RAMP: Resource-aware mapping for CGRAs

Shail Dave, Mahesh Balasubramanian, Aviral Shrivastava

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

47 Scopus citations


Coarse-grained reconfigurable array (CGRA) is a promising solution that can accelerate even non-parallel loops. Acceleration achieved through CGRAs critically depends on the goodness of mapping (of loop operations onto the PEs of CGRA), and in particular, the compiler's ability to route the dependencies among operations. Previous works have explored several mechanisms to route data dependencies, including, routing through other PEs, registers, memory, and even re-computation. All these routing options change the graph to be mapped onto PEs (often by adding new operations), and without re-scheduling, it may be impossible to map the new graph. However, existing techniques explore these routing options inside the Place and Route (P&R) phase of the compilation process, which is performed after the scheduling step. As a result, they either may not achieve the mapping or obtain poor results. Our method RAMP, explicitly and intelligently explores the various routing options, before the scheduling step, and makes improve the mapping-ability and mapping quality. Evaluating top performance-critical loops of MiBench benchmarks over 12 architectural configurations, we find that RAMP is able to accelerate loops by 23× over sequential execution, achieving a geomean speedup of 2.13× over state-of-the-art.

Original languageEnglish (US)
Title of host publicationProceedings of the 55th Annual Design Automation Conference, DAC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781450357005
StatePublished - Jun 24 2018
Event55th Annual Design Automation Conference, DAC 2018 - San Francisco, United States
Duration: Jun 24 2018Jun 29 2018

Publication series

NameProceedings - Design Automation Conference
VolumePart F137710
ISSN (Print)0738-100X


Other55th Annual Design Automation Conference, DAC 2018
Country/TerritoryUnited States
CitySan Francisco

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modeling and Simulation


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