Efficient Computation of RNA Partition Functions Using McCaskill’s Algorithm
Chunchun Zhao, Sartaj Sahni
DOI: http://dx.doi.org/10.15439/2020F85
Citation: Proceedings of the 2020 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 21, pages 449–452 (2020)
Abstract. We develop efficient single- and multi-core algorithms to compute partition functions for RNA sequences. Our algorithms, which are based on McCaskill's algorithm, are benchmarked against state-of-the-art fast algorithms obtained using the parallelizing source-to-source compilers PLUTO and TRACO. On our Intel I9 computational platform, our best single core algorithm takes up to 81.2\% less time than the single core algorithm resulting from PLUTO, which is faster than that obtained from TRACO. Our best multi-core algorithm takes up to 84.7\% less time than the multi-core algorithm obtained using TRACO when run with 20 threads (our I9 has 10 cores and supports hyperthreading); the TRACO multi-core algorithm is faster than the PLUTO one.
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