Efficient System-on-Chip Energy Management with a Segmented Bloom Filter

As applications tend to grow more complex and use more memory, the demand for cache space increases. Thus embedded processors are inclined to use larger caches. Predicting a miss in a long-latency cache becomes crucial in an embedded system-on-chip(SOC) platform to perform microarchitecture-level energy management. Counting Bloom filters are simple and fast structures that can eliminate associative lookup in a huge lookup space. This paper presents an innovative segmented design of the counting Bloom filter which can save SOC energy by detecting misses aiming at a cache level before the memory. The filter presented is successful in filtering out 89% of L2 cache misses and thus helps in reducing L2 accesses by upto 30%. This reduction in L2 Cache accesses and early triggering of energy management processes lead to an overall SOC energy savings by up to 9%.