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A framework for effective exploitation of partial reconfiguration in dataflow computing

机译:在数据流计算中有效利用部分重配置的框架

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The exploitation of high-performance architectures based on reconfigurable hardware to build power efficient supercomputing clusters is becoming more and more common. Indeed, large speedups have already been demonstrated in several high-performance computing (HPC) applications. On the other hand, partial reconfiguration (PR) has the potential to further increase performance and power efficiency in many applications; however, there is currently very limited support for transforming a traditional design into a reconfigurable one. In this work, we introduce a design methodology for PR designs that combines application analysis, partitioning, mapping and scheduling, and supports fast exploration of various design options. These steps are integrated in an automated toolchain which allows a designer to implement reconfigurable designs with simple guidance through a graphical interface. We demonstrate our approach by applying the methodology to an image processing application, implementing the proposed design on a Maxeler MaxWorkstation.
机译:利用基于可重配置硬件的高性能体系结构来构建高能效的超级计算集群变得越来越普遍。实际上,已经在几种高性能计算(HPC)应用程序中证明了大幅提速。另一方面,在许多应用中,部分重配置(PR)可能会进一步提高性能和电源效率。但是,目前对将传统设计转换为可重构设计的支持非常有限。在这项工作中,我们介绍了一种PR设计的设计方法,该方法结合了应用程序分析,分区,映射和调度,并支持快速探索各种设计选项。这些步骤集成在自动化工具链中,使设计人员可以通过图形界面在简单指导下实现可重新配置的设计。我们通过将方法论应用于图像处理应用程序并在Maxeler MaxWorkstation上实施建议的设计,来演示我们的方法。

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