This work aims at distilling a systematic methodology to modernize existing sequential scientific codes with a limited re-designing effort, turning an old codebase into modern code, i.e., parallel and robust code. We propose an automatable methodology to parallelize scientific applications designed with a purely sequential programming mindset, thus possibly using global variables, aliasing, random number generators, and stateful functions. We demonstrate the methodology by way of an astrophysical application, where we model at the same time the kinematic profiles of 30 disk galaxies with a Monte Carlo Markov Chain (MCMC), which is sequential by definition. The parallel code exhibits a 12 times speedup on a 48-core platform.

Practical Parallelization of Scientific Applications

Valentina Cesare;Iacopo Colonnelli;Marco Aldinucci
2020-01-01

Abstract

This work aims at distilling a systematic methodology to modernize existing sequential scientific codes with a limited re-designing effort, turning an old codebase into modern code, i.e., parallel and robust code. We propose an automatable methodology to parallelize scientific applications designed with a purely sequential programming mindset, thus possibly using global variables, aliasing, random number generators, and stateful functions. We demonstrate the methodology by way of an astrophysical application, where we model at the same time the kinematic profiles of 30 disk galaxies with a Monte Carlo Markov Chain (MCMC), which is sequential by definition. The parallel code exhibits a 12 times speedup on a 48-core platform.
2020
Euromicro International Conference on Parallel, Distributed and Network Based Processing
Västerås, Sweden
11-13 March 2020
Proc. of the 28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)
IEEE
376
384
978-1-7281-6582-0
loop parallelism, checkpointing, scientific code, openMP
Valentina Cesare, Iacopo Colonnelli, Marco Aldinucci
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1735377
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