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clODE is an efficient computational tool designed for parallel solving of ordinary differential equation (ODE) ensembles using OpenCL. It lets users define their ODE system and the ensemble of parameter sets and initial conditions in Python. By leveraging OpenCL, significant speedups can be obtained for this inherently parallel problem on any CPU, GPU, or other device with OpenCL support. Two primary modes of simulation are supported:
clODE offers flexibility in simulator deployment across different hardware, allowing, for example, the FeatureSimulator to operate on a GPU while the TrajectorySimulator runs on a CPU.
Developed in C++ and OpenCL, clODE is accessible for direct use in C++ applications or through a Python interface. The library compiles with bazel and bazelisk, and works on Linux, Windows, and MacOS platforms.
See installation for instructions on how to install CLODE.
See Getting Started for an example of clODE usage.
The source code is available on GitHub.
FAQs
A Python package for solving ordinary differential equations on the GPU using OpenCL
We found that clode demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
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