Quantitative Analysis and Optimization Techniques for On-Chip Cache Leakage Power

fraction of the total power consumption of microprocessors. In nanometer-scale technology, the subthreshold leakage power is becoming one of the dominant total power consumption com-ponents of those caches. In this study, we present optimization techniques to reduce the subthreshold leakage power of on-chip caches assuming that there are multiple threshold voltages, ’s, available. First, we show a cache leakage optimization technique that examines the tradeoff between access time and subthreshold leakage power by assigning distinct ’s to each of the four main cache components—address bus drivers, data bus drivers, decoders, and static random access memory (SRAM) cell arrays with sense amplifiers. Second, we show optimization techniques to reduce the leakage power of L1 and L2 on-chip caches without affecting the average memory access time. The key results are: 1) two additional high ’s are enough to minimize leakage in a single cache—3 ’s if we include a nominal low for micro-processor core logic; 2) if L1 size is fixed, increasing L2 size can result in much lower leakage without reducing average memory access time; 3) if L2 size is fixed, reducing L1 size may result in lower leakage without loss of the average memory access time for the SPEC2K benchmarks; and 4) smaller L1 and larger L2 caches than are typical in today’s processors result in significant leakage and dynamic power reduction without affecting the average memory access time. Index Terms—Microprocessor memory hierarchy, multiple threshold voltage, on-chip caches, SRAM, subthreshold leakage power. I