Exploiting statically schedulable regions in dataflow programs

Ruirui Gu, Jörn Janneck, Mickaël Raulet, Shuvra S. Bhattacharyya

Research output: Contribution to journalArticlepeer-review

15 Citations (SciVal)

Abstract

Abstract in Undetermined
Dataflow descriptions have been used in
a wide range of Digital Signal Processing (DSP)
applications, such as multi-media processing, and
wireless communications. Among various forms of
dataflow modeling, Synchronous Dataflow (SDF) is
geared towards static scheduling of computational
modules, which improves system performance and
predictability. However, many DSP applications
do not fully conform to the restrictions of SDF
modeling. More general dataflow models, such
as CAL (Eker and Janneck 2003), have been
developed to describe dynamically-structured DSP
applications. Such generalized models can express
dynamically changing functionality, but lose the
powerful static scheduling capabilities provided by
SDF. This paper focuses on the detection of SDF-
like regions in dynamic dataflow descriptions—
in particular, in the generalized specification
framework of CAL. This is an important step for
applying static scheduling techniques within a dynamic
dataflow framework. Our techniques combine the advantages of different dataflow languages and tools,
including CAL (Eker and Janneck 2003), DIF (Hsu
et al. 2005) and CAL2C (Roquier et al. 2008). In
addition to detecting SDF-like regions, we apply
existing SDF scheduling techniques to exploit the
static properties of these regions within enclosing
dynamic dataflow models. Furthermore, we propose
an optimized approach for mapping SDF-like regions
onto parallel processing platforms such as multi-core
processors.
Original languageEnglish
Pages (from-to)129-142
JournalJournal of Signal Processing Systems
Volume63
Issue number1
DOIs
Publication statusPublished - 2011

Subject classification (UKÄ)

  • Computer Science

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