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DTSTAMP:20250822T115808Z
LOCATION:Room 6.0D13
DTSTART;TZID=Europe/Stockholm:20250618T153000
DTEND;TZID=Europe/Stockholm:20250618T160000
UID:submissions.pasc-conference.org_PASC25_sess142_msa103@linklings.com
SUMMARY:What and How Would we Build the Future Eigenvalue Solver?
DESCRIPTION:Toshiyuki Imamura (RIKEN)\n\nIn the Japanese computational sci
 ence community, which has developed the K computer and Fugaku, the high de
 mand for large-scale eigenvalue calculations in condensed material science
  has prompted updates to numerical software. Capability Computing is a cru
 cial method for effectively addressing challenging large-scale systems and
  is a standard scientific tool. On the other hand, an evolving approach is
  also essential from the perspective of Capacity Computing, which manages 
 large batches of eigenvalue computations. We aim to develop statistical, e
 nsemble, and AI-enabled computational frameworks that leverage advanced ap
 proximation algorithms, cutting-edge system runtimes, and software framewo
 rks such as Kokkos, IRIS, C++, Python, and Julia. Our goal is to discuss t
 he development of the solver and present a roadmap that connects the creat
 ion of next-generation mathematical software with this framework and next-
 generation computers, encouraging participants to engage in conversation.\
 n\nDomain: Engineering, Computational Methods and Applied Mathematics\n\nS
 ession Chair: Het Yagnesh Mankad (Oak Ridge National Laboratory)\n\n
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