StageNetSlice: a reconfigurable microarchitecture building block for resilient CMP systems

  • Authors:

  • Shantanu Gupta;Shuguang Feng;Amin Ansari;Jason Blome;Scott Mahlke

  • Affiliations:

  • University of Michigan, Ann Arbor, MI, USA;University of Michigan, Ann Arbor, MI, USA;University of Michigan, Ann Arbor, MI, USA;University of Michigan, Ann Arbor, MI, USA;University of Michigan, Ann Arbor, MI, USA

  • Venue:
  • CASES '08 Proceedings of the 2008 international conference on Compilers, architectures and synthesis for embedded systems
  • Year:
  • 2008

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Abstract

Although CMOS feature size scaling has been the source of dramatic performance gains, it has lead to mounting reliability concerns due to increasing power densities and on-chip temperatures. Given that most wearout mechanisms that plague semiconductor devices are highly dependent on these parameters, significantly higher failure rates are projected for future technology generations. Traditional techniques for dealing with device failures have relied on coarse-grained redundancy to maintain service in the face of failed components. In this work, we challenge this practice by identifying its inability to scale to high failure rate scenarios and investigate the advantages of finer-grained configurations. We use this study to motivate the design of StageNet, an embedded CMP architecture designed from its inception with reliability as a first class design constraint. StageNet relies on a reconfigurable network of replicated processor pipeline stages to maximize the useful lifetime of the chip, gracefully degrading performance toward end of life. This paper addresses the microarchitecture of the basic building block of StageNet, named StageNetSlice, which is a processor core comprised of networked pipeline stages. A naive slice design results in approximately 4X slowdown verses a traditional processor due to longer communication delays in the pipeline. However, several small design changes that eliminate inter-stage communication paths and minimize communication bandwidth reduce this overhead to 11% on average while providing high levels of fine-grain adaptability.