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DTSTAMP:20250822T115810Z
LOCATION:Room 5.2D02
DTSTART;TZID=Europe/Stockholm:20250618T103000
DTEND;TZID=Europe/Stockholm:20250618T110000
UID:submissions.pasc-conference.org_PASC25_sess106_msa270@linklings.com
SUMMARY:Precision Redefined: Unlocking and Delivering the Full Power of Mo
 dern GPUs for Scientific Computing
DESCRIPTION:Harun Bayraktar (NVIDIA)\n\nOver the last decade GPU architect
 ures have dramatically improved in both performance and energy efficiency.
   Due largely to the rising importance of artificial intelligence (AI), es
 pecially in the areas of large language models (LLMs) and generative AI, t
 his growth has been most pronounced in reduced precision matrix multiplica
 tion capacity, where the introduction of Tensor Cores and new datatypes ha
 s sparked a wave of innovative techniques at the juncture of AI and scient
 ific computing.  In addition to extending the reach and impact of mixed-pr
 ecision algorithms, these hardware riches have sparked the development of 
 new floating point emulation algorithms across a wide range of precisions,
  including but not limited to single- and double-precision.  In this talk,
  we will look at the accuracy, performance, and energy efficiency of these
  methods and provide insights into the challenges and opportunities involv
 ed in making them broadly available to the scientific computing community.
 \n\nDomain: Computational Methods and Applied Mathematics\n\nSession Chair
 : Mantas Mikaitis (University of Leeds)\n\n
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