4.7 Article

Mixed-Precision Implementation of the Density Matrix Renormalization Group

Journal

JOURNAL OF CHEMICAL THEORY AND COMPUTATION
Volume 18, Issue 12, Pages 7260-7271

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.jctc.2c00632

Keywords

-

Funding

  1. GHfund A [20220201, ghfund202202015504]
  2. National Natural Science Foundation of China [22073045]
  3. Fundamental Research Funds for the Central Universities

Ask authors/readers for more resources

Mixed-precision optimization is an effective technique for improving computational performance while maintaining accuracy in quantum chemistry methods. In this study, a two-level mixed-precision implementation for the density matrix renormalization group (DMRG) method is developed. Benchmark results show that the proposed implementation achieves both improved performance and preserved accuracy.
The mixed-precision optimization is an effective emerging technique for quantum chemistry methods to obtain better computational performance and maintain the chemical accuracy. Here, we developed a two-level mixed-precision implementation for the density matrix renormalization group (DMRG) method. This implementation is based on the idea that the DMRG process is an iterative process. Therefore, the first several iteration steps can be executed in single precision. A feasible single-precision DMRG may generate moderate accuracy, and when a few double-precision cleanup sweeps are added, the double-precision accuracy will be recovered. In the double precision sweeps, we developed a mixed-precision diagonalization method that can run the most time-consuming step in single precision and maintain the double-precision accuracy. By combining these two mixed-precision schemes, we implemented our mixed-precision DMRG method. The benchmark result shows that our mixed-precision implementation achieved a good performance. A speed-up of up to 2.31 is achieved, and the accuracy is preserved within 0.01 kcal/mol.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available