Coordinated Science Laboratory, University of Illinois at Urbana-Champaign
Abstract
Technological advances in genomic analyses and computing sciences has led to a burst in genomics data. With those advances, there has also been parallel growth in dedicated accelerators for specific genomic analyses. However, biologists are in need of a reconfigurable machine that can allow them to perform multiple analyses without needing to go for dedicated compute platforms for each analysis. This work addresses the first steps in the design of such a reconfigurable machine. We hypothesize that this machine design can consist of some accelerators of computations common across various genomic analyses. This work studies a subset of genomic analyses and identifies such core computations. We further investigate the possibility of further accelerating through a deeper analysis of the computation primitives.National Science Foundation (NSF CNS 13-37732); Infosys; IBM Faculty Award; Office of the Vice Chancellor for Research, University of Illinois at Urbana-ChampaignOpe
