15 citations · 23 across the 7 of their papers we have counts for
7 papers
Efficient Orchestrated AI Workflows Execution on Scale-out Spatial Architecture
Jinyi Deng, Xinru Tang, Zhiheng Yue +8
Given the increasing complexity of AI applications, traditional spatial architectures frequently fall short. Our analysis identifies a pattern of interconnected, multi-faceted task…
Wafer-scale Computing: Advancements, Challenges, and Future Perspectives
Yang Hu, Xinhan Lin, Huizheng Wang +12
Nowadays, artificial intelligence (AI) technology with large models plays an increasingly important role in both academia and industry. It also brings a rapidly increasing demand f…
WindMill: A Parameterized and Pluggable CGRA Implemented by DIAG Design Flow
Haojia Hui, Jiangyuan Gu, Xunbo Hu +4
With the cross-fertilization of applications and the ever-increasing scale of models, the efficiency and productivity of hardware computing architectures have become inadequate. Th…
Towards Efficient Control Flow Handling in Spatial Architecture via Architecting the Control Flow Plane
Jinyi Deng, Xinru Tang, Jiahao Zhang +9
Spatial architecture is a high-performance architecture that uses control flow graphs and data flow graphs as the computational model and producer/consumer models as the execution…
HQNAS: Auto CNN deployment framework for joint quantization and architecture search
Hongjiang Chen, Yang Wang, Leibo Liu +2
Deep learning applications are being transferred from the cloud to edge with the rapid development of embedded computing systems. In order to achieve higher energy efficiency with…
FAQS: Communication-efficient Federate DNN Architecture and Quantization Co-Search for personalized Hardware-aware Preferences
Hongjiang Chen, Yang Wang, Leibo Liu +2
Due to user privacy and regulatory restrictions, federate learning (FL) is proposed as a distributed learning framework for training deep neural networks (DNN) on decentralized dat…
Small-footprint Keyword Spotting with Graph Convolutional Network
Xi Chen, Shouyi Yin, Dandan Song +3
Despite the recent successes of deep neural networks, it remains challenging to achieve high precision keyword spotting task (KWS) on resource-constrained devices. In this study, w…