An Architecture Framework for Transparent Instruction Set Customization in Embedded Processors

  • Authors:

  • Nathan Clark;Jason Blome;Michael Chu;Scott Mahlke;Stuart Biles;Krisztian Flautner

  • Affiliations:

  • University of Michigan - Ann Arbor;University of Michigan - Ann Arbor;University of Michigan - Ann Arbor;University of Michigan - Ann Arbor;ARM, Ltd.;ARM, Ltd.

  • Venue:
  • Proceedings of the 32nd annual international symposium on Computer Architecture
  • Year:
  • 2005

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Abstract

Instruction set customization is an effective way to improve processor performance. Critical portions of applicationdata-flow graphs are collapsed for accelerated execution on specialized hardware. Collapsing dataflow subgraphs will compress the latency along critical paths and reduces the number of intermediate results stored in the register file. While custom instructions can be effective, the time and cost of designing a new processor for each application is immense. To overcome this roadblock, this paper proposes a flexible architectural framework to transparently integrate custom instructions into a general-purpose processor. Hardware accelerators are added to the processor to execute the collapsed subgraphs. A simple microarchitectural interface is provided to support a plug-and-play model for integrating a wide range of accelerators into a pre-designed and verified processor core. The accelerators are exploited using an approach of static identification and dynamic realization. The compiler is responsible for identifying profitable subgraphs, while the hardware handles discovery, mapping, and execution of compatible subgraphs. This paper presents the design of a plug-and-play transparent accelerator system and evaluates the cost/performance implications of the design.