论文标题
超大规模申请的电力传递
Power Delivery for Ultra-Large-Scale Applications on Si-IF
论文作者
论文摘要
近年来，随着人工智能和大数据的兴起，对扩展计算能力和记忆力的需求更大。晶体互连织物（SI-IF）是一个晶圆尺度的集成平台，可促进包装功能的范式转移，并启用超大规模的系统，同时显着改善通信带宽和延迟。预计此类系统将耗散数十千瓦的功率。为这些高功率应用设计有效且强大的动力传递方法是SI-IF平台的启用的关键挑战。基于几个合格参数，有效的动力传递方法与SI-IF上的三个候选应用程序中的每一个相匹配，即人工智能加速器，高性能计算和神经形态计算。模拟了所提出的电力输送方法，并与SI-IF上相关的超大规模应用表现出兼容性。仿真结果证实，专用的电力输送拓扑可以支持SI-IF上的超大规模应用。
In recent years, with the rise of artificial intelligence and big data, there is an even greater demand for scaling out computing and memory capacity. Silicon interconnect fabric (Si-IF), a wafer-scale integration platform, promotes a paradigm shift in packaging features and enables ultra-large-scale systems, while significantly improving communication bandwidth and latency. Such systems are expected to dissipate tens of kilowatts of power. Designing an efficient and robust power delivery methodology for these high power applications is a key challenge in the enablement of the Si-IF platform. Based on several figure-of-merit parameters, an efficient power delivery methodology is matched with each of three candidate applications on the Si-IF, namely, artificial intelligence accelerators, high-performance computing, and neuromorphic computing. The proposed power delivery approaches were simulated and exhibit compatibility with the relevant ultra-large-scale application on Si-IF. The simulation results confirm that the dedicated power delivery topologies can support ultra-large-scale applications on the SI-IF.
