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Parallel Sparse and Conventional FFTs, Applications and Implementation

The fast Fourier Transform (FFT) is an algorithm used in a wide variety of applications, yet does not make optimal use of many current and emerging platforms such as many-core processors, GPUs, and distributed-memory systems. Hardware utilization performance on its own does not, however, imply optimal problem-solving. The purpose of this minisymposium is to enable an exchange of information between people working on FFT algorithms such as sparse and conventional FFTs, to those working on FFT implementations, in particular for parallel hardware.

Conference page.

Session 1.

Session 2.

Speaker Affiliation
Franz Fanchetti Carnegie Mellon University, USA
Andrew Canning Lawrence Berkeley National Laboratory, USA
Dmitry Pekurovsky University of California San Diego, USA
Daisuke Takahashi University of Tsukuba, Japan
Samar Aseeri King Abdullah University of Science and Technology (KAUST), Saudi Arabia
Lisandro Dalcin King Abdullah University of Science and Technology (KAUST), Saudi Arabia
John Bowman University of Alberta, Canada
Malcolm Roberts AMD, Canada