Standard

Comparative Analysis of System-Level Acceleration Techniques in Bioinformatics : A Case Study of Accelerating the Smith-Waterman Algorithm for BWA-MEM. / Houtgast, Ernst; Sima, Vlad; Bertels, Koen; Al-Ars, Zaid.

2018 IEEE 18th International Conference on BioInformatics and BioEngineering (BIBE). ed. / Nikolaos G. Bourbakis; Despina Kavraki. Piscataway, NJ. USA : IEEE, 2018. p. 243-246.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Harvard

Houtgast, E, Sima, V, Bertels, K & Al-Ars, Z 2018, Comparative Analysis of System-Level Acceleration Techniques in Bioinformatics: A Case Study of Accelerating the Smith-Waterman Algorithm for BWA-MEM. in NG Bourbakis & D Kavraki (eds), 2018 IEEE 18th International Conference on BioInformatics and BioEngineering (BIBE). IEEE, Piscataway, NJ. USA, pp. 243-246, 18th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2018, Taiching, Taiwan, Province of China, 29/10/18. https://doi.org/10.1109/BIBE.2018.00053

APA

Houtgast, E., Sima, V., Bertels, K., & Al-Ars, Z. (2018). Comparative Analysis of System-Level Acceleration Techniques in Bioinformatics: A Case Study of Accelerating the Smith-Waterman Algorithm for BWA-MEM. In N. G. Bourbakis, & D. Kavraki (Eds.), 2018 IEEE 18th International Conference on BioInformatics and BioEngineering (BIBE) (pp. 243-246). Piscataway, NJ. USA: IEEE. https://doi.org/10.1109/BIBE.2018.00053

Vancouver

Houtgast E, Sima V, Bertels K, Al-Ars Z. Comparative Analysis of System-Level Acceleration Techniques in Bioinformatics: A Case Study of Accelerating the Smith-Waterman Algorithm for BWA-MEM. In Bourbakis NG, Kavraki D, editors, 2018 IEEE 18th International Conference on BioInformatics and BioEngineering (BIBE). Piscataway, NJ. USA: IEEE. 2018. p. 243-246 https://doi.org/10.1109/BIBE.2018.00053

Author

Houtgast, Ernst ; Sima, Vlad ; Bertels, Koen ; Al-Ars, Zaid. / Comparative Analysis of System-Level Acceleration Techniques in Bioinformatics : A Case Study of Accelerating the Smith-Waterman Algorithm for BWA-MEM. 2018 IEEE 18th International Conference on BioInformatics and BioEngineering (BIBE). editor / Nikolaos G. Bourbakis ; Despina Kavraki. Piscataway, NJ. USA : IEEE, 2018. pp. 243-246

BibTeX

@inproceedings{11c22b0959654a599d545865f7ef4568,
title = "Comparative Analysis of System-Level Acceleration Techniques in Bioinformatics: A Case Study of Accelerating the Smith-Waterman Algorithm for BWA-MEM",
abstract = "Bioinformatics workloads are characterized by huge data sets and complex algorithms, requiring enormous data processing and making high performance heterogeneous computation platforms such as FPGAs and GPUs highly relevant. We compare three accelerated implementations of the widely used BWA-MEM genomic mapping tool as a case study on design-time optimization for heterogeneous architectures: BWA-MEM-CUDA, BWA-MEM-OpenCL, and BWA-MEMVHDL, each using an optimized Smith-Waterman algorithm implementation. Optimization of design-time is important because of the significant development effort of such implementations: BWA-MEM-CUDA and BWA-MEM-OpenCL require 5-7x more lines of code to express the Smith-Waterman algorithm, while BWA-MEM-VHDL requires more than 40x as many lines of code. Similar differences hold for required implementation time, ranging from one month for BWA-MEMOpenCL to six months for BWA-MEM-VHDL. The advantages and disadvantages of each implementation are described using both quantitative and qualitative metrics, and recommendations are given for future algorithm implementations.",
keywords = "Graphics processing units, Field programmable gate arrays, Kernel, Acceleration, Hardware, instruction sets, Bioinformatics",
author = "Ernst Houtgast and Vlad Sima and Koen Bertels and Zaid Al-Ars",
year = "2018",
doi = "10.1109/BIBE.2018.00053",
language = "English",
isbn = "978-1-5386-5043-1",
pages = "243--246",
editor = "Bourbakis, {Nikolaos G. } and Kavraki, {Despina }",
booktitle = "2018 IEEE 18th International Conference on BioInformatics and BioEngineering (BIBE)",
publisher = "IEEE",
address = "United States",

}

RIS

TY - GEN

T1 - Comparative Analysis of System-Level Acceleration Techniques in Bioinformatics

T2 - A Case Study of Accelerating the Smith-Waterman Algorithm for BWA-MEM

AU - Houtgast, Ernst

AU - Sima, Vlad

AU - Bertels, Koen

AU - Al-Ars, Zaid

PY - 2018

Y1 - 2018

N2 - Bioinformatics workloads are characterized by huge data sets and complex algorithms, requiring enormous data processing and making high performance heterogeneous computation platforms such as FPGAs and GPUs highly relevant. We compare three accelerated implementations of the widely used BWA-MEM genomic mapping tool as a case study on design-time optimization for heterogeneous architectures: BWA-MEM-CUDA, BWA-MEM-OpenCL, and BWA-MEMVHDL, each using an optimized Smith-Waterman algorithm implementation. Optimization of design-time is important because of the significant development effort of such implementations: BWA-MEM-CUDA and BWA-MEM-OpenCL require 5-7x more lines of code to express the Smith-Waterman algorithm, while BWA-MEM-VHDL requires more than 40x as many lines of code. Similar differences hold for required implementation time, ranging from one month for BWA-MEMOpenCL to six months for BWA-MEM-VHDL. The advantages and disadvantages of each implementation are described using both quantitative and qualitative metrics, and recommendations are given for future algorithm implementations.

AB - Bioinformatics workloads are characterized by huge data sets and complex algorithms, requiring enormous data processing and making high performance heterogeneous computation platforms such as FPGAs and GPUs highly relevant. We compare three accelerated implementations of the widely used BWA-MEM genomic mapping tool as a case study on design-time optimization for heterogeneous architectures: BWA-MEM-CUDA, BWA-MEM-OpenCL, and BWA-MEMVHDL, each using an optimized Smith-Waterman algorithm implementation. Optimization of design-time is important because of the significant development effort of such implementations: BWA-MEM-CUDA and BWA-MEM-OpenCL require 5-7x more lines of code to express the Smith-Waterman algorithm, while BWA-MEM-VHDL requires more than 40x as many lines of code. Similar differences hold for required implementation time, ranging from one month for BWA-MEMOpenCL to six months for BWA-MEM-VHDL. The advantages and disadvantages of each implementation are described using both quantitative and qualitative metrics, and recommendations are given for future algorithm implementations.

KW - Graphics processing units

KW - Field programmable gate arrays

KW - Kernel

KW - Acceleration

KW - Hardware

KW - instruction sets

KW - Bioinformatics

UR - http://ShowEdit http://www.scopus.com/inward/record.url?scp=85059608860&partnerID=8YFLogxK

U2 - 10.1109/BIBE.2018.00053

DO - 10.1109/BIBE.2018.00053

M3 - Conference contribution

SN - 978-1-5386-5043-1

SP - 243

EP - 246

BT - 2018 IEEE 18th International Conference on BioInformatics and BioEngineering (BIBE)

A2 - Bourbakis, Nikolaos G.

A2 - Kavraki, Despina

PB - IEEE

CY - Piscataway, NJ. USA

ER -

ID: 47895522