Ichitaro Yamazaki


Dense Linear Algebra
  1. I. Yamazaki, and S. Tomov, and J. Dongarra: Mixed-precision Cholesky QR factorization and its case studies on multicore CPU with multiple GPUs. SIAM J. Sci. Comput. 37(3): C307-C330 (2015).
    ▷ Initial performance studies: Mixed-precision orthogonalization scheme and adaptive step size for CA-GMRES on GPUs. VECPAR'14 (Best paper), LNCS 8969: 17-30 (2015): (link, preprint).
    ▷ Extension to orthogonalize a larger number of columns: Mixed-precision block Gram Schmidt orthogonalization. ScalA'15 (link).
  2. G. Ballard, D. Becker, J. Demmel, J. Dongarra, A. Druinsky, I. Peled, O. Schwartz, S. Toledo, and I. Yamazaki: Communication-avoiding symmetric-indefinite factorization. SIAM J. Matrix Anal. Appl. 35(4): 1364-1460 (2014). (link,preprint).
    ▷ Implementation and performance studies in: Implementing a blocked Aasen's algorithm with a dynamic scheduler on multicore architecture. IPDPS 2013 (Best paper): 895-907 (link)
  3. I. Yamazaki, T. Dong, R. Solca, S. Tomov, J. Dongarra, and T. Schulthess: Tridiagonalization of a dense symmetric matrix on multiple GPUs and its application to symmetric eigenvalue problems. Concurrency Computat.: Pract. Exper. 26(16): 2652-2666 (2014) (link, preprint).
  4. I. Yamazaki, S. Tomov, and J. Dongarra: One-sided dense matrix factorizations on a multicore with multiple GPU accelerators. ICCS 2012: 37-46 (link)
  5. Y. Nakatsukasa, K. Aishima, and I. Yamazaki: dqds with aggressive early deflation. SIAM J. Matrix Anal. Appl. 33(1): 22-51 (2012) (preprint, link).

Sparse Linear Algebra
  1. I. Yamazaki, S. Rajamanickam, E. Boman, M. Hoemmen, M. Heroux, and S. Tomov: Domain decomposition preconditioners for communication-avoiding Krylov methods on a hybrid CPU/GPU cluster. SC 2014: 933-944 (link).
  2. I. Yamazaki, S. Tomov, and J. Dongarra: Deflation strategies to improve the convergence of communication-avoiding GMRES. ScalA Workshop 2014: 39-46 (link).
  3. I. Yamazaki, H. Anzt, S. Tomov, M. Hoemmen, and J. Dongarra: Improving the performance of CA-GMRES on multicores with multiple GPUs. IPDPS 2014: 382-391 (link, preprint).
  4. I. Yamazaki and K. Wu: A communication-avoiding thick-restart Lanczos method on a distributed-memory system. HPSS worksop at EuroPar 2011: 345-354 (preprint, link).

  5. I. Yamazaki, X. Li, F.-H. Rouet, and B. Ucar: Partitioning, ordering, and load balancing in a hierchically parallel hybrid linear solver. PDSEC 2013: (preprint, link)
  6. X. Lacoste, P. Ramet, M. Faverge, I. Yamazaki, and J. Dongarra: Sparse direct solvers with accelerators over DAG runtimes. (preprint)
  7. I. Yamazaki and X. Li: New scheduling strategies and hybrid programming for a parallel right-looking sparse LU factorization algorithm on multicore cluster systems. IPDPS 2012: 619-630 (preprint, link)
  8. I. Yamazaki and X. Li: On techniques to improve robustness and scalability of a parallel hybrid linear solver. VECPAR 2010: 421-434 (preprint, link).
  9. I. Yamazaki, Z. Bai, H. Simon, L.-W. Wang, and K. Wu: Adaptive projection subspace dimension for the thick-restart Lanczos method. ACM Trans. Math. Soft. 37(3): (2010) (preprint, link).

Randomized Linear Algebra
  1. I. Yamazaki, J. Kurzak, P. Luszczek, and J. Dongarra: Randomized algorithms to update partial singular value decomposition on a hybrid CPU/GPU cluster. SC 2015: 59:1-59:12 (link).
  2. T. Mary, I. Yamazaki, J. Kurzak, P. Luszczek, S. Tomov, and J. Dongarra: Performance of random sampling for computing low-rank approximations of a dense matrix on GPUs. SC 2015: 60:1-60:11 (link).
  3. I. Yamazaki, T. Mary, J. Kurzak, S. Tomov, and J. Dongarra: Access-averse framework for computing low-rank matrix approximations. BigData Workshop 2014: 70-77 (link).

  1. X. Yuan, X. Li, I. Yamazaki, S. Jardin, A. Koniges, and D. Keyes: Application of PDSLin to the magnetic reconnection problem. ICNSP 2011 (link).
  2. I. Yamazaki, T. Ikegami, T. Sakurai, and H. Tadano: Performance comparison of parallel eigensolvers based on a contour integral method and a Lanczos method, PMAA 2010 (Parallel Computing 39: 280-290, 2013, link)
  3. Z. Bai, W. Chen, R. Scalettar, and I. Yamazaki: Numerical methods for quantum Monte Carlo simulations of the Hubbard model in multi-scale phenomena in complex fluids, Higher Education Press and World Scientific, 2009 (preprint).
  4. I. Yamazaki, Z. Bai, W. Chen, and R. Scalettar: A high-quality preconditioning technique for multi-length-scale symmetric positive definite linear systems. Numer. Math. Theor. Meth. Appl. 2(4) 2009 (preprint, link).
  5. S. Chatterji, I. Yamazaki, Z. Bai, and J. Eisen: CompostBin: A DNA composition-based algorithm for binning environmental shotgun reads. RECOMB 2008: 17-28 (preprint).
  6. I. Yamazaki, V. Natarajan, Z. Bai, and B. Hamann: Segmenting point-sampled surfaces. The Visual Computer 26(12): 1421-1433 (2010) (preprint, link).
    ▷ Initial results in: Segmenting point sets. SMI 2006: 6-15 (preprint, link).

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