Optimizing HiRep lattice simulations on CPU-based computer clusters

Abstract

In the scientific exploration of Quantum Chromodynamics (QCD) —the theory governing the strong interaction among quarks and gluons— large-scale numerical simulations are performed using the framework of lattice gauge theories. Lattice Gauge Theory (LGT) simulations involve the formulation of gauge field theories on a finite space-time lattice. HiRep is a simulation suite designed for running lattice simulations, leveraging high-performance computing platforms. The implementation of the Dirac operator application in HiRep is identified as one of the most computationally intensive routines. As such, we optimize the runtime performance bottleneck of this routine in HiRep software application for CPU-based distributed-memory hardware platforms. To this end, both algorithmic and hardware-dependent optimization strategies are employed. These strategies include efficient hybrid parallelization (using both MPI and Open MP parallel programming frameworks), optimizing OpenMP parallelism through loop collapsing, memory access patterns optimization, and vectorization (using both AVX2 and Clang compiler’s vector intrinsics). Based on experimental results obtained from two distinct High-Performance Computing (HPC) platforms, the proposed optimizations boost the performance of HiRep, achieving an overall speedup of up to ×1.80 compared to the baseline MPI version.

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