Journal of Low Power Electronics and Applications (Nov 2020)

Hybrid Application Mapping for Composable Many-Core Systems: Overview and Future Perspective

  • Behnaz Pourmohseni,
  • Michael Glaß,
  • Jörg Henkel,
  • Heba Khdr,
  • Martin Rapp,
  • Valentina Richthammer,
  • Tobias Schwarzer,
  • Fedor Smirnov,
  • Jan Spieck,
  • Jürgen Teich,
  • Andreas Weichslgartner,
  • Stefan Wildermann

DOI
https://doi.org/10.3390/jlpea10040038
Journal volume & issue
Vol. 10, no. 4
p. 38

Abstract

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Many-core platforms are rapidly expanding in various embedded areas as they provide the scalable computational power required to meet the ever-growing performance demands of embedded applications and systems. However, the huge design space of possible task mappings, the unpredictable workload dynamism, and the numerous non-functional requirements of applications in terms of timing, reliability, safety, and so forth. impose significant challenges when designing many-core systems. Hybrid Application Mapping (HAM) is an emerging class of design methodologies for many-core systems which address these challenges via an incremental (per-application) mapping scheme: The mapping process is divided into (i) a design-time Design Space Exploration (DSE) step per application to obtain a set of high-quality mapping options and (ii) a run-time system management step in which applications are launched dynamically (on demand) using the precomputed mappings. This paper provides an overview of HAM and the design methodologies developed in line with it. We introduce the basics of HAM and elaborate on the way it addresses the major challenges of application mapping in many-core systems. We provide an overview of the main challenges encountered when employing HAM and survey a collection of state-of-the-art techniques and methodologies proposed to address these challenges. We finally present an overview of open topics and challenges in HAM, provide a summary of emerging trends for addressing them particularly using machine learning, and outline possible future directions. While there exists a large body of HAM methodologies, the techniques studied in this paper are developed, to a large extent, within the scope of invasive computing. Invasive computing introduces resource awareness into applications and employs explicit resource reservation to enable incremental application mapping and dynamic system management.

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