activity
20222026
most citedREPS: Recycled Entropy Packet Spraying for Adaptive Load Balancing and Failure Mitigation

11 citations · 25 across the 10 of their papers we have counts for

collaborators

12 papers

cs.NI2026

PCM: Programmable Congestion Management for Terabit RDMA NICs

Mikhail Khalilov, Timo Schneider, Tommaso Bonato +10

Datacenter congestion control (CC) and load balancing (LB) evolve rapidly as workload demands change, but deployment depends on RDMA hardware and transport interfaces. Emerging pro…

cs.AR2026

Network Design for Wafer-Scale Systems with Wafer-on-Wafer Hybrid Bonding

Patrick Iff, Tommaso Bonato, Maciej Besta +2

Transformer-based large language models are increasingly constrained by data movement as communication bandwidth drops sharply beyond the chip boundary. Wafer-scale integration usi…

cs.NI2026

Spritz: Path-Aware Load Balancing in Low-Diameter Networks

Tommaso Bonato, Ales Kubicek, Abdul Kabbani +3

Low-diameter topologies such as Dragonfly and Slim Fly are increasingly adopted in HPC and datacenter networks, yet existing load balancing techniques either rely on proprietary in…

cs.NI2025★ 7 cited

Uno: A One-Stop Solution for Inter- and Intra-Datacenter Congestion Control and Reliable Connectivity

Tommaso Bonato, Sepehr Abdous, Abdul Kabbani +11

Cloud computing and AI workloads are driving unprecedented demand for efficient communication within and across datacenters. However, the coexistence of intra- and inter-datacenter…

cs.DC2025★ 4 cited

Bine Trees: Enhancing Collective Operations by Optimizing Communication Locality

Daniele De Sensi, Saverio Pasqualoni, Lorenzo Piarulli +5

Communication locality plays a key role in the performance of collective operations on large HPC systems, especially on oversubscribed networks where groups of nodes are fully conn…

cs.DC2025

Demystifying NCCL: An In-depth Analysis of GPU Communication Protocols and Algorithms

Zhiyi Hu, Siyuan Shen, Tommaso Bonato +6

The NVIDIA Collective Communication Library (NCCL) is a critical software layer enabling high-performance collectives on large-scale GPU clusters. Despite being open source with a…

cs.NI2025

Flowcut Switching: High-Performance Adaptive Routing with In-Order Delivery Guarantees

Tommaso Bonato, Daniele De Sensi, Salvatore Di Girolamo +4

Network latency severely impacts the performance of applications running on supercomputers. Adaptive routing algorithms route packets over different available paths to reduce laten…

cs.DC2025

ATLAHS: An Application-centric Network Simulator Toolchain for AI, HPC, and Distributed Storage

Siyuan Shen, Tommaso Bonato, Zhiyi Hu +3

Network simulators play a crucial role in evaluating the performance of large-scale systems. However, existing simulators rely heavily on synthetic microbenchmarks or narrowly focu…

cs.NI2024★ 11 cited

REPS: Recycled Entropy Packet Spraying for Adaptive Load Balancing and Failure Mitigation

Tommaso Bonato, Abdul Kabbani, Ahmad Ghalayini +7

Next-generation datacenters require highly efficient network load balancing to manage the growing scale of artificial intelligence (AI) training and general datacenter traffic. How…

cs.NI2024

SMaRTT: Sender-based Marked Rapidly-adapting Trimmed & Timed Transport

Tommaso Bonato, Abdul Kabbani, Ahmad Ghalayini +10

With the rapid growth of artificial intelligence (AI) workloads in datacenters, the Ultra Ethernet Consortium (UEC) has defined a new high-performance transport layer to deliver th…

cs.DC2024★ 3 cited

Swing: Short-cutting Rings for Higher Bandwidth Allreduce

Daniele De Sensi, Tommaso Bonato, David Saam +1

The allreduce collective operation accounts for a significant fraction of the runtime of workloads running on distributed systems. One factor determining its performance is the dis…

cs.DC2022

HammingMesh: A Network Topology for Large-Scale Deep Learning

Torsten Hoefler, Tommaso Bonato, Daniele De Sensi +7

Numerous microarchitectural optimizations unlocked tremendous processing power for deep neural networks that in turn fueled the AI revolution. With the exhaustion of such optimizat…