206 citations · 535 across the 22 of their papers we have counts for
22 papers
Randomized Numerical Linear Algebra : A Perspective on the Field With an Eye to Software
Riley Murray, James Demmel, Michael W. Mahoney +10
Randomized numerical linear algebra - RandNLA, for short - concerns the use of randomization as a resource to develop improved algorithms for large-scale linear algebra computation…
Proposed Consistent Exception Handling for the BLAS and LAPACK
James Demmel, Jack Dongarra, Mark Gates +7
Numerical exceptions, which may be caused by overflow, operations like division by 0 or sqrt(-1), or convergence failures, are unavoidable in many cases, in particular when softwar…
Reinventing High Performance Computing: Challenges and Opportunities
Daniel Reed, Dennis Gannon, Jack Dongarra
The world of computing is in rapid transition, now dominated by a world of smartphones and cloud services, with profound implications for the future of advanced scientific computin…
Efficient Exascale Discretizations: High-Order Finite Element Methods
Tzanio Kolev, Paul Fischer, Misun Min +27
Efficient exploitation of exascale architectures requires rethinking of the numerical algorithms used in many large-scale applications. These architectures favor algorithms that ex…
Integrating Deep Learning in Domain Sciences at Exascale
Rick Archibald, Edmond Chow, Eduardo D'Azevedo +8
This paper presents some of the current challenges in designing deep learning artificial intelligence (AI) and integrating it with traditional high-performance computing (HPC) simu…
Improving the Performance of the GMRES Method using Mixed-Precision Techniques
Neil Lindquist, Piotr Luszczek, Jack Dongarra
The GMRES method is used to solve sparse, non-symmetric systems of linear equations arising from many scientific applications. The solver performance within a single node is memory…