activity
20142023
most citedScaling Distributed Machine Learning with In-Network Aggregation

117 citations · 174 across the 9 of their papers we have counts for

collaborators

9 papers

cs.NI2023★ 1 cited

SFC: Near-Source Congestion Signaling and Flow Control

Yanfang Le, Jeongkeun Lee, Jeremias Blendin +11

State-of-the-art congestion control algorithms for data centers alone do not cope well with transient congestion and high traffic bursts. To help with these, we revisit the concept…

cs.NI2022

Enabling the Reflex Plane with the nanoPU

Stephen Ibanez, Alex Mallery, Serhat Arslan +4

Many recent papers have demonstrated fast in-network computation using programmable switches, running many orders of magnitude faster than CPUs. The main limitation of writing soft…

cs.AR2020★ 8 cited

The nanoPU: Redesigning the CPU-Network Interface to Minimize RPC Tail Latency

Stephen Ibanez, Alex Mallery, Serhat Arslan +4

The nanoPU is a new networking-optimized CPU designed to minimize tail latency for RPCs. By bypassing the cache and memory hierarchy, the nanoPU directly places arriving messages i…

cs.CV2020★ 6 cited

Decentralized Attribution of Generative Models

Changhoon Kim, Yi Ren, Yezhou Yang

Growing applications of generative models have led to new threats such as malicious personation and digital copyright infringement. One solution to these threats is model attributi…

cs.DC2019★ 117 cited

Scaling Distributed Machine Learning with In-Network Aggregation

Amedeo Sapio, Marco Canini, Chen-Yu Ho +7

Training machine learning models in parallel is an increasingly important workload. We accelerate distributed parallel training by designing a communication primitive that uses a p…

cs.DC2019★ 19 cited

DistCache: Provable Load Balancing for Large-Scale Storage Systems with Distributed Caching

Zaoxing Liu, Zhihao Bai, Zhenming Liu +5

Load balancing is critical for distributed storage to meet strict service-level objectives (SLOs). It has been shown that a fast cache can guarantee load balancing for a clustered…