XPS: FULL: DSD: Collaborative Research: Parallelizing and Accelerating Metagenomic Applications

University Of California-Santa Barbara, Santa Barbara CA

Investigators

Abstract

The importance of metagenomics arises from the fact that over 99% of the species yet to be discovered are resistant to cultivation. Unlike single genome sequencing, assembly of a metagenome is intractable and is in large part, an unsolved mystery. Moreover, the advent of high throughput sequencing is fueling rapid generation of enormous metagenomic datasets. There is no available sequenced genome for a majority of the species. There is a need to determine the number of species in a metagenomic dataset as well as the abundance of each of these species. The key steps (Assembly and Clustering) in the metagenomics analysis algorithms are compute-intensive, while the sheer amount of data the algorithms operate on is staggering. The most promising way to tackle the computational challenges is to build special purpose hardware, dedicated solely to suitable algorithms. The main objective of this project is to develop a range of flexible, affordable, parallel, fast hardware-accelerated bioinformatics solutions, using GPGPU, FPGA, and ASIC, for metagenomic analytics to provide an alternative to expensive computer clusters. Specifically, hardware solutions for metagenomic clustering and assembly will be developed. Several acceleration methodologies, including parallel software mapping and special hardware design, are proposed to explore the parallelism inside the applications and to improve the data access bandwidth in the hardware running bioinformatics applications. The ideas proposed in this work will be evaluated in a multi-pronged manner using a combination of simulation, emulation and prototyping efforts. Further, the PIs will use a combination of commercial tools, collaborator resources and existing internal tools. The research will be conducted in collaboration with industrial partners. Through close collaboration with several industry partners, direct transfer of many ideas to industry is enabled. The outcome of this research will, therefore, have a direct impact on future bioinformatics application solutions. This project will involve graduate and undergraduate students in all aspects of the research. The PIs will actively integrate the research results from this project into the graduate and undergraduate curricula, and develop new interdisciplinary courses on bioinformatics and computer architecture to train the next generation work-force. Finally, the tools and techniques developed in this research will be made available through web-sites for use by other educators, researchers, and industry practitioners.