Design and analysis of low-power cache using two-level filter scheme

  • Authors:
  • Yen-Jen Chang;Shanq-Jang Ruan;Feipei Lai

  • Affiliations:
  • Computer Science and Information Engineering Department, National Taiwan University, Taipei, Taiwan 106, R.O.C.;Synopsys Inc., Taipei, Taiwan, 110 R.O.C. and Electrical Engineering Department, National Taiwan University, Taipei, Taiwan 106, R.O.C.;Computer Science and Information Engineering and Electrical Engineering Departments, National Taiwan University, Taipei, Taiwan, 106, R.O.C.

  • Venue:
  • IEEE Transactions on Very Large Scale Integration (VLSI) Systems
  • Year:
  • 2003

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Abstract

Power consumption is an increasingly pressing problem in modern processor design. Since the on-chip caches usually consume a significant amount of power, it is one of the most attractive targets for power reduction. This paper presents a two-level filter scheme, which consists of the L1 and L2 filters, to reduce the power consumption of the on-chip cache. The main idea of the proposed scheme is motivated by the substantial unnecessary activities in conventional cache architecture. We use a single block buffer as the L1 filter to eliminate the unnecessary cache accesses. In the L2 filter, we then propose a new sentry-tag architecture to further filter out the unnecessary way activities in case of the L1 filter miss. We use SimpleScalar to simulate the SPEC2000 benchmarks and perform the HSPICE simulations to evaluate the proposed architecture. Experimental results show that the two-level filter scheme can effectively reduce the cache power consumption by eliminating most unnecessary cache activities, while the compromise of system performance is negligible. Compared to a conventional instruction cache (32 kB, two-way) implemented with only the L1 filter, the use of a two-level filter can result in roughly 30% reduction in total cache power consumption. Similarly, compared to a conventional data cache (32 kB, four-way) implemented with only the L1 filter, the total cache power reduction is approximately 46%.