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A Data-Driven Approach for Pipelining Sequences of Data-Dependent Loops

机译:一种用于数据依赖循环序列的流水线化的数据驱动方法

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Many video and image/signal processing applications can be structured as sequences of data-dependent tasks using a consumer/producer communication paradigm and are therefore amenable to pipelined execution. This paper presents an execution technique to speed-up the overall execution of successive, data-dependent tasks on a reconfigurable architecture. The technique pipelines sequences of data-dependent tasks by overlapping their execution subject to data-dependences. It decouples the concurrent data-path and control units and uses a custom, application data-driven, fine-grained synchronization and buffering scheme. In addition, the execution scheme allows for out-of- order, but data-dependent producer-consumer pairs not allowed by previous data-driven pipelining approaches. The approach has been exploited in the context of a high-level compiler targeting FPGAs. The preliminary experimental results reveal noticeable performance improvements and buffer size reductions for a number of benchmarks over traditional approaches.
机译:可以使用消费者/生产者通信范例将许多视频和图像/信号处理应用程序构造为与数据相关的任务序列,因此适合流水线执行。本文提出一种执行技术,以加快可重配置体系结构上连续的,与数据相关的任务的整体执行速度。该技术通过重叠执行依赖于数据依存关系的数据来对数据依存任务的序列进行流水线处理。它解耦并发数据路径和控制单元,并使用自定义的,应用程序数据驱动的细粒度同步和缓冲方案。另外,执行方案允许乱序,但以前的数据驱动流水线方法不允许数据相关的生产者-消费者对。该方法已在针对FPGA的高级编译器的上下文中得到了利用。初步的实验结果表明,与传统方法相比,许多基准测试的性能得到了显着改善,缓冲区大小也有所减少。

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