Abstract

BackgroundAn RNA primary structure, or sequence, is a single strand considered as a chain of nucleotides from the alphabet AUGC (adenine, uracil, guanine, cytosine). The strand can be folded onto itself, i.e., one segment of an RNA sequence might be paired with another segment of the same RNA sequence into a two-dimensional structure composed by a list of complementary base pairs, which are close together with the minimum energy. That list is called RNA’s secondary structure and is predicted by an RNA folding algorithm. RNA secondary structure prediction is a computing-intensive task that lies at the core of search applications in bioinformatics.ResultsWe suggest a space-time tiling approach and apply it to generate parallel cache effective tiled code for RNA folding using Nussinov’s algorithm.ConclusionsParallel tiled code generated with a suggested space-time loop tiling approach outperforms known related codes generated automatically by means of optimizing compilers and codes produced manually. The presented approach enables us to tile all the three loops of Nussinov’s recurrence that is not possible with commonly known tiling techniques. Generated parallel tiled code is scalable regarding to the number of parallel threads – increasing the number of threads reduces code execution time. Defining speed up as the ratio of the time taken to run the original serial program on one thread to the time taken to run the tiled program on P threads, we achieve super-linear speed up (a value of speed up is greater than the number of threads used) for parallel tiled code against the original serial code up to 32 threads and super-linear speed up scalability (increasing speed up with increasing the thread number) up to 8 threads. For one thread used, speed up is about 4.2 achieved on an Intel Xeon machine used for carrying out experiments.

Highlights

  • An Ribonucleic acid (RNA) primary structure, or sequence, is a single strand considered as a chain of nucleotides from the alphabet AUGC

  • The dynamic programming approach to RNA secondary structure prediction relies on the fact that structures can be recursively decomposed into smaller components

  • Nussinov proposed a dynamic programming algorithm for RNA folding in 1978 [1], which maximizes the number of non-crossing matchings between complimentary bases of an RNA sequence of length N

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Summary

Introduction

An RNA primary structure, or sequence, is a single strand considered as a chain of nucleotides from the alphabet AUGC (adenine, uracil, guanine, cytosine). That list is called RNA’s secondary structure and is predicted by an RNA folding algorithm. RNA is typically produced as a single stranded molecule, which folds intramolecularly to form a number of short base-paired stems. This base-paired structure is called the secondary structure of the RNA. The dynamic programming approach to RNA secondary structure prediction relies on the fact that structures can be recursively decomposed into smaller components. Nussinov proposed a dynamic programming algorithm for RNA folding in 1978 [1], which maximizes the number of non-crossing matchings between complimentary bases of an RNA sequence of length N

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