| 000 | 01764naa a2200181 a 4500 | ||
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| 003 | AR-LpUFIB | ||
| 005 | 20250311170419.0 | ||
| 008 | 230201s2011 ag r 000 0 spa d | ||
| 024 | 8 |
_aDIF-M6656 _b6795 _zDIF006019 |
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_aAR-LpUFIB _bspa _cAR-LpUFIB |
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| 100 | 1 | _aRucci, Enzo | |
| 245 | 1 | 0 |
_aDNA sequence alignment : _bhybrid parallel programming on a multicore cluster |
| 300 | _a1 archivo (484,8 KB) | ||
| 500 | _aFormato de archivo: PDF. -- Este documento es producción intelectual de la Facultad de Informática - UNLP (Colección BIPA/Biblioteca) | ||
| 520 | _aDNA sequence alignment is one of the most important operations of computational biology. In 1981, Smith and Waterman developed a method for sequences local alignment. Due to its computational power and memory requirements, various heuristics have been developed to reduce execution time at the expense of a loss of accuracy in the result. This is why heuristics do not ensure that the best alignment is found. For this reason, it is interesting to study how to apply the computer power of different parallel platforms to speed up the sequence alignment process without losing result accuracy. In this article, a new parallelization strategy (HI-M) of Smith-Waterman algorithm on a multi-core cluster is presented, configuring a pipeline with a hybrid communication model. Additionally, a performance analysis is carried out and compared with two previously presented parallel solutions. Finally, experimental results are presented, as well as future research lines. | ||
| 534 | _aRecent advances in computers, communications, applied social science and mathematics : Proceedings of the International Conference on Applied, Numerical and Computational Mathematics (ICANCM | ||
| 942 | _cCP | ||
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_c55801 _d55801 |
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