15 citations · 67 across the 12 of their papers we have counts for
12 papers
Torpor: GPU-Enabled Serverless Computing for Low-Latency, Resource-Efficient Inference
Minchen Yu, Ao Wang, Dong Chen +8
Serverless computing offers a compelling cloud model for online inference services. However, existing serverless platforms lack efficient support for GPUs, hindering their ability…
Dordis: Efficient Federated Learning with Dropout-Resilient Differential Privacy
Zhifeng Jiang, Wei Wang, Ruichuan Chen
Federated learning (FL) is increasingly deployed among multiple clients to train a shared model over decentralized data. To address privacy concerns, FL systems need to safeguard t…
SMLT: A Serverless Framework for Scalable and Adaptive Machine Learning Design and Training
Ahsan Ali, Syed Zawad, Paarijaat Aditya +3
In today's production machine learning (ML) systems, models are continuously trained, improved, and deployed. ML design and training are becoming a continuous workflow of various t…
Following the Data, Not the Function: Rethinking Function Orchestration in Serverless Computing
Minchen Yu, Tingjia Cao, Wei Wang +1
Serverless applications are typically composed of function workflows in which multiple short-lived functions are triggered to exchange data in response to events or state changes.…
Citadel: Protecting Data Privacy and Model Confidentiality for Collaborative Learning with SGX
Chengliang Zhang, Junzhe Xia, Baichen Yang +6
With the advancement of machine learning (ML) and its growing awareness, many organizations who own data but not ML expertise (data owner) would like to pool their data and collabo…
Approximate Distributed Joins in Apache Spark
Do Le Quoc, Istemi Ekin Akkus, Pramod Bhatotia +4
The join operation is a fundamental building block of parallel data processing. Unfortunately, it is very resource-intensive to compute an equi-join across massive datasets. The ap…