3 citations · 5 across the 4 of their papers we have counts for
4 papers
Dubhe: Towards Data Unbiasedness with Homomorphic Encryption in Federated Learning Client Selection
Shulai Zhang, Zirui Li, Quan Chen +3
Federated learning (FL) is a distributed machine learning paradigm that allows clients to collaboratively train a model over their own local data. FL promises the privacy of client…
DLFusion: An Auto-Tuning Compiler for Layer Fusion on Deep Neural Network Accelerator
Zihan Liu, Jingwen Leng, Quan Chen +4
Many hardware vendors have introduced specialized deep neural networks (DNN) accelerators owing to their superior performance and efficiency. As such, how to generate and optimize…
Towards QoS-Aware and Resource-Efficient GPU Microservices Based on Spatial Multitasking GPUs In Datacenters
Wei Zhang, Quan Chen, Kaihua Fu +6
While prior researches focus on CPU-based microservices, they are not applicable for GPU-based microservices due to the different contention patterns. It is challenging to optimize…
URSA: Precise Capacity Planning and Contention-aware Scheduling for Public Clouds
Ningxin Zheng, Quan Chen, Yong Yang +4
Database platform-as-a-service (dbPaaS) is developing rapidly and a large number of databases have been migrated to run on the Clouds for the low cost and flexibility. Emerging Clo…