• Publications
  • Influence
Applied Numerical Linear Algebra
  • J. Demmel
  • Mathematics, Computer Science
  • 1 September 1997
The symmetric Eigenproblem and singular value decomposition and the Iterative methods for linear systems Bibliography Index. Expand
LAPACK Users' Guide, 3rd ed.
Templates for the Solution of Algebraic Eigenvalue Problems
This book discusses iterative projection methods for solving Eigenproblems, and some of the techniques used to solve these problems came from the literature on Hermitian Eigenvalue. Expand
An updated set of basic linear algebra subprograms (BLAS)
L. SUSAN BLACKFORD Myricom, Inc. JAMES DEMMEL University of California, Berkeley JACK DONGARRA The University of Tennessee IAIN DUFF Rutherford Appleton Laboratory and CERFACS SVEN HAMMARLINGExpand
A Supernodal Approach to Sparse Partial Pivoting
A sparse LU code is developed that is significantly faster than earlier partial pivoting codes and compared with UMFPACK, which uses a multifrontal approach; the code is very competitive in time and storage requirements, especially for large problems. Expand
Benchmarking GPUs to tune dense linear algebra
It is argued that modern GPUs should be viewed as multithreaded multicore vector units and exploit blocking similarly to vector computers and heterogeneity of the system by computing both on GPU and CPU. Expand
SuperLU_DIST: A scalable distributed-memory sparse direct solver for unsymmetric linear systems
The main algorithmic features in the software package SuperLU_DIST, a distributed-memory sparse direct solver for large sets of linear equations, are presented, with an innovative static pivoting strategy proposed earlier by the authors. Expand
LAPACK Users' Guide, Third Edition
Large Batch Optimization for Deep Learning: Training BERT in 76 minutes
The empirical results demonstrate the superior performance of LAMB across various tasks such as BERT and ResNet-50 training with very little hyperparameter tuning, and the optimizer enables use of very large batch sizes of 32868 without any degradation of performance. Expand