Parallel SRP-PHAT for GPUs

Taewoo Lee, Sukmoon Chang, Dongsuk Yook

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

The steered response power phase transform (SRP-PHAT) is one of the widely used algorithms for sound source localization. Since it must examine a large number of candidate sound source locations, conventional SRP-PHAT approaches may not be used in real time. To overcome this problem, an effort was made previously to parallelize the SRP-PHAT on graphics processing units (GPUs). However, the full capacities of the GPU were not exploited since on-chip memory usage was not addressed. In this paper, we propose GPU-based parallel algorithms of the SRP-PHAT both in the frequency domain and time domain. The proposed methods optimize the memory access patterns of the SRP-PHAT and efficiently use the on-chip memory. As a result, the proposed methods demonstrate a speedup of 1276 times in the frequency domain and 80 times in the time domain compared to CPU-based algorithms, and 1.5 times in the frequency domain and 6 times in the time domain compared to conventional GPU-based methods.

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalComputer Speech and Language
Volume35
DOIs
Publication statusPublished - 2016 Jun 4

Keywords

  • GPUs
  • Sound source localization
  • SRP-PHAT

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Theoretical Computer Science

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