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Conference Papers Year : 2018

Toward Efficient Many-core Scheduling of Partial Expansion Graphs

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Jean-Pierre Talpin
Thierry Gautier

Abstract

Transformation of synchronous data flow graphs (SDF) into equivalent homogeneous SDF representations has been extensively applied as a pre-processing stage when mapping signal processing algorithms onto parallel platforms. While this transformation helps fully expose task and data parallelism, it also presents several limitations such as an exponential increase in the number of actors and excessive communication overhead. Partial expansion graphs were introduced to address these limitations for multi-core platforms. However, existing solutions are not well-suited to achieve efficient scheduling on many-core architectures. In this article, we develop a new approach that employs cyclo-static data flow techniques to provide a simple but efficient method of coordinating the data production and consumption in the expanded graphs. We demonstrate the advantage of our approach through experiments on real application models.
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Dates and versions

hal-01926955 , version 1 (04-12-2018)

Identifiers

Cite

Hai Nam Tran, Shuvra S Bhattacharyya, Jean-Pierre Talpin, Thierry Gautier. Toward Efficient Many-core Scheduling of Partial Expansion Graphs. SCOPES 2018 - 21st International Workshop on Software and Compilers for Embedded Systems, May 2018, Saint Goar, Germany. pp.1-4, ⟨10.1145/3207719.3207734⟩. ⟨hal-01926955⟩
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