Gridlan: a Multi-purpose Local Grid Computing Framework

TL;DR

Gridlan is a flexible, multi-purpose local grid computing framework that leverages underused workstations with virtual machines, enabling efficient parallel computations while integrating with existing cluster management tools.

Contribution

It introduces a novel framework combining grid and cluster features, allowing seamless job dispatch on virtualized workstations using existing software.

Findings

Suitable for embarrassingly parallel tasks

Integrates with existing cluster software like Torque

Demonstrates effective computational performance

Abstract

In scientific computing, more computational power generally implies faster and possibly more detailed results. The goal of this study was to develop a framework to submit computational jobs to powerful workstations underused by nonintensive tasks. This is achieved by using a virtual machine in each of these workstations, where the computations are done. This group of virtual machines is called the Gridlan. The Gridlan framework is intermediate between the cluster and grid computing paradigms. The Gridlan is able to profit from existing cluster software tools, such as resource managers like Torque, so a user with previous experience in cluster operation can dispatch jobs seamlessly. A benchmark test of the Gridlan implementation shows the system's suitability for computational tasks, principally in embarrassingly parallel computations.