Low-Power Scalable TSPI: A Modular Off-Chip Network for Edge AI Accelerators

Citations

WEB OF SCIENCE

1
Citations

SCOPUS

2

초록

In this paper, we present a novel off-chip network architecture, the Tile Serial Peripheral Interface (TSPI), designed for low-power, scalable edge AI accelerators. Our approach modifies the conventional SPI to support a modular network structure that facilitates the scalable connection of multiple accelerators. The TSPI network employs a subset mapping algorithm for efficient routing and integrates the message passing interface (MPI) protocol to ensure rapid data distribution and aggregation. This modular architecture significantly reduces power consumption and improves processing speed. Experimental results demonstrate that our proposed TSPI network achieves a 54.7% reduction in power consumption and an 82.3% decrease in switching power compared to traditional SPI networks, along with a 23% increase in processing speed when utilizing 16 nodes. These advancements make the TSPI network an effective solution for enhancing AI performance in edge computing environments.

키워드

Random access memory; Computational modeling; Performance evaluation; Edge AI; Distributed databases; Scalability; Indexes; Low power electronics; Network architecture; Accelerator architectures; TSPI; off-chip network; edge device; subset mapping algorithm; low power; MPI
제목
Low-Power Scalable TSPI: A Modular Off-Chip Network for Edge AI Accelerators
저자
Park, Seunghyun; Park, Daejin
DOI
10.1109/ACCESS.2024.3466965
발행일
2024-09
유형
Article
저널명
IEEE Access
권
12
페이지
141448 ~ 141459