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A GPU accelerated RNA-RNA interaction program

dc.contributor.authorGildemaster, Brandon, author
dc.contributor.authorRajopadhye, Sanjay, advisor
dc.contributor.authorChitsaz, Hamidreza, committee member
dc.contributor.authorAbdo, Zaid, committee member
dc.description.abstractRNA-RNA interaction (RRI) is important in processes like gene regulation, and is known to play roles in diseases including cancer and Alzheimer's. Large RRI computations run for days, weeks or even months, because the algorithms have time and space complexity of, respectively, O(N3M3) and O(N2M2), for sequences length N and M, and there is a need for high-throughput RRI tools. GPU parallelization of such algorithms is a challenge. We first show that the most computationally expensive part of base pair maximization (BPM) algorithms comprises O(N3) instances of upper banded tropical matrix products. We develop the first GPU library for this attaining close to theoretical machine peak (TMP). We next optimize other (fifth degree polynomial) terms in the computation and develop the first GPU implementation of the complete BPMax algorithm. We attain 12% of GPU TMP, a significant speedup over the original parallel CPU implementation, which attains less than 1% of CPU TMP. We also perform a large scale study of three small viral RNAs, hypothesized to be relevant to COVID-19.
dc.format.mediumborn digital
dc.format.mediummasters theses
dc.publisherColorado State University. Libraries
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dc.titleA GPU accelerated RNA-RNA interaction program
dcterms.rights.dplaThis Item is protected by copyright and/or related rights ( You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). Science State University of Science (M.S.)


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