Masoud Moshref Javadi



I'm an architect in Nvidia. Before in Google, I worked on kernel bypass networking and offloaded RDMA traffic for cloud, search, storage and large language models ML products. I led the congestion control and some host performance debugging efforts for these networking stacks.

I worked at Barefoot Networks as a software engineer in the Advanced App team. I used the programmable switching hardware in non-traditional networking applications such as Deep Insight, In-network DDoS Detection, Matching string queries, Packet subscription and Machine learning acceleration.

I got my PhD degree in Computer Engineering at USC under supervision of Ramesh Govindan and Minlan Yu in NSL from Fall 2010. I defended in July 2016, and my dissertation is about developing timely, accurate and scalable network management systems. Such systems allow operators to define high level intents and leverage efficient algorithms at the controller, switches and end-hosts. These algorithms can quickly fine tune the switches and end-hosts to keep high accuracy, drill down fast into issues, and leverage device optimizations and network knowledge to scale. I developed four systems: vCRIB (NSDI'13), DREAM (SIGCOMM'14), SCREAM (CoNEXT'15) and Trumpet (SIGCOMM'16). I got B.Sc. and M.Sc. degrees in Information Technology Engineering in 2007 and 2010 from Sharif University of Technology (Tehran, Iran).


2/22/2023 I'm excited to pursue the next step of my career in Nvidia.
9/2/2022 Congestion control is not only for fabric. Our HotNets'22 paper explains host inter-connect bottlenecks.
7/11/2022 Finally, a place for INT to shine: See Poseidon: Efficient, Robust, and Practical Datacenter Congestion Control via Deployable INT in NSDI'23
5/9/2022 PLB balances the network load over paths using only congestion signals at host. See SIGCOMM'22 experience track
12/11/2020 How programmable switches can speed-up ML? Check our paper in NSDI'21

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