Memory system design space exploration for low-power, real-time speech recognition

The recent proliferation of computing technology has generated new interest natural I/O interface technologies such as speech recognition. Unfortunately, the computational and memory demands of such applications currently prohibit their use on low-power portable devices in anything more than their simplest forms. Previous work has demonstrated that the thread level concurrency inherent in this application domain can be used to dramatically improve performance with minimal impact on overall system energy consumption, but that such benefits are severely constrained by memory system bandwidth. This work presents a design space exploration of potential memory system architectures. A range of low-power memory organizations are considered, from conventional caching to more advanced system-on-chip implementations. We find that, given architectures able to exploit concurrency in this domain, large L2 based cache hierarchies and high bandwidth memory systems employing data stream partitioning and on-chip embedded DRAM and ROM technologies can provide much of the performance of idealized memory systems without violating the power constraints of the low-power domain.