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SUMMARY:Evaluating and Characterizing Parallel I/O in HPC Systems: Best Pr
 actices and Future Directions
DTSTART;VALUE=DATE-TIME:20211202T123000Z
DTEND;VALUE=DATE-TIME:20211202T130000Z
DTSTAMP;VALUE=DATE-TIME:20260718T084102Z
UID:indico-contribution-1484@events.chpc.ac.za
DESCRIPTION:Speakers: Sarah Neuwirth (Goethe-University Frankfurt)\nAs  a 
  recent  I/O  behaviour  analysis  [1]  has  revealed\, High Performance C
 omputing(HPC) storage systems may no longer be dominated by write I/O – 
 challenging the long- and widely-held  belief  that  HPC  workloads  are  
 write-intensive.  HPC applications are evolving to include not only tradit
 ional scale-up modelling and simulation bulk-synchronous workloads but als
 o  scale-out  workloads  [2]  like  artificial  intelligence  (AI)\,advanc
 ed  and  big  data  analytics  [3]\,  machine  learning\,  deep learning  
 [4]\,  and  complex  multi-step  workflows  [5]–[7].  Exascale  workflow
 s  are  projected  to  include  multiple  different components  from  both
   scale-up  and  scale-out  communities operating together to drive scient
 ific discovery and innovation.With the often conflicting design choices be
 tween optimizing  for  write-intensive  vs.  read-intensive  workloads\,  
 having flexible  I/O  systems  will  be  crucial  to  support  these  emer
 ging  hybrid  workloads.  Another  performance  aspect  is  the intensifyi
 ng  complexity  of  parallel  file  and  storage  systems in  large-scale 
  cluster  environments.  Storage  system  designs are  advancing  beyond  
 the  traditional  two-tiered  file  system and  archive  model  by  introd
 ucing  new  tiers  of  temporary\,fast  storage  close  to  the  computing
   resources  with  distinctly different performance characteristics. The c
 hanging landscape of   emerging   hybrid  HPC   workloads   along   with  
  the   ever increasing gap between the compute and storage performance cap
 abilities  reinforce  the  need  for  an  in-depth  understanding of extre
 me-scale parallel I/O and for rethinking existing data storage and managem
 ent evaluation techniques and strategies.In  this  talk\,  an  overview  a
 nd  taxonomy  [8]  of  the  current state-of-the-art research on large-sca
 le parallel I/O evaluation and characterization techniques in the context 
 of HPC systems is presented. Traditionally\, the process of understanding 
 large-scale  I/O  behaviour  and  performance  for  specific  applications
  or storage systems is performed iteratively and empirically in a closed l
 oop fashion\, as outlined in Figure 1\, and consists of three main phases:
  (1) Measurements and Statistics Collection\, (2) Modelling and Prediction
 \, and (3) Simulation. The overview and broad knowledge base provided by t
 his talk is invaluable to the whole scientific community\, as applications
  often observe poor  performance  due  to  bottlenecks  in  the  parallel 
  I/O  and storage system. In addition\, this talk aims to identify future 
 re-search challenges with regard to emerging exascale computing systems an
 d more complex hybrid HPC workloads.\n\nhttps://events.chpc.ac.za/event/98
 /contributions/1484/
LOCATION:
URL:https://events.chpc.ac.za/event/98/contributions/1484/
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