Efficient Computation of RNA Partition Functions Using McCaskill’s Algorithm

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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1. This work was supported, in part, by the National Science Foundation under award 1447711.

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2. Track 2: Computer Science & Systems

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3. Technical Session: 13th Workshop on Computer Aspects of Numerical Algorithms

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4. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).