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UID:submissions.supercomputing.org_SC22_sess275_rpost160@linklings.com
SUMMARY:Low-Precision Multi-GPU Detection Approach for Massive MIMO Techno
 logy
DESCRIPTION:Posters, Research Posters\n\nLow-Precision Multi-GPU Detection
  Approach for Massive MIMO Technology\n\nDabah, Ltaief, Rezki, Alouini, Ke
 yes\n\nMassive Multiple-Input-Multiple-Output is a crucial technology for 
 Next-Generation networks (Next-G). It uses hundreds of antennas at transce
 ivers to exchange data. However, its accurate signal detection relies on s
 olving an NP-hard optimization problem in real-time latency.\n\nIn this po
 ster, we propose a new GPU-based detection algorithm that demonstrates the
  positive impact of low-precision arithmetic with multiple GPUs to achieve
  next-G latency/scalability/accuracy requirements.  Our approach iterative
 ly extends a solution with several symbols representing the best combinati
 on out of the aggregated levels.  The computation at each iteration is for
 mulated as a matrix multiplication operation to leverage GPU architectures
 . \n\nThe obtained results using A100 GPU show a 1.7x improvement by explo
 iting half-precision arithmetic without loss in accuracy. Furthermore, our
  low-precision multi-GPU version with four A100 GPUs is 4x faster than the
  single-precision single GPU version and 40x faster than a similar paralle
 l CPU implementation executed on a two-socket 28-core IceLake CPU with 56 
 threads.\n\nRegistration Category: Tech Program Reg Pass, Exhibits Reg Pas
 s
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