Challenges and Opportunities to Enable Large-Scale Computing via Heterogeneous Chiplets
Challenges and Opportunities to Enable Large-Scale Computing via Heterogeneous Chiplets
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DOI：
10.1109/asp-dac58780.2024.10473961
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发表时间：
2023-11
期刊：
影响因子：
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通讯作者：
Zhuoping Yang;Shixin Ji;Xingzhen Chen;Jinming Zhuang;Weifeng Zhang;Dharmesh Jani;Peipei Zhou
中科院分区：
文献类型：
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作者：
Zhuoping Yang;Shixin Ji;Xingzhen Chen;Jinming Zhuang;Weifeng Zhang;Dharmesh Jani;Peipei Zhou
快速发展的人工智能（AI）算法（例如大型语言模型）在当今的数据中心中推动了不断增长的计算需求。尤其是，异质的chiplet体系结构不断扩大和扩展系统，并降低了设计的复杂性以及传统的单片芯片设计的成本。在本文中，我们首先讨论了不同的AI工作量的多样性和不断发展的需求。问题。
Fast-evolving artificial intelligence (AI) algorithms such as large language models have been driving the ever-increasing computing demands in today’s data centers. Heterogeneous computing with domain-specific architectures (DSAs) brings many opportunities when scaling up and scaling out the computing system. In particular, heterogeneous chiplet architecture is favored to keep scaling up and scaling out the system as well as to reduce the design complexity and the cost stemming from the traditional monolithic chip design. However, how to interconnect computing resources and orchestrate heterogeneous chiplets is the key to success. In this paper, we first discuss the diversity and evolving demands of different AI workloads. We discuss how chiplet brings better cost efficiency and shorter time to market. Then we discuss the challenges in establishing chiplet interface standards, packaging, and security issues. We further discuss the software programming challenges in chiplet systems.