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      Exploiting locality in sparse matrix-matrix multiplication on many-core rchitectures

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      Author(s)
      Akbudak K.
      Aykanat, Cevdet
      Date
      2017
      Source Title
      IEEE Transactions on Parallel and Distributed Systems
      Print ISSN
      1045-9219
      Publisher
      IEEE Computer Society
      Volume
      28
      Issue
      8
      Pages
      2258 - 2271
      Language
      English
      Type
      Article
      Item Usage Stats
      230
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      329
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      Abstract
      Exploiting spatial and temporal localities is investigated for efficient row-by-row parallelization of general sparse matrix-matrix multiplication (SpGEMM) operation of the form C=A,B on many-core architectures. Hypergraph and bipartite graph models are proposed for 1D rowwise partitioning of matrix A to evenly partition the work across threads with the objective of reducing the number of B-matrix words to be transferred from the memory and between different caches. A hypergraph model is proposed for B-matrix column reordering to exploit spatial locality in accessing entries of thread-private temporary arrays, which are used to accumulate results for C-matrix rows. A similarity graph model is proposed for B-matrix row reordering to increase temporal reuse of these accumulation array entries. The proposed models and methods are tested on a wide range of sparse matrices from real applications and the experiments were carried on a 60-core Intel Xeon Phi processor, as well as a two-socket Xeon processor. Results show the validity of the models and methods proposed for enhancing the locality in parallel SpGEMM operations. © 1990-2012 IEEE.
      Keywords
      Bipartite graph model
      Computational hypergraph model
      Intel Xeon Phi
      SpGEMM
      Computer architecture
      Graph theory
      Bipartite graphs
      Data locality
      Graph clustering
      Graph model
      Graph partitioning
      Hypergraph clustering
      Hypergraph model
      Hypergraph partitioning
      Many-core architecture
      Sparse matrices
      Sparse matrix-matrix multiplications
      Matrix algebra
      Permalink
      http://hdl.handle.net/11693/37098
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/TPDS.2017.2656893
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      • Department of Computer Engineering 1561
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