High-Performance Computation of the Number of Nested RNA Structures with 3D Parallel Tiled Code

Many current bioinformatics algorithms have been implemented in parallel programming code. Some of them have already reached the limits imposed by Amdahl’s law, but many can still be improved. In our paper, we present an approach allowing us to generate a high-performance code for calculating the nu...

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Veröffentlicht in:Eng (Basel, Switzerland) Jg. 4; H. 1; S. 507 - 525
Hauptverfasser: Błaszyński, Piotr, Bielecki, Włodzimierz
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.03.2023
Schlagworte:
Algorithms
Bioinformatics
code parallelization
Codes
Dependence
dynamic programming
Gold
High performance computing
high-performance code
Parallel programming
RNA folding
tiled code generation
ISSN:2673-4117, 2673-4117
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Abstract Many current bioinformatics algorithms have been implemented in parallel programming code. Some of them have already reached the limits imposed by Amdahl’s law, but many can still be improved. In our paper, we present an approach allowing us to generate a high-performance code for calculating the number of RNA pairs. The approach allows us to generate parallel tiled code of the maximal dimension of tiles, which for the discussed algorithm is 3D. Experiments carried out by us on two modern multi-core computers, an Intel(R) Xeon(R) Gold 6326 (2.90 GHz, 2 physical units, 32 cores, 64 threads, 24 MB Cache) and Intel(R) i7(11700KF (3.6 GHz, 8 cores, 16 threads, 16 MB Cache), demonstrate a significant increase in performance and scalability of the generated parallel tiled code. For the Intel(R) Xeon(R) Gold 6326 and Intel(R) i7, target code speedup increases linearly with an increase in the number of threads. An approach presented in the paper to generate target code can be used by programmers to generate target parallel tiled code for other bioinformatics codes whose dependence patterns are similar to those of the code implementing the counting algorithm.
AbstractList Many current bioinformatics algorithms have been implemented in parallel programming code. Some of them have already reached the limits imposed by Amdahl’s law, but many can still be improved. In our paper, we present an approach allowing us to generate a high-performance code for calculating the number of RNA pairs. The approach allows us to generate parallel tiled code of the maximal dimension of tiles, which for the discussed algorithm is 3D. Experiments carried out by us on two modern multi-core computers, an Intel(R) Xeon(R) Gold 6326 (2.90 GHz, 2 physical units, 32 cores, 64 threads, 24 MB Cache) and Intel(R) i7(11700KF (3.6 GHz, 8 cores, 16 threads, 16 MB Cache), demonstrate a significant increase in performance and scalability of the generated parallel tiled code. For the Intel(R) Xeon(R) Gold 6326 and Intel(R) i7, target code speedup increases linearly with an increase in the number of threads. An approach presented in the paper to generate target code can be used by programmers to generate target parallel tiled code for other bioinformatics codes whose dependence patterns are similar to those of the code implementing the counting algorithm.
Author Bielecki, Włodzimierz
Błaszyński, Piotr
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SubjectTerms Algorithms
Bioinformatics
code parallelization
Codes
Dependence
dynamic programming
Gold
High performance computing
high-performance code
Parallel programming
RNA folding
tiled code generation
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Title High-Performance Computation of the Number of Nested RNA Structures with 3D Parallel Tiled Code
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