Original Research ARTICLE
CyNEST: a maintainable Cython-based interface for the NEST simulator
- 1Simulation Laboratory Neuroscience – Bernstein Facility for Simulation and Database Technology, Institute for Advanced Simulation, Jülich Aachen Research Alliance, Jülich Research Center, Jülich, Germany
- 2Faculty of Biology, Albert-Ludwig University of Freiburg, Freiburg im Breisgau, Germany
- 3Institute for Advanced Simulation (IAS-6), Theoretical Neuroscience and Institute of Neuroscience and Medicine (INM-6), Computational and Systems Neuroscience, Jülich Research Center and JARA, Jülich, Germany
- 4Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr-University Bochum, Bochum, Germany
NEST is a simulator for large-scale networks of spiking point neuron models (Gewaltig and Diesmann, 2007). Originally, simulations were controlled via the Simulation Language Interpreter (SLI), a built-in scripting facility implementing a language derived from PostScript (Adobe Systems, Inc., 1999). The introduction of PyNEST (Eppler et al., 2008), the Python interface for NEST, enabled users to control simulations using Python. As the majority of NEST users found PyNEST easier to use and to combine with other applications, it immediately displaced SLI as the default NEST interface. However, developing and maintaining PyNEST has become increasingly difficult over time. This is partly because adding new features requires writing low-level C++ code intermixed with calls to the Python/C API, which is unrewarding. Moreover, the Python/C API evolves with each new version of Python, which results in a proliferation of version-dependent code branches. In this contribution we present the re-implementation of PyNEST in the Cython language, a superset of Python that additionally supports the declaration of C/C++ types for variables and class attributes, and provides a convenient foreign function interface (FFI) for invoking C/C++ routines (Behnel et al., 2011). Code generation via Cython allows the production of smaller and more maintainable bindings, including increased compatibility with all supported Python releases without additional burden for NEST developers. Furthermore, this novel approach opens up the possibility to support alternative implementations of the Python language at no cost given a functional Cython back-end for the corresponding implementation, and also enables cross-compilation of Python bindings for embedded systems and supercomputers alike.
Keywords: Python language, neural simulator, maintainability, technical debt, HPC
Citation: Zaytsev YV and Morrison A (2014) CyNEST: a maintainable Cython-based interface for the NEST simulator. Front. Neuroinform. 8:23. doi: 10.3389/fninf.2014.00023
Received: 21 November 2013; Accepted: 22 February 2014;
Published online: 14 March 2014.
Edited by:Yaroslav O. Halchenko, Dartmouth College, USA
Reviewed by:Mikael Djurfeldt, KTH Royal Institute of Technology, Sweden
Laurent U. Perrinet, Centre National de la Recherche Scientifique, France
Copyright © 2014 Zaytsev and Morrison. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Yury V. Zaytsev, Simulation Laboratory Neuroscience - Bernstein Facility for Simulation and Database Technology, Institute for Advanced Simulation, Jülich Aachen Research Alliance, Jülich Research Center, Jülich Supercomputing Centre, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany e-mail: email@example.com