Variation trained drowsy cache (VTD-Cache): a history trained variation aware drowsy cache for fine grain voltage scaling

  • Authors:
  • Avesta Sasan;Kiarash Amiri;Houman Homayoun;Ahmed M. Eltawil;Fadi J. Kurdahi

  • Affiliations:
  • Department of Electrical Engineering and Computer Science, University of California, Irvine, CA;Department of Electrical Engineering and Computer Science, University of California, Irvine, CA;Department of Computer Science, University of California, Irvine, CA;Department of Electrical Engineering and Computer Science, University of California, Irvine, CA;Department of Electrical Engineering and Computer Science, University of California, Irvine, CA

  • Venue:
  • IEEE Transactions on Very Large Scale Integration (VLSI) Systems
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper we present the "Variation Trained Drowsy Cache" (VTD-Cache) architecture. VTD-Cache allows for a significant reduction in power consumption while addressing reliability issues raised by memory cell process variability. By managing voltage scaling at a very fine granularity, each cache way can be sourced at a different voltage where the selection of voltage levels depends on both the vulnerability of the memory cells in that cache way to process variation and the likelihood of access to that cache location. After a short training period, the proposed architecture will micro-tune the cache, allowing significant power reduction with negligible increase in the number of misses. In addition, the proposed architecture actively monitors the access pattern and reconfigures the supply voltage setting to adapt to the execution pattern of the program. The novel and modular architecture of the VTD-Cache and its associated controller makes it easy to be implemented in memory compilers with a small area and power overhead. In a case study, the SimpleScalar simulation of the proposed 32 kB cache architecture reports over 57% reduction in power consumption over standard SPEC2000 integer benchmarks while incurring an area overhead of less than 4% and an execution time penalty smaller than 1%.