Citation
Harris, LA, Nobile, MS, Pino, JC, Lubbock, ALR, Besozzi, D, Mauri, G, Cazzaniga, P, Lopez, CF (2017). GPU-powered model analysis with PySB/cupSODA. Bioinformatics, 33, 21:3492-3494.
Abstract
A major barrier to the practical utilization of large, complex models of biochemical systems is the lack of open-source computational tools to evaluate model behaviors over high-dimensional parameter spaces. This is due to the high computational expense of performing thousands to millions of model simulations required for statistical analysis. To address this need, we have implemented a user-friendly interface between cupSODA, a GPU-powered kinetic simulator, and PySB, a Python-based modeling and simulation framework. For three example models of varying size, we show that for large numbers of simulations PySB/cupSODA achieves order-of-magnitude speedups relative to a CPU-based ordinary differential equation integrator.
Availability and implementation:
The PySB/cupSODA interface has been integrated into the PySB modeling framework (version 1.4.0), which can be installed from the Python Package Index (PyPI) using a Python package manager such as pip. cupSODA source code and precompiled binaries (Linux, Mac OS/X, Windows) are available at github.com/aresio/cupSODA (requires an Nvidia GPU; developer.nvidia.com/cuda-gpus). Additional information about PySB is available at pysb.org.
Contact:
paolo.cazzaniga@unibg.it or c.lopez@vanderbilt.edu.
Supplementary information:
Supplementary data are available at Bioinformatics online.
https://academic.oup.com/bioinformatics/article/33/21/3492/3896987