12 citations · 42 across the 12 of their papers we have counts for
12 papers
m4: A Learned Flow-level Network Simulator
Chenning Li, Anton A. Zabreyko, Arash Nasr-Esfahany +4
Flow-level simulation is widely used to model large-scale data center networks due to its scalability. Unlike packet-level simulators that model individual packets, flow-level simu…
Fast Userspace Networking for the Rest of Us
Alireza Sanaee, Vahab Jabrayilov, Ilias Marinos +5
After a decade of research in userspace network stacks, why do new solutions remain inaccessible to most developers? We argue that this is because they ignored (1) the hardware con…
Ethereal: Divide and Conquer Network Load Balancing in Large-Scale Distributed Training
Vamsi Addanki, Prateesh Goyal, Ilias Marinos +1
Large-scale distributed training in production datacenters constitutes a challenging workload bottlenecked by network communication. In response, both major industry players (e.g.,…
DBO: Response Time Fairness for Cloud-Hosted Financial Exchanges
Prateesh Goyal, Eashan Gupta, Ilias Marinos +3
In this paper, we consider the problem of hosting financial exchanges in the cloud. Financial exchanges require predictable, equal latency to all market participants to ensure fair…
Scalable Tail Latency Estimation for Data Center Networks
Kevin Zhao, Prateesh Goyal, Mohammad Alizadeh +1
In this paper, we consider how to provide fast estimates of flow-level tail latency performance for very large scale data center networks. Network tail latency is often a crucial m…
Optimal Congestion Control for Time-varying Wireless Links
Prateesh Goyal, Mohammad Alizadeh, Thomas E. Anderson
Modern networks exhibit a high degree of variability in link rates. Cellular network bandwidth inherently varies with receiver motion and orientation, while class-based packet sche…