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DTSTART;TZID=America/Denver:20231112T152500
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UID:submissions.supercomputing.org_SC23_sess427_ws_scsc101@linklings.com
SUMMARY:Checkpoint/Restart for CUDA Kernels
DESCRIPTION:Niklas Eiling, Stefan Lankes, and Antonello Monti (RWTH Aachen
  University)\n\nIn HPC clusters, it has become common to employ Checkpoint
 /Restart, that is, saving the execution state of applications in order to 
 restore their computational progress at a later point in time. The benefit
 s of this technique for clusters include more flexibility when reacting to
  changing workloads and an increased fault tolerance. While many clusters 
 already benefit from C/R tools for traditional CPU applications, there is 
 a lack of comparable tools enabling preemptive and transparent C/R for het
 erogeneous computing, where applications execute partly on accelerator dev
 ices, such as GPUs. This is despite the increasing use of GPUs as accelera
 tors in HPC clusters. Therefore, we propose a novel C/R tool that enables 
 saving the execution state of CUDA kernels, thus allowing preemptive C/R o
 f GPU. We show that full-featured C/R for NVIDIA GPUs is possible despite 
 the proprietary nature of the hardware and software of these devices.\n\nT
 ag: Fault Handling and Tolerance\n\nRegistration Category: Workshop Reg Pa
 ss\n\nSession Chairs: Gene Cooperman (Northeastern University); Donglai Da
 i (Advanced Micro Devices (AMD)); Rebecca Hartman-Baker (National Energy R
 esearch Scientific Computing Center (NERSC), Lawrence Berkeley National La
 boratory (LBNL)); and Bogdan Nicolae (Argonne National Laboratory (ANL), I
 llinois Institute of Technology)\n\n
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