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DTSTART:19700308T020000
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DTSTAMP:20210402T160101Z
LOCATION:Track 3
DTSTART;TZID=America/New_York:20201118T153000
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UID:submissions.supercomputing.org_SC20_sess157_pap418@linklings.com
SUMMARY:Distributed-Memory Parallel Symmetric Nonnegative Matrix Factoriza
 tion
DESCRIPTION:Paper\n\nDistributed-Memory Parallel Symmetric Nonnegative Mat
 rix Factorization\n\nEswar, Hayashi, Ballard, Kannan, Vuduc...\n\nWe devel
 op the first distributed-memory parallel implementation of Symmetric Nonne
 gative Matrix Factorization (SymNMF), a key data analytics kernel for clus
 tering and dimensionality reduction. Our implementation includes two diffe
 rent algorithms for SymNMF, which give comparable results in terms of time
  and accuracy. The first algorithm is a parallelization of an existing seq
 uential approach that uses solvers for nonsymmetric NMF. The second algori
 thm is a novel approach based on the Gauss-Newton method. It exploits seco
 nd-order information without incurring large computational and memory cost
 s. We evaluate the scalability of our algorithms on the Summit system at O
 ak Ridge National Laboratory, scaling up to 128 nodes (4096 cores) with 70
 % efficiency. Additionally, we demonstrate our software on an image segmen
 tation task.\n\nTag: Applications, Linear Algebra, Scalable Computing\n\nR
 egistration Category: Tech Program Reg Pass
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