后百亿亿次计算时代的微处理器体系结构与设计

Wang Di, LI Hong-Liang
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引用次数: 2

摘要

在后百亿亿次计算时代,传统互补金属氧化物半导体(CMOS)工艺的能效提升速度明显放缓。为了在2035年实现zettascale的计算能力,需要在微处理器架构和设计上进行重大创新。本文选取了具有广阔发展前景的低功耗技术、近数据处理(NDP)技术、以互联为中心的设计方法和特定领域架构(DSA)四个方面,重点分析了每种技术的能效效益。首先,分析了各种传统的低功耗技术和近阈值计算技术;其次,分析了近内存计算、内存计算和网络计算等NDP技术;第三,分析了低开销片上网络、新工艺支持的片上网络和缓存相干片上网络技术;最后,以目前流行的人工智能处理器为例,对DSA进行了分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Microprocessor Architecture and Design in Post Exascale Computing Era
In the post exascale computing era, the energy efficiency improvement speed of traditional complementary metal-oxide-semiconductor (CMOS) process has slowed down significantly. In order to realize the zettascale computing capacity in 2035, a great innovation is needed in the microprocessor architecture and design. This paper selects four aspects, which are low power consumption technology, near data processing (NDP) technology, interconnection centered design method and domain specific architecture (DSA), which has a broad development prospect, and focus on the energy efficiency benefits of each technology. Firstly, we analyze various traditional low power consumption technologies and near threshold computing (NTC) technology; secondly, we analyze the NDP technologies such as near memory computing, in memory computing and in network computing; thirdly, we analyze the low overhead network on chip (NOC), NOC supported by new process and cache coherent NOC technology; finally, we take the popular artificial intelligence (AI) processor as an example to analyze the DSA.
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