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LOCATION:Singapore Room
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UID:submissions.pasc-conference.org_PASC22_sess173_pap112@linklings.com
SUMMARY:ChASE - A Distributed Hybrid CPU-GPU Eigensolver for Large-Scale H
 ermitian Eigenvalue Problems
DESCRIPTION:Paper\n\nChASE - A Distributed Hybrid CPU-GPU Eigensolver for 
 Large-Scale Hermitian Eigenvalue Problems\n\nWu, Davidović, Achilles, Di N
 apoli\n\nAs modern massively parallel clusters are getting larger with bee
 fier compute nodes, traditional parallel eigensolvers, such as direct solv
 ers, struggle keeping the pace with the hardware evolution and being able 
 to scale efficiently due to additional layers of communication and synchro
 nization. This difficulty is especially important when porting traditional
  libraries to heterogeneous computing architectures equipped with accelera
 tors, such as Graphics Processing Unit (GPU). Recently, there have been si
 gnificant scientific contributions to the development of filter-based subs
 pace eigensolver to compute partial eigenspectrum. The simpler structure o
 f these type of algorithms makes for them easier to avoid the communicatio
 n and synchronization bottlenecks typical of direct solvers. The Chebyshev
  Accelerated Subspace Eigensolver (ChASE) is a modern subspace eigensolver
  to compute partial extremal eigenpairs of large-scale Hermitian eigenprob
 lems with the acceleration of a filter based on Chebyshev polynomials. In 
 this work, we extend our previous work on ChASE by adding support for dist
 ributed hybrid CPU-multi-GPU computing architectures. Out tests show that 
 ChASE achieves very good scaling performance up to 144 nodes with 526 NVID
 IA A100 GPUs in total on dense eigenproblems of size up to 360k.\n\nDomain
 : Climate, Weather and Earth Sciences
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