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Automatic generation of maps of memory accesses for energy-aware memory management

机译:自动生成内存访问映射以进行能源敏感的内存管理

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Many signal processing systems are synthesized to execute data-dominated applications. Their behavior is described in a high-level programming language, where the code is typically organized in sequences of loop nests and the main data structures are multidimensional arrays. Since data transfer and storage have a significant impact on both the system performance and the major cost parameters - power consumption and chip area, the designer must spend a significant effort during the system development process on the exploration of the memory subsystem in order to achieve a cost-optimized design. This paper focuses on the reduction of the dynamic energy consumption in the hierarchical memory subsystem of multidimensional signal processing systems, starting from the high-level behavioral specification of the application. The paper presents an algorithm which identifies those parts of arrays from a high-level specification that are intensely accessed (for read and/or write operations), whose storage on-chip yields the highest benefit in terms of dynamic energy consumption. Tested on a two-layer memory hierarchy (scratch-pad and off-chip memories), this algorithm led to significant savings of energy in comparison to previous computation models.
机译:许多信号处理系统都经过综合以执行以数据为主的应用程序。它们的行为用高级编程语言描述,其中代码通常按循环嵌套的顺序进行组织,而主要数据结构是多维数组。由于数据传输和存储对系统性能以及主要的成本参数(功耗和芯片面积)都具有重大影响,因此设计人员必须在系统开发过程中花费大量精力来探索内存子系统,以实现最佳性能。成本优化设计。从应用程序的高级行为规范出发,本文着重于降低多维信号处理系统的分层存储子系统中的动态能耗。本文提出了一种算法,该算法可以从高级别规范中识别出阵列中被密集访问的部分(用于读和/或写操作),就动态能耗而言,其片上存储产生了最高的收益。经过两层存储器层次结构(便笺式存储器和片外存储器)的测试,与以前的计算模型相比,该算法可节省大量能源。

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