Power Delivery for Ultra-Large-Scale Applications on Si-IF

TL;DR

This paper proposes and simulates dedicated power delivery methods for ultra-large-scale systems on Si-IF, addressing the challenge of high power dissipation in AI, HPC, and neuromorphic computing applications.

Contribution

It introduces tailored power delivery topologies for Si-IF, validated through simulations for different high-power applications.

Findings

Power delivery topologies support ultra-large-scale applications on Si-IF

Simulations confirm compatibility with AI, HPC, neuromorphic computing

Proposed methods improve power efficiency and robustness

Abstract

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.