静态分析用于快速、准确地设计空间探索缓存

Yun Liang, T. Mitra
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引用次数: 18

摘要

特定于应用程序的片上系统平台创造了定制缓存配置的机会,以最小的芯片占用实现最佳性能。仿真,特别是跟踪驱动仿真,被广泛用于估计缓存命中率。然而,在设计空间探索中,特别是涉及数百个设计点和巨大的轨迹或长时间的程序执行时,仿真速度太慢。在本文中,我们提出了一种新的静态分析技术,用于快速准确地探索指令缓存的设计空间。给定程序控制流图(CFG)仅注释了基本块和控制流边缘执行计数,我们的分析估计了一次通过多个缓存配置的命中率。我们通过以概率方式对CFG的每个节点的缓存状态进行建模,并利用相关缓存配置之间的结构相似性来实现这一目标。实验结果表明,我们的分析比已知最快的缓存模拟器快24- 3,855倍,同时保持高精度(平均误差0.7%),预测流行嵌入式基准的命中率。
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Static analysis for fast and accurate design space exploration of caches
Application-specific system-on-chip platforms create the opportunity to customize the cache configuration for optimal performance with minimal chip estate. Simulation, in particular trace-driven simulation, is widely used to estimate cache hit rates. However, simulation is too slow to be deployed in the design space exploration, specially when it involves hundreds of design points and huge traces or long program execution. In this paper, we propose a novel static analysis technique for rapid and accurate design space exploration of instruction caches. Given the program control flow graph (CFG) annotated only with basic block and control flow edge execution counts, our analysis estimates the hit rates for multiple cache configurations in one pass. We achieve this by modeling the cache states at each node of the CFG in probabilistic manner and exploiting the structural similarities among related cache configurations. Experimental results indicate that our analysis is 24--3,855 times faster compared to the fastest known cache simulator while maintaining high accuracy (0.7% average error), in predicting hit rates for popular embedded benchmarks.
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