activity
20232026
most citedSSR: Spatial Sequential Hybrid Architecture for Latency Throughput Tradeoff in Transformer Acceleration

33 citations · 50 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CR2026

AgileOS: A GPU Operating System Layer for Protected CUDA Services

Zhuoping Yang, Yiyu Shi, Alex Jones +1

Modern GPU applications increasingly interact with storage systems, network devices, vendor libraries, and GPU-resident services rather than executing only isolated compute kernels…

cs.ET2026

Report for NSF Workshop on Algorithm-Hardware Co-design for Medical Applications

Peipei Zhou, Zheng Dong, Insup Lee +8

This report summarizes the discussions and recommendations from the NSF Workshop on Algorithm-Hardware Co-design for Medical Applications, held on September 26-27, 2024, in Pittsbu…

cs.LG2024★ 1 cited

Data-Algorithm-Architecture Co-Optimization for Fair Neural Networks on Skin Lesion Dataset

Yi Sheng, Junhuan Yang, Jinyang Li +6

As Artificial Intelligence (AI) increasingly integrates into our daily lives, fairness has emerged as a critical concern, particularly in medical AI, where datasets often reflect i…

cs.AR2024★ 33 cited

SSR: Spatial Sequential Hybrid Architecture for Latency Throughput Tradeoff in Transformer Acceleration

Jinming Zhuang, Zhuoping Yang, Shixin Ji +5

With the increase in the computation intensity of the chip, the mismatch between computation layer shapes and the available computation resource significantly limits the utilizatio…

cs.DC2024

SCARIF: Towards Carbon Modeling of Cloud Servers with Accelerators

Shixin Ji, Zhuoping Yang, Xingzhen Chen +5

Embodied carbon has been widely reported as a significant component in the full system lifecycle of various computing systems' green house gas emissions. Many efforts have been und…

cs.AR2023★ 1 cited

REFRESH FPGAs: Sustainable FPGA Chiplet Architectures

Peipei Zhou, Jinming Zhuang, Stephen Cahoon +6

There is a growing call for greater amounts of increasingly agile computational power for edge and cloud infrastructure to serve the computationally complex needs of ubiquitous com…

cs.CL2023★ 15 cited

Enabling On-Device Large Language Model Personalization with Self-Supervised Data Selection and Synthesis

Ruiyang Qin, Jun Xia, Zhenge Jia +5

After a large language model (LLM) is deployed on edge devices, it is desirable for these devices to learn from user-generated conversation data to generate user-specific and perso…