Deep learning, and machine learning in general, is taking over the world. It is, however, quite expensive to tune, train, and serve deep learning models. Naturally, improving the efficiency and performance of deep learning workflows has received significant attention (Salus, Tiresias, and Fluid to … Continue Reading ››
Tag Archives: Systems + AI
Peifeng has Phinished. Congrats Dr. Yu!
Peifeng just became my second student to finish PhD a few days ago after successfully defending his dissertation "Application-Aware Scheduling in Deep Learning Software Stacks." This will be a big loss for the SymbioticLab as we will miss his presence and deep technical insights. Peifeng is joining Google to continue working on … Continue Reading ››
FedScale Accepted to Appear at ICML’2022
Although theoretical federated learning (FL) research is growing exponentially, we are far from putting those theories into practice. Over the course of last few years, SymbioticLab has made significant progress in building deployable FL systems, with Oort being the most prominent example. As I discussed in the past, while evaluating Oort, … Continue Reading ››
Thanks Cisco for Sponsoring Our FL Research
Look forward to even more work in the context of federated learning and edge AI/ML building on top of FedScale.
Join SymbioticLab if you are excited about building practical federated learning and analytics systems that can be deployed in the wild!
FedScale Wins the Best Paper Award at ResilientFL’2021
Many congratulations to Fan, Yinwei, and Xiangfeng!
Check out FedScale at fedscale.ai
Juncheng Levels Up. Congrats Dr. Gu!
My first Ph.D. student Juncheng Gu graduated earlier this month after successfully defending his dissertation titled "Efficient Resource Management for Deep Learning Clusters." This is a bittersweet moment. While I am extremely proud of everything he has done, I will miss having him around. I do know that a bigger stage awaits … Continue Reading ››
Oort Wins the Distinguished Artifact Award at OSDI’2021. Congrats Fan and Xiangfeng!
Oort, our federated learning system for scalable machine learning over millions of edge devices has received the distinguished artifact award at this year's USENIX OSDI conference!
This is a testament to a lot of hard work put in by Fan and Xiangfeng over the course of last … Continue Reading ››
NSF Award to Expand Our Federated Learning Research!
This collaborative project with Harsha Madhyastha (Michigan) and Aditya Akella (UT Austin) aims to extend and expand our recent forays into federated learning and analytics. Join us in this adventure.
Thanks NSF for supporting our research!
FedScale Released on GitHub
Anyone working on federated learning (FL) has faced this problem at least once: you are reading two papers and they either use very different datasets for performance evaluation or unclear about their experimental assumptions about the runtime environment, or both. They often deal with very small datasets as well. There have been attempts … Continue Reading ››