Software-assisted cache mechanisms for embedded systems

Abstract

Embedded systems are increasingly using on-chip caches as part of their on-chip memory system. This thesis presents cache mechanisms to improve cache performance and provide opportunities to improve data availability that can lead to more predictable cache performance. The first cache mechanism presented is an intelligent cache replacement policy that utilizes information about dead data and data that is very frequently used. This mechanism is analyzed theoretically to show that the number of misses using intelligent cache replacement is guaranteed to be no more than the number of misses using traditional LRU replacement. Hardware and software-assisted mechanisms to implement intelligent cache replacement are presented and evaluated. The second cache mechanism presented is that of cache partitioning which exploits disjoint access sequences that do not overlap in the memory space. A theoretical result is proven that shows that modifying an access sequence into a concatenation of disjoint access sequences is guaranteed to improve the cache hit rate. Partitioning mechanisms inspired by the concept of disjoint sequences are designed and evaluated. A profit-based analysis, annotation, and simulation framework has been implemented to evaluate the cache mechanisms. This framework takes a compiled benchmark program and a set of program inputs and evaluates various cache mechanisms to provide a range of possible performance improvement scenarios. The proposed cache mechanisms have been evaluated using this framework by measuring cache miss rates and Instructions Per Clock (IPC) information. The results show that the proposed cache mechanisms show promise in improving cache performance and predictability with a modest increase in silicon area.