Change search
ReferencesLink to record
Permanent link

Direct link
Accelerating DNA Sequence Analysis using Intel(R) Xeon Phi(TM)
Linnaeus University, Faculty of Technology, Department of Computer Science. (Parallel Computing)
Linnaeus University, Faculty of Technology, Department of Computer Science. (Parallel Computing)
2015 (English)In: 2015 IEEE TRUSTCOM/BIGDATASE/ISPA, IEEE Press, 2015, Vol. 3, 222-227 p.Conference paper (Refereed)
Abstract [en]

Genetic information is increasing exponentially, doubling every 18 months. Analyzing this information within a reasonable amount of time requires parallel computing resources. While considerable research has addressed DNA analysis using GPUs, so far not much attention has been paid to the Intel Xeon Phi coprocessor. In this paper we present an algorithm for large-scale DNA analysis that exploits thread-level and the SIMD parallelism of the Intel Xeon Phi. We evaluate our approach for various numbers of cores and thread allocation affinities in the context of real-world DNA sequences of mouse, cat, dog, chicken, human and turkey. The experimental results on Intel Xeon Phi show speed-ups of up to 10× compared to a sequential implementation running on an Intel Xeon processor E5.

Place, publisher, year, edition, pages
IEEE Press, 2015. Vol. 3, 222-227 p.
National Category
Computer Science
Research subject
Computer and Information Sciences Computer Science, Computer Science
URN: urn:nbn:se:lnu:diva-46198DOI: 10.1109/Trustcom.2015.636ISI: 000380431400031ISBN: 978-1-4673-7951-9OAI: diva2:852873
The 13th IEEE International Symposium on Parallel and Distributed Processing with Applications (IEEE ISPA-15) Helsinki, Finland, 20-22 August, 2015
Available from: 2015-09-10 Created: 2015-09-10 Last updated: 2016-10-06Bibliographically approved

Open Access in DiVA

fulltext(780 kB)9 downloads
File information
File name FULLTEXT01.pdfFile size 780 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Other links

Publisher's full textArXiv

Search in DiVA

By author/editor
Memeti, SuejbPllana, Sabri
By organisation
Department of Computer Science
Computer Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 9 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 22 hits
ReferencesLink to record
Permanent link

Direct link