Parallel Software Architecture for Experimental Workflows in Computational Biology on Clouds

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Abstract

Cloud computing opens new possibilities for computational biologists. Given the pay-as-you-go model and the commodity hardware base, new tools for extensive parallelism are needed to make experimentation in the cloud an attractive option. In this paper, we present EasyProt, a parallel message-passing architecture designed for developing experimental workflows in computational biology while harnessing the power of cloud resources. The system exploits parallelism in two ways: by multithreading modular components on virtual machines while respecting data dependencies and by allowing expansion across multiple virtual machines. Components of the system, called elements, are easily configured for efficient modification and testing of workflows during ever-changing experimentation. Though EasyProt, as an abstract cloud programming model, can be extended beyond computational biology, current development brings cloud computing to experimenters in this important discipline who are facing unprecedented data-processing challenges, with a type system designed for proteomics, interactomics and comparative genomics data, and a suite of elements that perform useful analysis tasks on biological data using cloud resources.

Availability: EasyProt is available as a public abstract machine image (AMI) on Amazon EC2 cloud service, with an open source license, registered with manifest easyprot-ami/easyprot.img.manifest.xml.