2011/08/23 by Eiji Tsuchida, Tsuchida, Eiji, Yoong‐Kee Choe +2
Computer Science · Engineering · Mathematics · Physics and Astronomy · #Advanced Measurement and Metrology Techniques #Advanced Optimization Algorithms Research #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Matrix Theory and Algorithms #physics.comp-ph
paper · pdf · doi:10.48550/arxiv.1108.4509
10 pages, 7 figures
arxiv created 2011/08/23 · openalex publication_date 2011/08/23 · arxiv updated 2011/08/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Diagonalization of a large matrix is the computational bottleneck in many applications such as electronic structure calculations. We show that a speedup of over 30% can be achieved by exploiting 32-bit floating point operations, while keeping 64-bit accuracy. Moreover, most of the computationally expensive operations are performed by level-3 BLAS/LAPACK routines in our implementation, thus leading to optimal performance on most platforms. Further improvement can be made by using problem-specific preconditioners which take into account nondiagonal elements.