39 citations · 54 across the 15 of their papers we have counts for
6 papers · 1 filter
Finding Adversarial Inputs for Heuristics using Multi-level Optimization
Pooria Namyar, Behnaz Arzani, Ryan Beckett +5
Production systems use heuristics because they are faster or scale better than their optimal counterparts. Yet, practitioners are often unaware of the performance gap between a heu…
Solving Max-Min Fair Resource Allocations Quickly on Large Graphs
Pooria Namyar, Behnaz Arzani, Srikanth Kandula +5
We consider the max-min fair resource allocation problem. The best-known solutions use either a sequence of optimizations or waterfilling, which only applies to a narrow set of cas…
Enhancing Network Management Using Code Generated by Large Language Models
Sathiya Kumaran Mani, Yajie Zhou, Kevin Hsieh +3
Analyzing network topologies and communication graphs plays a crucial role in contemporary network management. However, the absence of a cohesive approach leads to a challenging le…
Rethinking Machine Learning Collective Communication as a Multi-Commodity Flow Problem
Behnaz Arzani, Siva Kesava Reddy Kakarla, Miguel Castro +3
We show communication schedulers' recent work proposed for ML collectives does not scale to the increasing problem sizes that arise from training larger models. These works also of…
Enhancing Network Failure Mitigation with Performance-Aware Ranking
Pooria Namyar, Arvin Ghavidel, Daniel Crankshaw +5
Cloud providers install mitigations to reduce the impact of network failures within their datacenters. Existing network mitigation systems rely on simple local criteria or global p…
A Deep Learning Perspective on Network Routing
Yarin Perry, Felipe Vieira Frujeri, Chaim Hoch +4
Routing is, arguably, the most fundamental task in computer networking, and the most extensively studied one. A key challenge for routing in real-world environments is the need to…