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  • 1Computer Network Information Center, Chinese Academy of Sciences, Beijing, China.

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|September 28, 2020
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Summary

We developed an efficient method for constructing configuration-interaction (CI) expansions from matrix product states (MPS) using Charm++ for improved computational efficiency. This approach enhances productivity and enables large-scale quantum chemistry calculations.

Keywords:
Charm++ frameworkconfiguration interactiondensity-matrix renormalization groupfirefly dioxetonane anionparallel computing

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Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • High-Performance Computing

Background:

  • Constructing configuration-interaction (CI) expansions from matrix product states (MPS) is computationally intensive.
  • Efficiently sampling configurations in large Hilbert spaces is crucial for accurate quantum chemical calculations.

Purpose of the Study:

  • To present an efficient procedure for constructing CI expansions from MPS.
  • To leverage parallel computing frameworks for enhanced performance in quantum chemistry simulations.

Main Methods:

  • Utilized the parallel object-oriented Charm++ programming framework for automatic load balancing and object migration.
  • Implemented the procedure in existing computational chemistry utilities like MPS-to-CI, SR-CAS, and EDGA.
  • Developed population-expansion versions of algorithms, such as PE-EDGA.

Main Results:

  • Demonstrated persistent improvement in parallel efficiencies by increasing asynchronous execution proportions.
  • Successfully constructed a sampled CAS-type CI wave function for a complex bi-radical-state molecule (FDO-) within hours using thousands of cores.
  • Showcased the scalability and efficiency of the Charm++ based approach for large active space calculations.

Conclusions:

  • The Charm++ framework provides an efficient and scalable platform for constructing CI expansions from MPS.
  • The developed procedure significantly enhances productivity and enables the study of complex molecular systems.
  • This work paves the way for more accurate and efficient quantum chemical calculations on large systems.