一种基于延迟感知封装算法的rfet FPGA结构

IF 5.4 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Sheng Lu;Liuting Shang;Sungyong Jung;Qilian Liang;Chenyun Pan
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引用次数: 0

摘要

可重构器件作为传统CMOS技术的潜在替代和补充,正引起人们越来越多的兴趣。本文开发了一种基于MClusters的新型现场可编程门阵列(FPGA)架构,该架构通过可重构场效应晶体管(rfet)组成快速高效的2输入查找表(lut)。为了充分利用MClusters,我们提出了一种基于sat的延迟感知封装算法用于技术映射。此外,我们还集成了一种划分算法,将电路划分为若干个子电路,以进一步减少系统的全局路由资源及其相关的交换能量。最后,我们开发了一个高效的技术/电路/系统协同设计框架,以优化fpga的整体性能。基于全面的基准测试,结果表明,与传统的CMOS 6输入LUT fpga相比,优化设计可显着减少高达39%的面积,36%的线长和40%的开关能量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel RFET-Based FPGA Architecture Based on Delay-Aware Packing Algorithm
Reconfigurable devices are attracting growing interest as both a potential alternative and complement to traditional CMOS technology. This paper develops a novel field-programmable gate array (FPGA) architecture based on MClusters, which is made of fast and area-efficient 2-input look-up tables (LUTs) through reconfigurable field-effect transistors (RFETs). To fully utilize the MClusters, we propose an SAT-based delay-aware packing algorithm for the technology mapping. In addition, we integrate a partitioning algorithm to divide the circuit into several sub-circuits to further reduce the global routing resources and their associated switching energy of the system. Finally, we develop an efficient technology/circuit/system co-design framework for optimizing the overall performance of FPGAs. Based on comprehensive benchmarking, results demonstrate that optimal design yields significant reductions of up to 39% area, 36% wire length, and 40% switching energy compared to traditional CMOS 6-input LUT FPGAs.
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来源期刊
IEEE Transactions on Emerging Topics in Computing
IEEE Transactions on Emerging Topics in Computing Computer Science-Computer Science (miscellaneous)
CiteScore
12.10
自引率
5.10%
发文量
113
期刊介绍: IEEE Transactions on Emerging Topics in Computing publishes papers on emerging aspects of computer science, computing technology, and computing applications not currently covered by other IEEE Computer Society Transactions. Some examples of emerging topics in computing include: IT for Green, Synthetic and organic computing structures and systems, Advanced analytics, Social/occupational computing, Location-based/client computer systems, Morphic computer design, Electronic game systems, & Health-care IT.
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