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UID:submissions.supercomputing.org_SC24_sess633_bof213@linklings.com
SUMMARY:Can Python Do for HPC What It Did for Machine Learning?
DESCRIPTION:George Biros (University of Texas, Oden Institute); Rosa Badia
  (Barcelona Supercomputing Center (BSC)); Elliott Slaughter (SLAC National
  Accelerator Laboratory); Mattan Erez and Milos Gligoric (The University o
 f Texas at Austin); and Harald Koestler (Friedrich-Alexander University, E
 rlangen-Nuremberg)\n\nPython is now one of the most popular programming la
 nguages. In HPC, it has predominantly been used to coordinate coarse-grain
  library components or workflows. However, it is increasingly being used t
 o develop and coordinate applications with dynamic finer-grain components 
 that are challenging to map efficiently onto heterogeneous resources. In t
 his BoF, we discuss this challenge and efforts to design Python-based HPC,
  production quality codes for HPC leadership platforms. We will discuss is
 sues such as multithreading, GPU kernel development, task-based coordinati
 on on heterogeneous systems with a mix of CPUs and GPUs, inter-node intero
 perability, scalability, portability, and reproducibility.\n\nRegistration
  Category: Tech Program Reg Pass, Exhibits Reg Pass\n\n
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