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STATIC PATTERN PREDICTOR (SPP) BASED LOW POWER INSTRUCTION CACHE DESIGN

机译:基于静态图案预测器(SPP)低功耗教学缓存设计

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Energy dissipation in cache memories is becoming a major design issue in embedded microprocessors. Predictive filter cache based instruction cache hierarchy is effective in reducing the access energy substantially at the cost of certain performance degradation. Here, the energy-delay product reduction heavily depends on the prediction accuracy of the predictor. In this paper, a simplified pattern prediction algorithm, which maximizes power savings in the novel filter cache prediction hierarchy, is proposed. The prediction mechanism relies on the static nature of the hit or miss pattern of the instruction access stream over the past filter cache line accesses. These static patterns are stored in a 32-entry single-bit Pattern Table (PT). The entries could be dynamically changed during run time to provide options for real-time adaptation in a complex application. The proposed prediction algorithm results in better prediction for all the benchmarks simulated. Energy delay product reduction of up to 8.19% over existing NFPT prediction scheme was reported for the benchmarks simulated.
机译:缓存记忆中的能量耗散正在成为嵌入式微处理器中的主要设计问题。基于预测的滤波器高速缓存的指令高速缓存层级在基本上以某种性能下降的成本降低了降低的访问能量。这里,能量延迟产品减少大量取决于预测器的预测精度。本文提出了一种简化的模式预测算法,其最大化了新型滤波器高速缓存预测层级中的功率节省。预测机制依赖于过去过滤器缓存行访问的指令访问流的命中或错过模式的静态性质。这些静态模式存储在32条进入单位模式表(PT)中。在运行时可以动态地改变条目,以提供复杂应用程序中的实时适应选项。所提出的预测算法导致对模拟所有基准的更好预测。报告了对现有的NFPT预测方案的能量延迟产品降低了高达8.19%的基准。

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