Parallelizing and optimizing a bioinformatics pairwise sequence alignment algorithm for many-core architecture
► MC64-NW/SW is a very efficient implementation of Smith–Waterman. ► MC64-NW/SW is the fastest pairwise aligner for long sequences in a standalone PC. ► MC64-NW/SW is based on Tile64 many-core SoC technology. ► Many-core SoC programs require fine-tuning to achieve a first-rate performance. ► Many-co...
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| Published in: | Parallel computing Vol. 37; no. 4; pp. 244 - 259 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier B.V
01.04.2011
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| ISSN: | 0167-8191, 1872-7336 |
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| Abstract | ► MC64-NW/SW is a very efficient implementation of Smith–Waterman. ► MC64-NW/SW is the fastest pairwise aligner for long sequences in a standalone PC. ► MC64-NW/SW is based on Tile64 many-core SoC technology. ► Many-core SoC programs require fine-tuning to achieve a first-rate performance. ► Many-core technologies can meet successfully challenging bioinformatics needs.
Current computer engineering evolves at an accelerated pace, with hardware advancing towards new chip multiprocessors (CMP) architectures and with supporting software gearing towards new programming and abstraction paradigms, to obtain the maximum efficiency of the hardware at a low cost. In this context, Tilera Corporation has developed a brand new CMP architecture with 64 cores (tiles) called Tile64, and has launched several Peripheral Component Interconnect Express (PCIe) cards to be used and monitored from a host Personal Computer (PC). These cards may execute parallel applications built in C/C++ and compiled with the Tile-GCC compiler. We have previously demonstrated the usefulness of the Tile64 architecture for bioinformatics [S. Gálvez, D. Díaz, P. Hernández, F.J. Esteban, J.A. Caballero, G. Dorado, Next-generation bioinformatics: using many-core processor architecture to develop a web service for sequence alignment, Bioinformatics, 26 (2010) 683–686]. We have chosen a bioinformatics algorithm to test this many-core Tile64 architecture because of actual bioinformatics challenging needs: data-intensive workloads, space and time-consuming requirements and massive calculation. This algorithm, known as Needleman–Wunsch/Smith–Waterman (NW/SW), obtains an optimal sequence alignment in quadratic time and space cost, yet requires to be optimized to take full advantage of computing parallelization. In this paper we redesign, implement and fine-tune this algorithm, introducing key optimizations and changes that take advantage of specific Tile64 characteristics: RISC architecture, local tile’s cache, length of memory word, shared memory usage, RAM file system, tile’s intercommunication and job selection from a pool. The resulting algorithm – named MC64-NW/SW for Multicore64 Needleman–Wunsch/Smith–Waterman – achieves a gain of ∼1000% when compared with the same algorithm on a ×86 multi-core architecture. As far as we know, our NW/SW implementation is the fastest ever published for a standalone PC when aligning a pair of sequences larger than 20
kb. |
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| AbstractList | Current computer engineering evolves at an accelerated pace, with hardware advancing towards new chip multiprocessors (CMP) architectures and with supporting software gearing towards new programming and abstraction paradigms, to obtain the maximum efficiency of the hardware at a low cost. In this context, Tilera Corporation has developed a brand new CMP architecture with 64 cores (tiles) called Tile64, and has launched several Peripheral Component Interconnect Express (PCIe) cards to be used and monitored from a host Personal Computer (PC). These cards may execute parallel applications built in C/C++ and compiled with the Tile-GCC compiler. We have previously demonstrated the usefulness of the Tile64 architecture for bioinformatics [S. Galvez, D. Diaz, P. Hernandez, F.J. Esteban, J.A. Caballero, G. Dorado, Next-generation bioinformatics: using many-core processor architecture to develop a web service for sequence alignment, Bioinformatics, 26 (2010) 683-686]. We have chosen a bioinformatics algorithm to test this many-core Tile64 architecture because of actual bioinformatics challenging needs: data-intensive workloads, space and time-consuming requirements and massive calculation. This algorithm, known as Needleman-Wunsch/Smith-Waterman (NW/SW), obtains an optimal sequence alignment in quadratic time and space cost, yet requires to be optimized to take full advantage of computing parallelization. In this paper we redesign, implement and fine-tune this algorithm, introducing key optimizations and changes that take advantage of specific Tile64 characteristics: RISC architecture, local tile's cache, length of memory word, shared memory usage, RAM file system, tile's intercommunication and job selection from a pool. The resulting algorithm - named MC64-NW/SW for Multicore64 Needleman-Wunsch/Smith-Waterman - achieves a gain of [inline image]1000% when compared with the same algorithm on a x86 multi-core architecture. As far as we know, our NW/SW implementation is the fastest ever published for a standalone PC when aligning a pair of sequences larger than 20 kb. ► MC64-NW/SW is a very efficient implementation of Smith–Waterman. ► MC64-NW/SW is the fastest pairwise aligner for long sequences in a standalone PC. ► MC64-NW/SW is based on Tile64 many-core SoC technology. ► Many-core SoC programs require fine-tuning to achieve a first-rate performance. ► Many-core technologies can meet successfully challenging bioinformatics needs. Current computer engineering evolves at an accelerated pace, with hardware advancing towards new chip multiprocessors (CMP) architectures and with supporting software gearing towards new programming and abstraction paradigms, to obtain the maximum efficiency of the hardware at a low cost. In this context, Tilera Corporation has developed a brand new CMP architecture with 64 cores (tiles) called Tile64, and has launched several Peripheral Component Interconnect Express (PCIe) cards to be used and monitored from a host Personal Computer (PC). These cards may execute parallel applications built in C/C++ and compiled with the Tile-GCC compiler. We have previously demonstrated the usefulness of the Tile64 architecture for bioinformatics [S. Gálvez, D. Díaz, P. Hernández, F.J. Esteban, J.A. Caballero, G. Dorado, Next-generation bioinformatics: using many-core processor architecture to develop a web service for sequence alignment, Bioinformatics, 26 (2010) 683–686]. We have chosen a bioinformatics algorithm to test this many-core Tile64 architecture because of actual bioinformatics challenging needs: data-intensive workloads, space and time-consuming requirements and massive calculation. This algorithm, known as Needleman–Wunsch/Smith–Waterman (NW/SW), obtains an optimal sequence alignment in quadratic time and space cost, yet requires to be optimized to take full advantage of computing parallelization. In this paper we redesign, implement and fine-tune this algorithm, introducing key optimizations and changes that take advantage of specific Tile64 characteristics: RISC architecture, local tile’s cache, length of memory word, shared memory usage, RAM file system, tile’s intercommunication and job selection from a pool. The resulting algorithm – named MC64-NW/SW for Multicore64 Needleman–Wunsch/Smith–Waterman – achieves a gain of ∼1000% when compared with the same algorithm on a ×86 multi-core architecture. As far as we know, our NW/SW implementation is the fastest ever published for a standalone PC when aligning a pair of sequences larger than 20 kb. |
| Author | Dorado, Gabriel Hernández, Pilar Díaz, David Gálvez, Sergio Caballero, Juan Antonio Esteban, Francisco José |
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| Cites_doi | 10.1109/ISSCC.2008.4523070 10.1145/360825.360861 10.1016/S0022-2836(05)80360-2 10.1073/pnas.85.8.2444 10.1109/MM.2007.4378780 10.1101/gr.089532.108 10.1007/s00453-006-1217-y 10.1002/cpe.1416 10.1002/pro.5560040613 10.1111/j.1467-8659.2007.01012.x 10.1006/geno.1996.0614 10.1109/ASSCC.2007.4425786 10.1016/S0168-9525(00)02024-2 10.1093/bioinformatics/btl582 10.1147/rd.515.0559 10.1093/nar/22.22.4673 10.1016/0888-7543(91)90071-L 10.1016/0022-2836(70)90057-4 10.1073/pnas.0409137102 10.1016/j.parco.2009.05.002 10.1145/165939.165948 10.1016/0001-8708(76)90202-4 10.1016/j.jpdc.2008.05.010 10.1016/j.parco.2008.04.001 10.1109/IPPS.1999.760546 10.1147/rd.494.0589 10.1016/j.jpdc.2007.08.007 10.5753/sbac-pad.2001.22185 10.1147/rd.515.0573 10.1016/0097-3165(74)90050-8 10.1186/1756-0500-2-73 10.1016/0022-2836(81)90087-5 10.1016/0022-2836(82)90398-9 10.1093/bioinformatics/btq017 10.1016/j.parco.2008.12.010 10.1186/1471-2105-9-S2-S10 10.1186/1756-0500-1-61 |
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| Keywords | Smith–Waterman High performance optimization Multithreading Chip multiprocessor architecture Tile64 processor System-on-chip Needleman–Wunsch Multi-core parallelization |
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| SubjectTerms | Algorithms Alignment Architecture Bioinformatics Chip multiprocessor architecture Computation Computer programs High performance optimization Multi-core parallelization Multithreading Needleman–Wunsch Optimization Parallel processing Smith–Waterman System-on-chip Tile64 processor |
| Title | Parallelizing and optimizing a bioinformatics pairwise sequence alignment algorithm for many-core architecture |
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