PESC ‐ Parallel Experience for Sequential Code

ABSTRACT The need for computational resources grows as computational algorithms gain popularity in different sectors of the scientific community. Sequential codes need to be converted to parallel versions to optimize the use of these resources. Maintaining a local infrastructure for the execution of...

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Vydáno v:Concurrency and computation Ročník 37; číslo 12-14
Hlavní autoři: Santos, Henrique C. T., Souza, Luciano S., Carvalho, Jonathan H. A., Ferreira, Tiago A. E.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Hoboken, USA John Wiley & Sons, Inc 25.06.2025
Témata:
container virtualization
desktop grid
distributed computing
parallel programing
sequential code
ISSN:1532-0626, 1532-0634
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Shrnutí:ABSTRACT The need for computational resources grows as computational algorithms gain popularity in different sectors of the scientific community. Sequential codes need to be converted to parallel versions to optimize the use of these resources. Maintaining a local infrastructure for the execution of distributed computing, through desktop grids, for example, has been replaced in favor of cloud platforms that the complexity of these local infrastructures. Unfortunately, the cost of accessing these resources could leave out various studies that could be carried by a simpler infrastructure. In this article, we present a platform for distributing computer simulations on resources available on a local network using container virtualization that s the complexity needed to configure these execution environments and allows any user can benefit from this infrastructure. Simulations could be developed in any programming language (such as Python, Java, C, and R) and with specific execution needs within reach of the scientific community in a general way. We will present results obtained in running simulations that required more than 1000 runs with different initial parameters and various other experiments that benefited from using the platform.
ISSN:1532-0626
1532-0634
DOI:10.1002/cpe.70102