PESC -- Parallel Experiment for Sequential Code

TL;DR

This paper introduces PESC, a platform that enables distributed execution of scientific simulations across networked resources using containers, simplifying setup and reducing costs for researchers.

Contribution

The paper presents a novel container-based platform for distributed scientific simulations that abstracts infrastructure complexity and supports multiple programming languages.

Findings

Successfully ran over 1000 simulation runs with varied parameters.

Demonstrated platform's ability to facilitate complex, resource-intensive experiments.

Reduced infrastructure complexity for scientific computing.

Abstract

The need for computational resources grows as computational algorithms gain popularity in different sectors of the scientific community. This search has stimulated the development of several cloud platforms that abstract the complexity of computational infrastructure. 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 network using containers that abstracts 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 (like Python, Java, C, 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.