ROBTIC: An On-chip Instruction Cache Design for Low Power Embedded Systems
Ji Gu, Hui Guo, Patrick Li
Abstract
Ji Gu, Hui Guo, Patrick Li
Abstract
The on-chip instruction cache is a potential power hungry component in embedded systems due to its large chip area and high access-frequency. Aiming at reducing power consumption of the on-chip cache, we proposed a Reduced One-Bit Tag Instruction Cache (ROBTIC), where the cache size is judiciously reduced and the cache tag field only contains the least significant bit of the full tag. We developed a cache operational control scheme for ROBTIC so that with the one-bit cache tag, the program locality can still be efficiently exploited. For applications where most of the memory accesses are localized, our cache is able to achieve similar performance as a traditional full-tag cache; however, the power consumption of the cache can be significantly reduced due to the much smaller cache size, narrower tag array (just one bit), and tinier tag comparison circuit being used. The experiments on a set of benchmarks demonstrate that our approach can reduce up to 25.8% power consumption and 30.9% area of the traditional cache when the cache size is fixed at 32 instructions. With the cache size customization, a further 48% power saving can be achieved.
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The on-chip instruction cache is a potential power hungry component in embedded systems due to its large chip area and high access-frequency. Aiming at reducing power consumption of the on-chip cache, we proposed a Reduced One-Bit Tag Instruction Cache (ROBTIC), where the cache size is judiciously reduced and the cache tag field only contains the least significant bit of the full tag. We developed a cache operational control scheme for ROBTIC so that with the one-bit cache tag, the program locality can still be efficiently exploited. For applications where most of the memory accesses are localized, our cache is able to achieve similar performance as a traditional full-tag cache; however, the power consumption of the cache can be significantly reduced due to the much smaller cache size, narrower tag array (just one bit), and tinier tag comparison circuit being used. The experiments on a set of benchmarks demonstrate that our approach can reduce up to 25.8% power consumption and 30.9% area of the traditional cache when the cache size is fixed at 32 instructions. With the cache size customization, a further 48% power saving can be achieved.
Key concepts: Cache, Cache pollution, Cache coloring, Page cache, Cache algorithms, Smart Cache, Cache invalidation, Computer science