Scalable parallelization strategies to accelerate NuFFT data translation on multicores

Yuanrui Zhang, Jun Liu, Emre Kultursay, Mahmut Kandemir, Nikos Pitsianis, Xiaobai Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationEuro-Par 2010 Parallel Processing - 16th International Euro-Par Conference, Proceedings
Pages125-136
Number of pages12
EditionPART 2
DOIs
StatePublished - Nov 19 2010
Event16th International Euro-Par Conference on Parallel Processing, Euro-Par 2010 - Ischia, Italy
Duration: Aug 31 2010Sep 3 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6272 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other16th International Euro-Par Conference on Parallel Processing, Euro-Par 2010
CountryItaly
CityIschia
Period8/31/109/3/10

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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    Zhang, Y., Liu, J., Kultursay, E., Kandemir, M., Pitsianis, N., & Sun, X. (2010). Scalable parallelization strategies to accelerate NuFFT data translation on multicores. In Euro-Par 2010 Parallel Processing - 16th International Euro-Par Conference, Proceedings (PART 2 ed., pp. 125-136). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6272 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-15291-7_13