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.
翻译:近年来,随着人工智能和大数据的上升,对扩大计算和记忆能力的需求更大。硅互联结构(Si-IF)是一个大型集成平台,它推动包装特性的范式转变,使超大型系统能够使用,同时大大改进通信带宽和延迟度。这些系统预计将耗尽数十千瓦的电能。为这些高功率应用设计高效和强大的电力输送方法是使Si-IF平台能够运作的关键挑战。根据若干实绩参数,高效的电力输送方法与Si-IF的三种候选应用,即人工智能加速器、高性能计算和神经形态计算相匹配。拟议的电力输送方法经过模拟,与Si-IF的相关超大型应用相兼容。模拟结果证实,专用电力输送结构可以支持SI-IF的超大规模应用。