctr[2], &hi1);



    ctr[0] = hi1^ctr[1]^key[0];

    ctr[1] = lo1;

    ctr[2] = hi0^ctr[3]^key[1];

    ctr[3] = lo0;

}



QUALIFIERS void _philox4x32bumpkey(uint32* key)

{

    key[0] += PHILOX_W32_0;

    key[1] += PHILOX_W32_1;

}



QUALIFIERS double _uniform_double_hq(uint32 x, uint32 y)

{

    uint64 z = (uint64)x ^ ((uint64)y << (53 - 32));

    return z * TWOPOW53_INV_DOUBLE + (TWOPOW53_INV_DOUBLE/2.0);

}





QUALIFIERS void philox_double2(uint32 ctr0, uint32 ctr1, uint32 ctr2, uint32 ctr3,

                               uint32 key0, uint32 key1, double & rnd1, double & rnd2)

{

    uint32 key[2] = {key0, key1};

    uint32 ctr[4] = {ctr0, ctr1, ctr2, ctr3};

    _philox4x32round(ctr, key);                           // 1

    _philox4x32bumpkey(key); _philox4x32round(ctr, key);  // 2

    _philox4x32bumpkey(key); _philox4x32round(ctr, key);  // 3

    _philox4x32bumpkey(key); _philox4x32round(ctr, key);  // 4

    _philox4x32bumpkey(key); _philox4x32round(ctr, key);  // 5

    _philox4x32bumpkey(key); _philox4x32round(ctr, key);  // 6

    _philox4x32bumpkey(key); _philox4x32round(ctr, key);  // 7

    _philox4x32bumpkey(key); _philox4x32round(ctr, key);  // 8

    _philox4x32bumpkey(key); _philox4x32round(ctr, key);  // 9

    _philox4x32bumpkey(key); _philox4x32round(ctr, key);  // 10



    rnd1 = _uniform_double_hq(ctr[0], ctr[1]);

    rnd2 = _uniform_double_hq(ctr[2], ctr[3]);

}







QUALIFIERS void philox_float4(uint32 ctr0, uint32 ctr1, uint32 ctr2, uint32 ctr3,

                              uint32 key0, uint32 key1,

                              float & rnd1, float & rnd2, float & rnd3, float & rnd4)

{

    uint32 key[2] = {key0, key1};

    uint32 ctr[4] = {ctr0, ctr1, ctr2, ctr3};

    _philox4x32round(ctr, key);                           // 1

    _philox4x32bumpkey(key); _philox4x32round(ctr, key);  // 2

    _philox4x32bumpkey(key); _philox4x32round(ctr, key);  // 3

    _philox4x32bumpkey(key); _philox4x32round(ctr, key);  // 4

    _philox4x32bumpkey(key); _philox4x32round(ctr, key);  // 5

    _philox4x32bumpkey(key); _philox4x32round(ctr, key);  // 6

    _philox4x32bumpkey(key); _philox4x32round(ctr, key);  // 7

    _philox4x32bumpkey(key); _philox4x32round(ctr, key);  // 8

    _philox4x32bumpkey(key); _philox4x32round(ctr, key);  // 9

    _philox4x32bumpkey(key); _philox4x32round(ctr, key);  // 10



    rnd1 = ctr[0] * TWOPOW32_INV_FLOAT + (TWOPOW32_INV_FLOAT/2.0f);

    rnd2 = ctr[1] * TWOPOW32_INV_FLOAT + (TWOPOW32_INV_FLOAT/2.0f);

    rnd3 = ctr[2] * TWOPOW32_INV_FLOAT + (TWOPOW32_INV_FLOAT/2.0f);

    rnd4 = ctr[3] * TWOPOW32_INV_FLOAT + (TWOPOW32_INV_FLOAT/2.0f);

}
 
 No newline at end of file

pystencils/kerncraft_coupling/__init__.py

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from .generate_benchmark import generate_benchmark, run_c_benchmark

from .kerncraft_interface import KerncraftParameters, PyStencilsKerncraftKernel



__all__ = ['PyStencilsKerncraftKernel', 'KerncraftParameters', 'generate_benchmark', 'run_c_benchmark']

pystencils/llvm/__init__.py

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from .kernelcreation import create_kernel

from .llvmjit import make_python_function



__all__ = ['create_kernel', 'make_python_function']

pystencils/llvm/control_flow.py

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import llvmlite.ir as ir





class Loop(object):

    def __init__(self, builder, start_val, stop_val, step_val=1, loop_name='loop', phi_name="_phi"):

        self.builder = builder

        self.start_val = start_val

        self.stop_val = stop_val

        self.step_val = step_val

        self.loop_name = loop_name

        self.phi_name = phi_name



    def __enter__(self):

        self.loop_end, self.after, phi = self._for_loop(self.start_val, self.stop_val, self.step_val, self.loop_name,

                                                        self.phi_name)

        return phi



    def _for_loop(self, start_val, stop_val, step_val, loop_name, phi_name):

        # TODO size of int??? unisgned???

        integer = ir.IntType(64)



        # Loop block

        pre_loop_bb = self.builder.block

        loop_bb = self.builder.append_basic_block(name='loop_' + loop_name)



        self.builder.branch(loop_bb)



        # Insert an explicit fall through from the current block to loop_bb

        self.builder.position_at_start(loop_bb)



        # Add phi

        phi = self.builder.phi(integer, name=phi_name)

        phi.add_incoming(start_val, pre_loop_bb)



        loop_end_bb = self.builder.append_basic_block(name=loop_name + "_end_bb")

        self.builder.position_at_start(loop_end_bb)



        next_var = self.builder.add(phi, step_val, name=loop_name + '_next_it')

        cond = self.builder.icmp_unsigned('<', next_var, stop_val, name=loop_name + "_cond")



        after_bb = self.builder.append_basic_block(name=loop_name + "_after_bb")



        self.builder.cbranch(cond, loop_bb, after_bb)

        phi.add_incoming(next_var, loop_end_bb)



        self.builder.position_at_end(loop_bb)



        return loop_end_bb, after_bb, phi



    def __exit__(self, exc_type, exc, exc_tb):

        self.builder.branch(self.loop_end)

        self.builder.position_at_end(self.after)

pystencils/llvm/kernelcreation.py

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from pystencils.llvm.llvmjit import make_python_function

from pystencils.transformations import insert_casts





def create_kernel(assignments, function_name="kernel", type_info=None, split_groups=(),

                  iteration_slice=None, ghost_layers=None, target='cpu'):

    """

    Creates an abstract syntax tree for a kernel function, by taking a list of update rules.



    Loops are created according to the field accesses in the equations.



    Args:

    assignments: list of sympy equations, containing accesses to :class:`pystencils.field.Field`.

                 Defining the update rules of the kernel

    function_name: name of the generated function - only important if generated code is written out

                   type_info: a map from symbol name to a C type specifier. If not specified all symbols are assumed to

                   be of type 'double' except symbols which occur on the left hand side of equations where the

                   right hand side is a sympy Boolean which are assumed to be 'bool' .

    split_groups: Specification on how to split up inner loop into multiple loops. For details see

                  transformation :func:`pystencils.transformation.split_inner_loop`

    iteration_slice: if not None, iteration is done only over this slice of the field

    ghost_layers: a sequence of pairs for each coordinate with lower and upper nr of ghost layers

                 if None, the number of ghost layers is determined automatically and assumed to be equal for a

                 all dimensions



    :return: :class:`pystencils.ast.KernelFunction` node

    """

    if target == 'cpu':

        from pystencils.cpu import create_kernel

        code = create_kernel(assignments, function_name, type_info, split_groups, iteration_slice, ghost_layers)

        code._backend = 'llvm'

    elif target == 'gpu':

        from pystencils.gpucuda.kernelcreation import create_cuda_kernel

        code = create_cuda_kernel(assignments,

                                  function_name,

                                  type_info,

                                  iteration_slice=iteration_slice,

                                  ghost_layers=ghost_layers)

        code._backend = 'llvm_gpu'

    else:

        NotImplementedError()

    code.body = insert_casts(code.body)

    code._compile_function = make_python_function



    return code

pystencils/llvm/llvm.py

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pystencils/sympy_gmpy_bug_workaround.py

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# Disable gmpy backend until this bug is resolved if joblib serialize

# See https://github.com/sympy/sympy/pull/13530

import os

import warnings



os.environ['MPMATH_NOGMPY'] = '1'

try:

    import mpmath.libmp

    # In case the user has imported sympy first, then pystencils

    if mpmath.libmp.BACKEND == 'gmpy':

        warnings.warn("You are using the gmpy backend. You might encounter an error 'argument is not an mpz sympy'. "

                      "This is due to a known bug in sympy/gmpy library. "

                      "To prevent this, import pystencils first then sympy or set the environment variable "

                      "MPMATH_NOGMPY=1")

except ImportError:

    pass



__all__ = []

pystencils_tests/benchmark/main.c

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#include "iacaMarks.h"



int main(int argc, char * argv[]){

	int a = 0;

	for(int i = 0; i < argc+100000; i++){

		IACA_START

		a += i;

	}

	IACA_END

	return a;

}

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#!/usr/bin/env python3



from contextlib import redirect_stdout

import io

from tests.test_quicktests import (

    test_basic_kernel,

    test_basic_blocking_staggered,

    test_basic_vectorization,

)



quick_tests = [

    test_basic_kernel,

    test_basic_blocking_staggered,

    test_basic_vectorization,

]



if __name__ == "__main__":

    print("Running pystencils quicktests")

    for qt in quick_tests:

        print(f"   -> {qt.__name__}")

        with redirect_stdout(io.StringIO()):

            qt()

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