Using cubie

cubie is a Python library designed to provide an easy entry point for users to perform large-scale batch integration of ivps: from many initial values or with many different parameter sets, or both, cubie don’t care.

Installation

Install cubie using pip:

pip install cubie

Basic Usage

Here’s a simple example of how to use cubie:

import cubie

# Example usage will be added as the API develops
# The library provides GPU-accelerated Monte Carlo simulations
# for parameter estimation in ODE systems

Features

  • Forward simulation of non-stiff and (soon) stiff systems of ODEs

Requirements

  • Python >= 3.8

  • NumPy

  • Numba

  • Numba-CUDA

  • SciPy

  • attrs

Optoinal Dependencies

  • Cupy-cu12x: For pool-based memory management (if you’re doing a lot of consecutive batches of different sizes)

GPU Requirements

cubie requires an NVIDIA GPU with compute capability 6.0 or higher (see nvidia’s documentation for details). The library is designed to leverage the power of CUDA for efficient computation. * Numba-CUDA for GPU kernel compilation

Make sure you have appropriate CUDA drivers installed for your system.