Macho: A Failure Model-oriented Adaptive Cache Architecture to enable Near-Threshold Voltage Scaling

Abstract

Recent interest in CMOS voltage scaling has produced a class of cache architectures which tolerate parametric SRAM failures at low voltage by substituting faulty words of one cache line with healthy words of another line. These caches rely on the fault maps (which grow reciprocally with smaller word sizes) for fault identification. Therefore, the benefits of cache voltage scaling must be rigorously investigated against the cost of their fault map overheads, especially in large caches.

This paper reviews the word substitution caches and develops their parametric failure model. Our developed model leads to a non-intrusive and reconfigurable cache (Macho) which can be locally optimized (based on local fault density) by two graph-based algorithms. Specifically, our adaptive matching algorithm increases effective cache capacity by dynamically concentrating healthy cache blocks into active cache sets. Macho enables voltage scaling down to 400mV by tolerating high SRAM-failure rates (>= 1 %) and achieves better energy reduction (44 %) than other substitution caches with similar area overheads.