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May 18, 2026Lobachevskii Journal of Mathematics0 citations

Optimization of a 3D Plasma Physics Code for the Numerical Simulation of a Diamagnetic ‘‘Bubble’’ in Linear Traps

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ICI. G. ChernykhВВВ.А. ВшивковICI. S. Chernoshtanov

Key Points

  • The aim is to explore how SIMD optimization can enhance the performance of plasma physics simulations.
  • Utilized SIMD instructions for parallel processing of data elements in plasma physics code.
  • Focused on data alignment and memory layout to achieve optimal performance.
  • Evaluated the performance improvements and energy savings from vectorization.
  • Achieved significant reductions in runtime for plasma simulations compared to scalar implementations (exact figures not provided).
  • Demonstrated near-GPU-level performance for certain workloads with effective SIMD usage.
  • Reduced energy consumption per calculation due to improved efficiency in vectorized code.

Abstract

SIMD optimization plays a crucial role in the acceleration of scientific plasma physics codes, where large arrays and repetitive numerical operations dominate computation. Using SIMD instructions, multiple data elements can be processed simultaneously within a single CPU cycle, greatly reducing runtime compared to scalar implementations. This efficiency enables researchers to perform higher-resolution plasma simulations within practical time limits. Modern CPUs offer wide SIMD registers, allowing near-GPU-level performance for certain workloads when used effectively. Without SIMD optimization, a significant portion of processor computational power remains untapped. To fully benefit from these capabilities, careful attention must be paid to data alignment and memory layout. In addition to improving performance, the well-vectorized code also decreases energy consumption per calculation. Consequently, mastering SIMD optimization has become an essential skill for developing efficient, high-performance software in computational plasma physics. In this paper, we will show how vectorization affects plasma physics code performance.

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Cite This Study

Chernykh et al. (2026) studied this question.

synapsesocial.com/papers/6a0aac6d5ba8ef6d83b6fdf7https://doi.org/10.1134/s1995080225614584
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