4 citations · 4 across the 7 of their papers we have counts for
8 papers
The Multipath Reliable Connection (MRC) Transport
Rip Sohan, Eric Spada, Eric Davis +36
MRC is an open, production-grade transport designed for large-scale AI/ML training over best-effort Ethernet. It extends RoCEv2 with explicit, composable primitives for per-packet…
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…
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…
Finetuning a Weather Foundation Model with Lightweight Decoders for Unseen Physical Processes
Fanny Lehmann, Firat Ozdemir, Benedikt Soja +3
Recent advances in AI weather forecasting have led to the emergence of so-called "foundation models", typically defined by expensive pretraining and minimal fine-tuning for downstr…
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…
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…
SDR-RDMA: Software-Defined Reliability Architecture for Planetary Scale RDMA Communication
Mikhail Khalilov, Siyuan Shen, Marcin Chrapek +16
RDMA is vital for efficient distributed training across datacenters, but millisecond-scale latencies complicate the design of its reliability layer. We show that depending on long-…
Fortify Your Foundations: Practical Privacy and Security for Foundation Model Deployments In The Cloud
Marcin Chrapek, Anjo Vahldiek-Oberwagner, Marcin Spoczynski +3
Foundation Models (FMs) display exceptional performance in tasks such as natural language processing and are being applied across a growing range of disciplines. Although typically…