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首页> 外文期刊>IEICE Transactions on fundamentals of electronics, communications & computer sciences >A Two-Level Cache Design Space Exploration System for Embedded Applications
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A Two-Level Cache Design Space Exploration System for Embedded Applications

机译:嵌入式应用的二级缓存设计空间探索系统

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Recently, two-level cache, L1 cache and L2 cache, is commonly used in a processor. Particularly in an embedded system whereby a single application or a class of applications is repeatedly executed on a processor, its cache configuration can be customized such that an optimal one is achieved. An optimal two-level cache configuration can be obtained which minimizes overall memory access time or memory energy consumption by varying the three cache parameters: the number of sets, a line size, and an associativity, for L1 cache and L2 cache. In this paper, we first extend the L1 cache simulation algorithm so that we can explore two-level cache configuration. Second, we propose two-level cache design space exploration algorithms: CRCB-T1 and CRCB-T2, each of which is based on applying Cache Inclusion Property to two-level cache configuration. Each of the proposed algorithms realizes exact cache simulation but decreases the number of cache hit/miss judgments by a factor of several thousands. Experimental results show that, by using our approach, the number of cache hit/miss judgments required to optimize a cache configurations is reduced to 1/50-1/5500 compared to the exhaustive approach. As a result, our proposed approach totally runs an average of 1398.25 times faster compared to the exhaustive approach. Our proposed cache simulation approach achieves the world fastest two-level cache design space exploration.
机译:近来,处理器中通常使用二级高速缓存,即L1高速缓存和L2高速缓存。特别是在嵌入式系统中,其中一个应用程序或一类应用程序在处理器上重复执行,其缓存配置可以进行自定义,以实现最佳配置。通过更改三个高速缓存参数(L1高速缓存和L2高速缓存的组数,行大小和关联性),可以获得最佳的二级高速缓存配置,该配置可以最大程度地减少总体内存访问时间或内存能耗。在本文中,我们首先扩展了L1缓存模拟算法,以便我们可以探索两级缓存配置。其次,我们提出了两级高速缓存设计空间探索算法:CRCB-T1和CRCB-T2,它们各自基于将高速缓存包含属性应用于两级高速缓存配置。每种提出的算法都可以实现精确的高速缓存模拟,但是将高速缓存命中/未中判断的次数减少了数千倍。实验结果表明,与详尽的方法相比,通过使用我们的方法,优化缓存配置所需的缓存命中/未命中判断次数减少到1 / 50-1 / 5500。结果,与穷举方法相比,我们提出的方法的平均运行速度平均快了1398.25倍。我们提出的缓存仿真方法实现了世界上最快的两级缓存设计空间探索。

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