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

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The importance of metagenomics arises from the fact that over 99% ofthe species yet to be discovered are resistant to cultivation. Unlikesingle genome sequencing, assembly of a metagenome is intractable andis in large part, an unsolved mystery. Moreover, the advent of highthroughput sequencing is fueling rapid generation of enormousmetagenomic datasets. There is no available sequenced genome for amajority of the species. There is a need to determine the number of species ina metagenomic dataset as well as the abundance of each of thesespecies. The key steps (Assembly and Clustering) in the metagenomicsanalysis algorithms are compute-intensive, while the sheer amount ofdata the algorithms operate on is staggering. The most promising wayto tackle the computational challenges is to build special purposehardware, dedicated solely to suitable algorithms.The main objective of this project is to develop a range of flexible,affordable, parallel, fast hardware-accelerated bioinformaticssolutions, using GPGPU, FPGA, and ASIC, for metagenomic analytics to provide an alternative toexpensive computer clusters. Specifically, hardware solutions formetagenomic clustering and assembly will be developed. Severalacceleration methodologies, including parallel software mapping andspecial hardware design, are proposed to explore the parallelisminside the applications and to improve the data access bandwidth inthe hardware running bioinformatics applications. The ideas proposedin this work will be evaluated in a multi-pronged manner using acombination of simulation, emulation and prototyping efforts. Further,the PIs will use a combination of commercial tools, collaboratorresources and existing internal tools. The research will be conducted in collaboration with industrial partners. Through closecollaboration with several industry partners, direct transfer of manyideas to industry is enabled. The outcome of this research will,therefore, have a direct impact on future bioinformatics applicationsolutions. This project will involve graduate and undergraduatestudents in all aspects of the research. The PIs will activelyintegrate the research results from this project into the graduate andundergraduate curricula, and develop new interdisciplinary courses onbioinformatics and computer architecture to train the next generationwork-force. Finally, the tools and techniques developed in thisresearch will be made available through web-sites for use by othereducators, researchers, and industry practitioners.