sympy2c: From symbolic expressions to fast C/C++ functions and ODE solvers in Python
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Date
2023-01
Publication Type
Journal Article
ETH Bibliography
yes
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Abstract
Computer algebra systems play an important role in science as they facilitate the development of new theoretical models. The resulting symbolic equations are often implemented in a compiled programming language in order to provide fast and portable codes for practical applications. We describe sympy2c, a new Python package designed to bridge the gap between the symbolic development and the numerical implementation of a theoretical model. sympy2c translates symbolic equations implemented in the SymPy Python package to C/C++ code that is optimized using symbolic transformations. The resulting functions can be conveniently used as an extension module in Python. sympy2c is used within the PyCosmo Python package to solve the Einstein–Boltzmann equations, a large system of ODEs describing the evolution of linear perturbations in the Universe. After reviewing the functionalities and usage of sympy2c, we describe its implementation and optimization strategies. This includes, in particular, a novel approach to generate optimized ODE solvers making use of the sparsity of the symbolic Jacobian matrix. We demonstrate its performance using the Einstein–Boltzmann equations as a test case. sympy2c is general and potentially useful for various areas of computational physics. sympy2c is publicly available at https://cosmology.ethz.ch/research/software-lab/sympy2c.html.
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Publication status
published
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Book title
Journal / series
Volume
42
Pages / Article No.
100666
Publisher
Elsevier
Event
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
code generation; ODE solver; Python; Computer algebra
Organisational unit
03928 - Refregier, Alexandre / Refregier, Alexandre
Notes
Funding
192243 - Cosmological Weak Lensing and Neutral Hydrogen (SNF)