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DTSTAMP:20250626T234542Z
LOCATION:B206
DTSTART;TZID=America/New_York:20241122T091500
DTEND;TZID=America/New_York:20241122T093000
UID:submissions.supercomputing.org_SC24_sess769_ws_adugai107@linklings.com
SUMMARY:Enabling cross-Facility LLM pre-Training
DESCRIPTION:Gianluca Mittone, Alberto Mulone, Iacopo Colonnelli, Robert Bi
 rke, and Marco Aldinucci (University of Turin, Italy)\n\nBig-tech companie
 s pre-train SOTA LLMs on special-purpose, private HPCs, while public resea
 rch centres lack the resources to compete. We advocate a new take on large
  model training, e.g., LLMs, called xFFL, which leverages federated learni
 ng as an enabling technique to exploit geographically distributed computin
 g power to bridge such digital divide. This work introduces a proof-of-con
 cept federated training of LLaMA-3 8B on three EuroHPC Top500 facilities, 
 proving the viability of leveraging cross-facility publicly available comp
 utational power to sustain SOTA LLM workloads.\n\nTag: Artificial Intellig
 ence/Machine Learning\n\nRegistration Category: Workshop Reg Pass\n\nSessi
 on Chairs: Charlie Catlett (Argonne National Laboratory (ANL), University 
 of Chicago); Fabrizio Gagliardi (Barcelona Supercomputing Center (BSC), As
 sociation for Computing Machinery (ACM)); Neeraj Kumar (Pacific Northwest 
 National Laboratory (PNNL)); Satoshi Matsuoka (RIKEN, Tokyo Institute of T
 echnology); Irina Rish (University of Montreal, Canada; Mila – Quebec AI I
 nstitute); Rick Stevens (Argonne National Laboratory (ANL), University of 
 Chicago); and Valerie Taylor (Argonne National Laboratory (ANL), Universit
 y of Chicago)\n\n
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