HILO: Quasi Diffusion Accelerated Monte Carlo on Hybrid Architectures

The Boltzmann transport equation provides high fidelity simulation of a diverse range of kinetic systems.
June 29, 2013
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The Boltzmann transport equation provides high fidelity simulation of a diverse range of kinetic systems.

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HILO:  Quasi Diffusion Accelerated Monte Carlo on Hybrid Architectures

The Boltzmann transport equation provides high fidelity simulation of a diverse range of kinetic systems. Classical methods to solve the equation are computationally and data intensive. Existing stochastic solutions to the Boltzmann equation map well to traditional large multi-core and many-node architectures but suffer performance degradations on graphics processing units (GPUs) due to heavy thread divergence. We present a novel algorithm, Quasi-Diffusion Accelerated Monte Carlo (QDA-MC), which improves performance on heterogeneous CPU/GPU architectures.

An equally important aspect of this project is the joint development of QDA-MC through collaboration between the computational and computer science communities. This collaboration identified computational platforms and features that best suit the algorithm, and influenced algorithmic details which improve its computational efficiency. In addition to algorithm details and implementation results, we present the code optimizations and the design decisions that were critical to the co-design process.

Licensing Status:

Available for Express Licensing(?). This software is open source.

To download, please visit github. For more information, contact Software@lanl.gov.

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