Scalable parallelization strategies to accelerate NuFFT data translation on multicores
Publication
, Journal Article
Zhang, Y; Liu, J; Kultursay, E; Kandemir, M; Pitsianis, N; Sun, X
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
November 19, 2010
The non-uniform FFT (NuFFT) has been widely used in many applications. In this paper, we propose two new scalable parallelization strategies to accelerate the data translation step of the NuFFT on multicore machines. Both schemes employ geometric tiling and binning to exploit data locality, and use recursive partitioning and scheduling with dynamic task allocation to achieve load balancing. The experimental results collected from a commercial multicore machine show that, with the help of our parallelization strategies, the data translation step is no longer the bottleneck in the NuFFT computation, even for large data set sizes, with any input sample distribution. © 2010 Springer-Verlag.
Duke Scholars
Published In
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
DOI
EISSN
1611-3349
ISSN
0302-9743
Publication Date
November 19, 2010
Volume
6272 LNCS
Issue
PART 2
Start / End Page
125 / 136
Related Subject Headings
- Artificial Intelligence & Image Processing
- 46 Information and computing sciences
Citation
APA
Chicago
ICMJE
MLA
NLM
Zhang, Y., Liu, J., Kultursay, E., Kandemir, M., Pitsianis, N., & Sun, X. (2010). Scalable parallelization strategies to accelerate NuFFT data translation on multicores. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6272 LNCS(PART 2), 125–136. https://doi.org/10.1007/978-3-642-15291-7_13
Zhang, Y., J. Liu, E. Kultursay, M. Kandemir, N. Pitsianis, and X. Sun. “Scalable parallelization strategies to accelerate NuFFT data translation on multicores.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6272 LNCS, no. PART 2 (November 19, 2010): 125–36. https://doi.org/10.1007/978-3-642-15291-7_13.
Zhang Y, Liu J, Kultursay E, Kandemir M, Pitsianis N, Sun X. Scalable parallelization strategies to accelerate NuFFT data translation on multicores. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2010 Nov 19;6272 LNCS(PART 2):125–36.
Zhang, Y., et al. “Scalable parallelization strategies to accelerate NuFFT data translation on multicores.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6272 LNCS, no. PART 2, Nov. 2010, pp. 125–36. Scopus, doi:10.1007/978-3-642-15291-7_13.
Zhang Y, Liu J, Kultursay E, Kandemir M, Pitsianis N, Sun X. Scalable parallelization strategies to accelerate NuFFT data translation on multicores. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2010 Nov 19;6272 LNCS(PART 2):125–136.
Published In
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
DOI
EISSN
1611-3349
ISSN
0302-9743
Publication Date
November 19, 2010
Volume
6272 LNCS
Issue
PART 2
Start / End Page
125 / 136
Related Subject Headings
- Artificial Intelligence & Image Processing
- 46 Information and computing sciences