This week, I presented a keynote talk at the DistributedML'21 workshop on our recent works on building software systems support for practical federated computation (Sol, Oort, and FedScale). This is a longer version of my talk at Google FL workshop last month, and the updated slides go into more … Continue Reading ››
All posts by Mosharaf
Presented a Keynote at 2021 Workshop on Federated Learning and Analytics
Recently I presented a keynote talk at the 2021 federated learning and analytics workshop organized Google on our recent works on building software systems support for practical federated computation (Sol, Oort, and FedScale).
I based my talk around the similarities … Continue Reading ››
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!
Justitia Accepted to Appear at NSDI’2022
The need for higher throughput and lower latency is driving kernel-bypass networking (KBN) in datacenters. Of the two related trends in KBN, hardware-based KBN is especially challenging because, unlike software KBN such as DPDK, it does not provide any control once a request is posted to the hardware. RDMA, which is the … Continue Reading ››
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 ››
AIFO Accepted to Appear at SIGCOMM’2021
Packet scheduling is a classic problem in networking. In recent years, however, the focus on packet scheduling has somewhat shifted from designing new scheduling algorithms to designing generalized frameworks that can be programmed to approximate a variety of scheduling disciplines. Push-In-First-Out (PIFO) from SIGCOMM 2016 is such a framework that has been shown … Continue Reading ››
Treehouse Funded. Thanks NSF and VMware!
Treehouse, our proposal on energy-first software infrastructure designs for sustainable cloud computing has recently won a three million dollar joint funding from NSF and VMware! Here is a link to the VMware press release. SymbioticLab now has a chance to collaborate with a stellar team consisting of Tom Anderson, … Continue Reading ››