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CBESW: sequence alignment on the Playstation 3.

Wirawan A, Kwoh CK, Hieu NT, Schmidt B - BMC Bioinformatics (2008)

Bottom Line: As a result, the computational power needed by bioinformatics applications is growing exponentially as well.For large datasets, our implementation on the PlayStation 3 provides a significant improvement in running time compared to other implementations such as SSEARCH, Striped Smith-Waterman and CUDA.The results from our experiments demonstrate that the PlayStation 3 console can be used as an efficient low cost computational platform for high performance sequence alignment applications.

View Article: PubMed Central - HTML - PubMed

Affiliation: School of Computer Engineering, Nanyang Technological University, Singapore. adri0004@ntu.edu.sg

ABSTRACT

Background: The exponential growth of available biological data has caused bioinformatics to be rapidly moving towards a data-intensive, computational science. As a result, the computational power needed by bioinformatics applications is growing exponentially as well. The recent emergence of accelerator technologies has made it possible to achieve an excellent improvement in execution time for many bioinformatics applications, compared to current general-purpose platforms. In this paper, we demonstrate how the PlayStation 3, powered by the Cell Broadband Engine, can be used as a computational platform to accelerate the Smith-Waterman algorithm.

Results: For large datasets, our implementation on the PlayStation 3 provides a significant improvement in running time compared to other implementations such as SSEARCH, Striped Smith-Waterman and CUDA. Our implementation achieves a peak performance of up to 3,646 MCUPS.

Conclusion: The results from our experiments demonstrate that the PlayStation 3 console can be used as an efficient low cost computational platform for high performance sequence alignment applications.

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Pseudocode of the Cell BE mapping. Pseudocode of the SPE code for the Cell BE mapping.
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Figure 4: Pseudocode of the Cell BE mapping. Pseudocode of the SPE code for the Cell BE mapping.

Mentions: Figure 3 illustrates the mapping of different stages of SW-based protein sequence database scanning application onto the Cell BE. The PPE starts by reading the query and the database from the respective files and then pre-processes the query sequences such that they are suitable for vector operations. The pre-processed query sequence, together with some context data, is sent to each respective SPEs, which in turn will generate its own query profile. This process is done using DMA transfers, namely mfc_get and mfc_put. Given a database D consisting of /D/ sequences and k SPEs. Each SPE aligns the query sequence to database sequences. Pseudocode of the mapping is illustrated in Figure 4. Scores obtained from those alignments are sorted locally in the SPEs and the b highest scores are sent to the PPE, where they are sorted once again to obtain the b overall highest scores.


CBESW: sequence alignment on the Playstation 3.

Wirawan A, Kwoh CK, Hieu NT, Schmidt B - BMC Bioinformatics (2008)

Pseudocode of the Cell BE mapping. Pseudocode of the SPE code for the Cell BE mapping.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2571991&req=5

Figure 4: Pseudocode of the Cell BE mapping. Pseudocode of the SPE code for the Cell BE mapping.
Mentions: Figure 3 illustrates the mapping of different stages of SW-based protein sequence database scanning application onto the Cell BE. The PPE starts by reading the query and the database from the respective files and then pre-processes the query sequences such that they are suitable for vector operations. The pre-processed query sequence, together with some context data, is sent to each respective SPEs, which in turn will generate its own query profile. This process is done using DMA transfers, namely mfc_get and mfc_put. Given a database D consisting of /D/ sequences and k SPEs. Each SPE aligns the query sequence to database sequences. Pseudocode of the mapping is illustrated in Figure 4. Scores obtained from those alignments are sorted locally in the SPEs and the b highest scores are sent to the PPE, where they are sorted once again to obtain the b overall highest scores.

Bottom Line: As a result, the computational power needed by bioinformatics applications is growing exponentially as well.For large datasets, our implementation on the PlayStation 3 provides a significant improvement in running time compared to other implementations such as SSEARCH, Striped Smith-Waterman and CUDA.The results from our experiments demonstrate that the PlayStation 3 console can be used as an efficient low cost computational platform for high performance sequence alignment applications.

View Article: PubMed Central - HTML - PubMed

Affiliation: School of Computer Engineering, Nanyang Technological University, Singapore. adri0004@ntu.edu.sg

ABSTRACT

Background: The exponential growth of available biological data has caused bioinformatics to be rapidly moving towards a data-intensive, computational science. As a result, the computational power needed by bioinformatics applications is growing exponentially as well. The recent emergence of accelerator technologies has made it possible to achieve an excellent improvement in execution time for many bioinformatics applications, compared to current general-purpose platforms. In this paper, we demonstrate how the PlayStation 3, powered by the Cell Broadband Engine, can be used as a computational platform to accelerate the Smith-Waterman algorithm.

Results: For large datasets, our implementation on the PlayStation 3 provides a significant improvement in running time compared to other implementations such as SSEARCH, Striped Smith-Waterman and CUDA. Our implementation achieves a peak performance of up to 3,646 MCUPS.

Conclusion: The results from our experiments demonstrate that the PlayStation 3 console can be used as an efficient low cost computational platform for high performance sequence alignment applications.

Show MeSH