pycodegen.
Python Packages for Scientific Code Generation
Stable Packages
pystencils 1.3.x
Describe stencil-based numerical schemes
using symbolic algebra and generate
highly efficient kernels for the latest
CPU and GPU hardware.
lbmpy
Define lattice Boltzmann methods in a
symbolic mathematical framework and
derive highly optimized collision and
boundary handling kernels.
Under Development
pystencils 2.0
The next generation of
pystencils, featuring a
cleaned-up and
consolidated symbolic
toolbox, an improved
type system, and a
brand-new code
generation backend.
pystencils-sfg
Integrate pystencils
with your build system
and embed generated
kernels into C++ HPC
applications of all
scales.
Cite Us
pystencils:
-
Bauer, M., Hötzer, J., Ernst, D., Hammer, J., Seiz, M., Hierl, H., Hönig,
J., Köstler, H., Wellein, G., Nestler, B., & Rüde, U. (2019).
Code generation for massively parallel phase-field simulations.
In Proceedings of the International Conference for High Performance Computing, Networking,
Storage and Analysis.
SC ’19: The International Conference for High Performance Computing, Networking, Storage,
and Analysis.
ACM.
https://doi.org/10.1145/3295500.3356186
lbmpy:
-
Hennig, F., Holzer, M., & Rüde, U. (2023).
Advanced Automatic Code Generation for Multiple Relaxation-Time Lattice Boltzmann Methods.
In SIAM Journal on Scientific Computing (Vol. 45, Issue 4, pp. C233–C254).
Society for Industrial & Applied Mathematics (SIAM).
https://doi.org/10.1137/22m1531348
-
Holzer, M., Bauer, M., Köstler, H., & Rüde, U. (2021).
Highly efficient lattice Boltzmann multiphase simulations of immiscible fluids at high-density ratios on CPUs and GPUs through code generation.
In The International Journal of High Performance Computing Applications (Vol. 35, Issue 4, pp. 413–427). SAGE Publications.
https://doi.org/10.1177/10943420211016525
-
Bauer, M., Köstler, H., & Rüde, U. (2021).
lbmpy: Automatic code generation for efficient parallel lattice Boltzmann methods.
In Journal of Computational Science (Vol. 49, p. 101269). Elsevier BV.
https://doi.org/10.1016/j.jocs.2020.101269