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UID:928@lincs.fr
DTSTART;TZID=Europe/Paris:20260114T140000
DTEND;TZID=Europe/Paris:20260114T150000
DTSTAMP:20260122T114240Z
URL:https://www.lincs.fr/events/network-acceleration-for-ai-workloads/
SUMMARY:Network acceleration for AI workloads
DESCRIPTION:Network acceleration is critical for modern AI workloads\,
 particularly in optimizing communication and data transfer among
 distributed GPUs. The network has emerged as a significant bottleneck for
 Large Language Model (LLM) training and execution\, driving rapid
 advancements in GPU network technologies. This evolution\, however\,
 introduces complex research challenges spanning load balancing\, congestion
 control\, collective communications\, and novel network architectures. This
 presentation will first establish the fundamental distinctions between AI
 data centers and conventional cloud computing environments\, followed by an
 overview of ongoing research topics in this rapidly evolving field.\n\n
 \n\nBio:\nJeremie Leguay received his Ph.D. degree in computer science from
 Pierre et Marie Curie University\, Paris\, France. He is Department Head at
 Nokia Bell Labs Paris Saclay on Network Systems Research. From 2004\, he
 conducted research and led the Networking Lab at Thales Communications and
 Security (SIX GTS division) where he developed activities on sensor
 networks\, mobile networks\, and software-defined networks for
 mission-critical networked systems. In 2014\, he joined Huawei Technologies
 as leader of the Network and Traffic Optimization Team to conduct research
 activities on the planning and control of IP networks. He is Senior IEEE
 member. He has been a Senior Expert and Director of the Datacom Dijkstra
 Lab at Huawei Technologies. His current activities are mainly on Routing\,
 Network Management and Optimization\, Self-driving networks\, Automation\,
 Network for AI.
CATEGORIES:Seminars,Youtube
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TZID:Europe/Paris
X-LIC-LOCATION:Europe/Paris
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DTSTART:20251026T020000
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