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TZOFFSETFROM:-0700
TZOFFSETTO:-0600
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DTSTART:19700308T020000
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DTSTART:19701101T020000
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DTSTAMP:20260422T000713Z
LOCATION:405
DTSTART;TZID=America/Denver:20231112T083000
DTEND;TZID=America/Denver:20231112T170000
UID:submissions.supercomputing.org_SC23_sess227_tut102@linklings.com
SUMMARY:Fault-Tolerance for High-Performance and Big Data Applications: Th
 eory and Practice
DESCRIPTION:George Bosilca, Aurelien Bouteiller, and Thomas Herault (Unive
 rsity of Tennessee) and Yves Robert (ENS Lyon, Univ. Tennessee Knoxville)\
 n\nResilience is a critical issue for large-scale platforms. This tutorial
  provides a comprehensive survey of fault-tolerant techniques for high-per
 formance and big data applications, with a fair balance between theory and
  practice. This tutorial is organized across four main topics:\n\n   (i)  
 Overview of failure types (software/hardware, transient/fail-stop), and ty
 pical probability distributions (Exponential, Weibull, Log-Normal);\n\n   
 (ii)  General-purpose techniques, which include several checkpoints and ro
 llback recovery protocols, replication, prediction, and silent error detec
 tion;\n\n   (iii)  Application-specific techniques, such as user-level in-
 memory checkpointing, data replication (map-reduce), or fixed-point conver
 gence for iterative applications (back-propagation);\n\n   (iv)  Practical
  deployment of fault tolerance techniques with User Level Fault Mitigation
  (MPI standard extension). Relevant examples will include widely used rout
 ines such as Monte-Carlo methods, SPMD stencil, map-reduce, and back-propa
 gation in neural networks.\n\nA step-by-step approach will  show how to pr
 otect these routines and make them fault-tolerant, using a variety of tech
 niques, in a hands-on session.\n\nThe tutorial is open to all SC23 attende
 es who are interested in the current status and expected promise of fault-
 tolerant approaches for scientific and big data applications. There are no
  audience prerequisites: background will be provided for all protocols and
  probabilistic models.  However, basic knowledge of MPI will be helpful fo
 r the hands-on session.\n\nTag: Algorithms, Data Movement and Memory, Faul
 t Handling and Tolerance\n\nRegistration Category: Tutorial Reg Pass\n\n
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