Statistical Cache Bypassing for Non-Volatile Memory

With the increasing data throughput requirement, non-volatile memories, such as STT-RAM, PCM and RRAM, have become very competitive designs as on-chip caches in chip-multi-processors (CMPs). Since the write operations are more expensive in an asymmetric-access cache, it is more valuable to justify the data allocation. However, the asymmetric-access property of non-volatile memory is not well addressed in prior bypassing approaches, which are not energy efficient and induce non-trivial operation overhead. In this paper, we propose cache-bypassing methods designed for non-volatile memory. The basic method, SBAC, is based on data locality statistics of the whole cache rather than a signature of each cache line. The multicore extensions, SBAC-C and SBAC-G, strengthen the SBAC by distinguishing data patterns in CMPs. We observe that the decision-making of SBAC and its multicore extensions is highly accurate. Experiments show that SBAC can reduce overall energy consumption by 22.3 percent, and reduce execution time by 8.3 percent on average. The energy consumption is reduced by 21.4 and 23.4 percent for SBAC-C and SBAC-G. And the performance is improved by 7.8 and 9.6 percent for SBAC-C and SBAC-G in multicore scenario. Compared to prior approaches, SBAC outperforms and induces trivial design overhead.

Duke Scholars

Author Yiran Chen Electrical and Computer Engineering