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This study details a parallel implementation of multireference coupled-cluster (MRCCSD(T)) calculations optimized for Intel Xeon Phi coprocessors. Enhanced performance was achieved through task reordering for improved load balancing in complex quantum chemistry computations.

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Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • High-Performance Computing

Background:

  • Multireference coupled-cluster (MRCCSD(T)) methods are crucial for accurate electronic structure calculations.
  • Existing implementations face computational bottlenecks, limiting their application to larger systems.
  • Leveraging specialized hardware like coprocessors is essential for advancing computational chemistry.

Purpose of the Study:

  • To implement and optimize the multireference coupled-cluster formalism with singles, doubles, and noniterative triples (MRCCSD(T)) on Intel Xeon Phi coprocessors.
  • To enhance the parallel performance and efficiency of MRCCSD(T) calculations.
  • To explore strategies for efficient optimization and vectorization for high-performance computing.

Main Methods:

  • Integration of two levels of parallelism within the MRCCSD(T) implementation.
  • Offloading computationally intensive kernels to Intel Xeon Phi coprocessors.
  • Task reordering for improved load balancing in noniterative calculations.

Main Results:

  • Successful implementation of MRCCSD(T) leveraging Intel Xeon Phi coprocessor capabilities.
  • Significant enhancement of parallel performance through optimized task reordering and load balancing.
  • Demonstrated efficient optimization and vectorization strategies for computational kernels.

Conclusions:

  • The implemented MRCCSD(T) formalism effectively utilizes Intel Xeon Phi coprocessors for advanced quantum chemistry.
  • Task reordering is a key strategy for improving parallel performance in MRCCSD(T) calculations.
  • The study provides a framework for accelerating complex electronic structure calculations on modern hardware architectures.