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20232026
most citedExploring GPU-to-GPU Communication: Insights into Supercomputer Interconnects

22 citations · 55 across the 10 of their papers we have counts for

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5 papers · 1 filter

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

PICO: Performance Insights for Collective Operations

Saverio Pasqualoni, Tommaso Bonato, Lorenzo Piarulli +3

Collective operations are cornerstones of both HPC applications and large-scale AI training and inference, yet benchmarking them in a systematic and reproducible way remains diffic…

cs.DC2024★ 22 cited

Exploring GPU-to-GPU Communication: Insights into Supercomputer Interconnects

Daniele De Sensi, Lorenzo Pichetti, Flavio Vella +11

Multi-GPU nodes are increasingly common in the rapidly evolving landscape of exascale supercomputers. On these systems, GPUs on the same node are connected through dedicated networ…

cs.DC2024★ 7 cited

Near-Optimal Wafer-Scale Reduce

Piotr Luczynski, Lukas Gianinazzi, Patrick Iff +3

Efficient Reduce and AllReduce communication collectives are a critical cornerstone of high-performance computing (HPC) applications. We present the first systematic investigation…

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…