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

机译:用于低功耗实时语音识别的内存系统设计空间探索

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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.
机译:计算技术的近来激增引起了新的兴趣,例如语音识别等自然的I / O接口技术。不幸的是,此类应用程序的计算和内存需求目前禁止它们以最简单的形式用于低功率便携式设备。先前的工作表明,此应用程序域中固有的线程级别并发性可用于显着提高性能,而对整体系统能耗的影响最小,但是这种好处受到内存系统带宽的严重限制。这项工作提出了对潜在的内存系统体系结构的设计空间探索。从传统的缓存到更高级的片上系统实现,已经考虑了许多低功耗存储组织。我们发现,给定能够在此域中利用并发性的体系结构,基于大型L2的缓存层次结构和采用数据流分区以及片上嵌入式DRAM和ROM技术的高带宽存储系统可以提供理想化存储系统的大部分性能,而不会破坏存储系统的性能。低功率域的功率约束。

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