activity
20102022
most citedpCAMP: Performance Comparison of Machine Learning Packages on the Edges

50 citations · 155 across the 23 of their papers we have counts for

collaborators
Showing cs.DCShow all

14 papers · 1 filter

cs.DC2021★ 2 cited

4C: A Computation, Communication, and Control Co-Design Framework for CAVs

Liangkai Liu, Shaoshan Liu, Weisong Shi

Connected and autonomous vehicles (CAVs) are promising due to their potential safety and efficiency benefits and have attracted massive investment and interest from government agen…

cs.DC2021

Revisiting the Arguments for Edge Computing Research

Blesson Varghese, Eyal de Lara, Aaron Ding +8

This article argues that low latency, high bandwidth, device proliferation, sustainable digital infrastructure, and data privacy and sovereignty continue to motivate the need for e…

cs.DC2020★ 25 cited

Computing Systems for Autonomous Driving: State-of-the-Art and Challenges

Liangkai Liu, Sidi Lu, Ren Zhong +4

The recent proliferation of computing technologies (e.g., sensors, computer vision, machine learning, and hardware acceleration), and the broad deployment of communication mechanis…

cs.DC2020

A Case For Adaptive Deep Neural Networks in Edge Computing

Francis McNamee, Schahram Dustadar, Peter Kilpatrick +3

Edge computing offers an additional layer of compute infrastructure closer to the data source before raw data from privacy-sensitive and performance-critical applications is transf…

cs.DC2020★ 2 cited

A Survey on Edge Performance Benchmarking

Blesson Varghese, Nan Wang, David Bermbach +4

Edge computing is the next Internet frontier that will leverage computing resources located near users, sensors, and data stores to provide more responsive services. Therefore, it…

cs.DC2019★ 50 cited

pCAMP: Performance Comparison of Machine Learning Packages on the Edges

Xingzhou Zhang, Yifan Wang, Weisong Shi

Machine learning has changed the computing paradigm. Products today are built with machine intelligence as a central attribute, and consumers are beginning to expect near-human int…