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Monte Carlo MP2 on Many Graphical Processing Units.

Alexander E Doran1, So Hirata1

  • 1Department of Chemistry, University of Illinois at Urbana-Champaign , 600 South Mathews Avenue, Urbana, Illinois 61801, United States.

Journal of Chemical Theory and Computation
|September 8, 2016
PubMed
Summary
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The Monte Carlo MP2 (MC-MP2) method significantly accelerates quantum chemistry calculations by using graphics processing units (GPUs) and a redundant-walker algorithm. This approach achieves substantial speedups, enabling the study of larger chemical systems.

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Area of Science:

  • Computational Chemistry
  • Quantum Mechanics
  • High-Performance Computing

Background:

  • Traditional MP2 energy calculations involve complex matrix expressions with poor scalability.
  • Efficient computation of electron correlation is crucial for accurate molecular modeling.

Purpose of the Study:

  • To develop and assess a scalable Monte Carlo second-order many-body perturbation (MC-MP2) method.
  • To leverage graphical processing units (GPUs) and parallel algorithms for computational acceleration.

Main Methods:

  • Recasting the MP2 energy expression into a high-dimensional integral evaluated via Monte Carlo integration.
  • Employing the redundant-walker algorithm to enhance sampling efficiency and reuse electron pairs.
  • Utilizing multi-GPU architectures for fine-grain data-parallelism and coarse-grain instruction-parallelism.

Main Results:

  • MC-MP2 demonstrates significantly improved scalability on GPUs compared to central processing units (CPUs).
  • A benzene dimer calculation showed a 2700x speedup on 256 GPUs versus two CPUs.
  • The computational cost scales as O(n^3) or better with system size n, outperforming deterministic MP2's O(n^5) scaling.

Conclusions:

  • The MC-MP2 method, accelerated by GPUs and the redundant-walker algorithm, offers a highly scalable approach for quantum chemistry.
  • This method enables efficient calculations for larger chemical systems, advancing computational chemistry capabilities.