处理后摩尔时代工作负载的可扩展系统和硅架构

I. Bolsens
{"title":"处理后摩尔时代工作负载的可扩展系统和硅架构","authors":"I. Bolsens","doi":"10.1145/3439706.3446894","DOIUrl":null,"url":null,"abstract":"The end of Moore's law has been proclaimed on many occasions and it's probably safe to say that we are now working in the post-Moore era. But no one is ready to slow down just yet. We can view Gordon Moore's observation on transistor densification as just one aspect of a longer-term underlying technological trend - the Law of Accelerating Returns articulated by Kurzweil. Arguably, companies became somewhat complacent in the Moore era, happy to settle for the gains brought by each new process node. Although we can expect scaling to continue, albeit at a slower pace, the end of Moore's Law delivers a stronger incentive to push other trends harder. Some exciting new technologies are now emerging such as multi-chip 3D integration and the introduction of new technologies such as storage-class memory and silicon photonics. Moreover, we are also entering a golden age of computer architecture innovation. One of the key drivers is the pursuit of domain-specific architectures as proclaimed by Turing award winners John Hennessy and David Patterson. A good example is the Xilinx's AI Engine, one of the important features of the Versal? ACAP (adaptive compute acceleration platform). Today, the explosion of AI workloads is one of the most powerful drivers shifting our attention to find faster ways of moving data into, across, and out of accelerators. Features such as massive parallel processing elements, the use of domain specific accelerators, the dense interconnect between distributed on-chip memories and processing elements, are examples of the ways chip makers are looking beyond scaling to achieve next-generation performance gains.","PeriodicalId":184050,"journal":{"name":"Proceedings of the 2021 International Symposium on Physical Design","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Scalable System and Silicon Architectures to Handle the Workloads of the Post-Moore Era\",\"authors\":\"I. Bolsens\",\"doi\":\"10.1145/3439706.3446894\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The end of Moore's law has been proclaimed on many occasions and it's probably safe to say that we are now working in the post-Moore era. But no one is ready to slow down just yet. We can view Gordon Moore's observation on transistor densification as just one aspect of a longer-term underlying technological trend - the Law of Accelerating Returns articulated by Kurzweil. Arguably, companies became somewhat complacent in the Moore era, happy to settle for the gains brought by each new process node. Although we can expect scaling to continue, albeit at a slower pace, the end of Moore's Law delivers a stronger incentive to push other trends harder. Some exciting new technologies are now emerging such as multi-chip 3D integration and the introduction of new technologies such as storage-class memory and silicon photonics. Moreover, we are also entering a golden age of computer architecture innovation. One of the key drivers is the pursuit of domain-specific architectures as proclaimed by Turing award winners John Hennessy and David Patterson. A good example is the Xilinx's AI Engine, one of the important features of the Versal? ACAP (adaptive compute acceleration platform). Today, the explosion of AI workloads is one of the most powerful drivers shifting our attention to find faster ways of moving data into, across, and out of accelerators. Features such as massive parallel processing elements, the use of domain specific accelerators, the dense interconnect between distributed on-chip memories and processing elements, are examples of the ways chip makers are looking beyond scaling to achieve next-generation performance gains.\",\"PeriodicalId\":184050,\"journal\":{\"name\":\"Proceedings of the 2021 International Symposium on Physical Design\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2021 International Symposium on Physical Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3439706.3446894\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2021 International Symposium on Physical Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3439706.3446894","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

摩尔定律的终结已经在很多场合被宣布过,我们现在可能会安全地说,我们正处于后摩尔时代。但目前还没有人准备放慢脚步。我们可以把戈登·摩尔对晶体管致密化的观察看作是长期潜在技术趋势的一个方面——库兹韦尔阐述的加速回报定律。可以说,在摩尔时代,公司变得有些自满,乐于满足于每个新流程节点带来的收益。尽管我们可以预期规模会继续扩大,尽管速度会放缓,但摩尔定律的终结为推动其他趋势提供了更强的动力。一些令人兴奋的新技术正在出现,如多芯片3D集成和新技术的引入,如存储级存储器和硅光子学。此外,我们也正在进入计算机架构创新的黄金时代。正如图灵奖得主John Hennessy和David Patterson所宣称的那样,其中一个关键驱动因素是对特定领域架构的追求。赛灵思的AI引擎就是一个很好的例子,它是Versal的重要功能之一。ACAP(自适应计算加速平台)。如今,人工智能工作负载的爆炸式增长是最强大的驱动因素之一,它将我们的注意力转移到寻找更快的方式来将数据移入、跨出加速器。诸如大规模并行处理元件、特定领域加速器的使用、分布式片上存储器和处理元件之间的密集互连等特性,都是芯片制造商超越扩展以实现下一代性能提升的方法的例子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scalable System and Silicon Architectures to Handle the Workloads of the Post-Moore Era
The end of Moore's law has been proclaimed on many occasions and it's probably safe to say that we are now working in the post-Moore era. But no one is ready to slow down just yet. We can view Gordon Moore's observation on transistor densification as just one aspect of a longer-term underlying technological trend - the Law of Accelerating Returns articulated by Kurzweil. Arguably, companies became somewhat complacent in the Moore era, happy to settle for the gains brought by each new process node. Although we can expect scaling to continue, albeit at a slower pace, the end of Moore's Law delivers a stronger incentive to push other trends harder. Some exciting new technologies are now emerging such as multi-chip 3D integration and the introduction of new technologies such as storage-class memory and silicon photonics. Moreover, we are also entering a golden age of computer architecture innovation. One of the key drivers is the pursuit of domain-specific architectures as proclaimed by Turing award winners John Hennessy and David Patterson. A good example is the Xilinx's AI Engine, one of the important features of the Versal? ACAP (adaptive compute acceleration platform). Today, the explosion of AI workloads is one of the most powerful drivers shifting our attention to find faster ways of moving data into, across, and out of accelerators. Features such as massive parallel processing elements, the use of domain specific accelerators, the dense interconnect between distributed on-chip memories and processing elements, are examples of the ways chip makers are looking beyond scaling to achieve next-generation performance gains.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信