Message-passing programming for embedded multicore signal-processing platforms

Shih Hao Hung, Po Hsun Chiu, Chia Heng Tu, Wei Ting Chou, Wen Long Yang

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


Recently, embedded multicore platforms have become popular for signal processing, but software development for such platforms is still very slow. First, parallel programming is more challenging than sequential programming to average programmers. To make the problem worse, software is not portable among the platforms, since each multicore signal-processing platform offers its own programming interface/language. We believe this problem can be relieved by adding the support of a standard message-passing programming to embedded multicore platforms. In particular, we would like to leverage MPI, the most successful message-passing system, which practically enables the development of portable applications to run on many parallel machines. There are technical challenges to support MPI on embedded multicore platforms: the size of the library, architecture issues, and performance issues. This paper identifies and addresses these issues. To enable the reuse of existing MPI programs and make message-passing programming portable and efficient, we designed a light-weight MPI-like message-passing library with a three-layer modular design, where the top two layers are mostly platform-independent, and the bottom layer enables platform-specific optimizations. This approach has allowed us to effectively support message-passing on several popular embedded multicore signal-processing platforms, including the IBM CELL and the ITRI PAC Duo. Our results show that message-passing programming is a viable solution for multicore signal processing applications and may be considered by platform vendors.

Original languageEnglish
Pages (from-to)123-139
Number of pages17
JournalJournal of Signal Processing Systems
Issue number2
Publication statusPublished - 2014 May

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Signal Processing
  • Information Systems
  • Modelling and Simulation
  • Hardware and Architecture

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