An Approach for Parallel Reading in Multiple Sequence Alignment

Ko, Soon-Heum; Gаnchеvа, Vеskа

doi:10.1109/icai50593.2020.9311347

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2022

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“…Figures 8 and 9 can explain the strategy. MPI I/O over a subset of MPI cores can also be used to foster file reading in any parallel MSA data set [11].…”

Section: Implementation Details and Resultsmentioning

confidence: 99%

An Improved Strategy for Task Scheduling in the Parallel Computational Alignment of Multiple Sequences

Ishaq

Khan

Su’ud

et al. 2022

Computational and Mathematical Methods in Medicine

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Task scheduling in parallel multiple sequence alignment (MSA) through improved dynamic programming optimization speeds up alignment processing. The increased importance of multiple matching sequences also needs the utilization of parallel processor systems. This dynamic algorithm proposes improved task scheduling in case of parallel MSA. Specifically, the alignment of several tertiary structured proteins is computationally complex than simple word-based MSA. Parallel task processing is computationally more efficient for protein-structured based superposition. The basic condition for the application of dynamic programming is also fulfilled, because the task scheduling problem has multiple possible solutions or options. Search space reduction for speedy processing of this algorithm is carried out through greedy strategy. Performance in terms of better results is ensured through computationally expensive recursive and iterative greedy approaches. Any optimal scheduling schemes show better performance in heterogeneous resources using CPU or GPU.

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“…Figures 8 and 9 can explain the strategy. MPI I/O over a subset of MPI cores can also be used to foster file reading in any parallel MSA data set [11].…”

Section: Implementation Details and Resultsmentioning

confidence: 99%