Dynamic Zero Compression reduces the energy required for cache accesses by only writing and reading a single bit for every zero-valued byte. This energy-conscious compression is invisible to software and is handled with additional circuitry embedded inside the cache RAM arrays and the CPU. The additional circuitry imposes a cache area overhead of 9% and a read latency overhead of around two FO4 gate delays. Simulation results show that we can reduce total data cache energy by around 26% and instruction cache energy by around 10% for SPECint95 and Media-Bench benchmarks. We also describe the use of an instruction recoding technique that increases instruction cache energy savings to 18%.
A new dynamic cache resizing scheme for low-power CAMtag caches is introduced. A control algorithm that is only activated on cache misses uses a duplicate set of tags, the miss tags, to minimize active cache size while sustaining close to the same hit rate as a full size cache. The cache partitioning mechanism saves both switching and leakage energy in unused partitions with little impact on cycle time. Simulation results show that the scheme saves 28-56% of data cache energy and 34-49% of instruction cache energy with minimal performance impact.
A new dynamic cache resizing scheme for low-power CAMtag caches is introduced. A control algorithm that is only activated on cache misses uses a duplicate set of tags, the miss tags, to minimize active cache size while sustaining close to the same hit rate as a full size cache. The cache partitioning mechanism saves both switching and leakage energy in unused partitions with little impact on cycle time. Simulation results show that the scheme saves 28-56% of data cache energy and 34-49% of instruction cache energy with minimal performance impact.
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