RISPP: A run-time adaptive reconfigurable embedded processor

Lars Bauer, Muhammad Shafique, Jörg Henkel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Processors that deploy reconfigurable fabrics to implement application-specific accelerators on-demand obtained significant attention within the last decade. They trade-off the flexibility of general-purpose processors with the performance of application-specific circuits without tailoring the processor towards a specific application domain like Application Specific Instruction Set Processors (ASIPs). However, even though they reconfigure parts of the hardware at run time, the decisions which accelerators shall be reconfigured at which time are typically determined at compile time. Therefore, it is conceptually not possible to react to dynamically changing situations like varying dynamic control flow (e.g. due to changed input data), changing task priorities / performance constraints, and changing availability of reconfigurable hardware (may be reassigned to another task). This work presents the novel Rotating Instruction Set Processing Platform (RISPP) with its run-time system that enables dynamic adaptations in the above highlighted scenarios efficiently. Therefore, the presented approach is suitable for long-term as well as frequent adaptation requirements.

Original languageEnglish (US)
Title of host publicationFPL 09
Subtitle of host publication19th International Conference on Field Programmable Logic and Applications
Pages725-726
Number of pages2
DOIs
StatePublished - 2009
EventFPL 09: 19th International Conference on Field Programmable Logic and Applications - Prague, Czech Republic
Duration: Aug 31 2009Sep 2 2009

Publication series

NameFPL 09: 19th International Conference on Field Programmable Logic and Applications

Other

OtherFPL 09: 19th International Conference on Field Programmable Logic and Applications
CountryCzech Republic
CityPrague
Period8/31/099/2/09

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications

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