Unified Code Generation for the Parallel Computation of Pairwise Interactions using Partial Evaluation

Schmitt J, Köstler H, Eitzinger J, Membarth R (2018)


Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2018

Pages Range: 17-24

Conference Proceedings Title: Proceedings of the 17th International Symposium on Parallel and Distributed Computing (ISPDC)

Event location: Geneva CH

ISBN: 978-1-5386-5330-2

URI: https://ieeexplore.ieee.org/document/8452015/

DOI: 10.1109/ISPDC2018.2018.00012

Abstract

The evaluation of pairwise interactions is fundamental for the simulation of most molecular processes. Their efficient computation is therefore crucial for the overall performance of these simulations on modern computer architectures. We show how code for the computation of pairwise interactions on parallel and heterogeneous platforms can be generated from a unified base through partial evaluation of higher-order functions. For this purpose we introduce a complete implementation of the neighbor list algorithm based on the AnyDSL framework, from which we are able to generate executables for both CPU and GPU through compile-time specialization. Furthermore, we discuss the advantages and disadvantages of our approach and compare it with the miniMD simulation package from the Mantevo project, which is implemented in the C++ programming language and uses a similar computational core as the widely used molecular dynamics package LAMMPS. Finally, we assess the performance of our implementation in a number of test cases on modern CPU and GPU hardware.

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APA:

Schmitt, J., Köstler, H., Eitzinger, J., & Membarth, R. (2018). Unified Code Generation for the Parallel Computation of Pairwise Interactions using Partial Evaluation. In IEEE (Eds.), Proceedings of the 17th International Symposium on Parallel and Distributed Computing (ISPDC) (pp. 17-24). Geneva, CH.

MLA:

Schmitt, Jonas, et al. "Unified Code Generation for the Parallel Computation of Pairwise Interactions using Partial Evaluation." Proceedings of the 17th International Symposium on Parallel and Distributed Computing (ISPDC), Geneva Ed. IEEE, 2018. 17-24.

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