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AUTOMATIC GENERATION OF MAPS OF MEMORY ACCESSES FOR ENERGY-AWARE MEMORY MANAGEMENT

机译:自动生成能量感知内存管理的内存访问地图

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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:合成许多信号处理系统以执行数据主导的应用程序。它们的行为是以高级编程语言描述的,其中代码通常以循环巢的序列组织,并且主数据结构是多维数组。由于数据传输和存储对系统性能和主要成本参数的重大影响 - 功耗和芯片面积,因此设计师必须在系统开发过程中花费重大努力,以实现内存子系统的探索,以实现a经济优化的设计。本文侧重于从应用程序的高级行为规范开始的多维信号处理系统的分层存储器子系统中的动态能耗。本文提出了一种算法,该算法从高级规范中识别阵列的那些部分,该算法从强烈访问的高级规范(用于读取和/或写入操作),其存储片在动态能耗方面产生最高的益处。在双层存储层级(划痕垫和片外存储器)上测试,与先前的计算模型相比,该算法导致了高能量节省。

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