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首页> 外文期刊>International journal of parallel programming >Automatic Design of Application Specific Instruction Set Extensions through Dataflow Graph Exploration
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Automatic Design of Application Specific Instruction Set Extensions through Dataflow Graph Exploration

机译：通过数据流图探索自动设计专用指令集扩展

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General-purpose processors are often incapable of achieving the challenging cost, performance, and power demands of high-performance applications. To meet these demands, most systems employ a number of hardware accelerators to off-load the computationally demanding portions of the application. As an alternative to this strategy, we examine customizing the computation capabilities of a processor for a particular application. The processor is extended with hardware in the form of a set of custom function units and instruction set extensions. To effectively identify opportunities for creating custom hardware, a dataflow graph design space exploration engine heuristically identifies candidate computation subgraphs without artificially constraining their size or shape. The engine combines estimates of performance gain, cost, and inherent limitations of the processor to grow candidate graphs in profitable directions while pruning unprofitable paths. This paper describes the dataflow graph exploration engine and evaluates its effectiveness across a set of embedded applications.
机译：通用处理器通常无法满足高性能应用程序具有挑战性的成本，性能和功耗要求。为了满足这些需求，大多数系统采用了许多硬件加速器来减轻应用程序的计算需求。作为此策略的替代方法，我们研究了为特定应用定制处理器的计算能力。处理器以一组定制功能单元和指令集扩展的形式通过硬件进行扩展。为了有效地识别创建定制硬件的机会，数据流图设计空间探索引擎可启发式地识别候选计算子图，而无需人为地限制其大小或形状。该引擎结合了性能增益，成本和处理器的固有局限性的估计，以在有利可图的方向上增长候选图形，同时修剪了无利可图的路径。本文介绍了数据流图探索引擎，并评估了其在一组嵌入式应用程序中的有效性。

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