数据驱动机器中部分可重构硬件分区模型开销的研究与部分分析

Francisco Dias de Souza Júnior, J. L. Silva, Lucas Sanches, V. Astolfi
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引用次数: 0

摘要

计算机应用变得越来越复杂,需要更大的处理能力。为了在这些应用中实现更高的性能,算法通常在现场可编程门阵列(fpga)中实现。然而,大多数计算机辅助设计(CAD)工具仍然使用硬件描述语言(HDL),与命令式高级语言(HLL)相比,它是复杂的。ChipCflow是一个旨在将HDL转换为HDL的工具,使用动态数据流模型和主动部分重构(APR)。在本文中,我们提出了硬件架构的分区模型的研究报告,这是使用apr将数据流图(DFGs)正确分配到FPGA结构中所必需的。为了计算系统的逻辑开销,我们给出了一些结果,表示了操作员的逻辑和必要的可重构区域之间的比率,以及这些可重构区域的重构时间的一些准则。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research and Partial analysis of overhead of a partition model for a Partially Reconfigurable hardware in a data-driven machine - chicflow
Computer applications have become increasingly more complex and require greater processing capacity. In order to achieve higher performance for these applications, algorithms are often implemented in Field-Programmable Gate Arrays (FPGAs). However, most of the Computer-Aided Design (CAD) tools still uses Hardware Description Languages (HDL), which are complex if compared with imperative High Level Languages (HLL). ChipCflow is a tool that aims to convert HLL to HDL, using the dynamic dataflow model and Active Partial Reconfiguration (APR). In this paper we present a research report for the hardware architecture's partition model, necessary for the correct allocation of Dataflow Graphs (DFGs) into FPGA's fabric using APR. In order to calculate system's logic overhead, we show some results which denotes a ratio between the operator's logic and the necessary reconfigurable area, as well as some guidelines about the reconfiguration time of these reconfigurable areas.
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