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High-Performance Implementation of the Optimized Event Generator for Strong-Field QED Plasma Simulations

Elena Panova, Valentin Volokitin, Aleksei Bashinov, Alexander Muraviev, Evgeny Efimenko, Iosif Meyerov

TL;DR

SFQED simulations are computationally intensive due to stochastic rates and potential cascades. The authors implement a high‑performance version of the QED module using inverse sampling with minimal rate evaluations, augmented with vectorization and multi‑threading. They demonstrate 2.4x speedups on hi-$\chi$ and 30% improvements on PICADOR, with overall runtime reductions, validating portability and practical impact. The work provides portable techniques and open‑source code to enable scalable SFQED‑PIC simulations on modern HPC systems.

Abstract

Numerical simulation of strong-field quantum electrodynamics (SFQED) processes is an essential step towards current and future high-intensity laser experiments. The complexity of SFQED phenomena and their stochastic nature make them extremely computationally challenging, requiring the use of supercomputers for realistic simulations. Recently, we have presented a novel approach to numerical simulation of SFQED processes based on an accurate approximation of precomputed rates, which minimizes the number of rate calculations per QED event. The current paper is focused on the high-performance implementation of this method, including vectorization of resource-intensive kernels and improvement of parallel computing efficiency. Using two codes, PICADOR and hi-$χ$ (the latter being free and publicly available), we demonstrate significant reduction in computation time due to these improvements. We hope that the proposed approach can be applied in other codes for the numerical simulation of SFQED processes.

High-Performance Implementation of the Optimized Event Generator for Strong-Field QED Plasma Simulations

TL;DR

SFQED simulations are computationally intensive due to stochastic rates and potential cascades. The authors implement a high‑performance version of the QED module using inverse sampling with minimal rate evaluations, augmented with vectorization and multi‑threading. They demonstrate 2.4x speedups on hi- and 30% improvements on PICADOR, with overall runtime reductions, validating portability and practical impact. The work provides portable techniques and open‑source code to enable scalable SFQED‑PIC simulations on modern HPC systems.

Abstract

Numerical simulation of strong-field quantum electrodynamics (SFQED) processes is an essential step towards current and future high-intensity laser experiments. The complexity of SFQED phenomena and their stochastic nature make them extremely computationally challenging, requiring the use of supercomputers for realistic simulations. Recently, we have presented a novel approach to numerical simulation of SFQED processes based on an accurate approximation of precomputed rates, which minimizes the number of rate calculations per QED event. The current paper is focused on the high-performance implementation of this method, including vectorization of resource-intensive kernels and improvement of parallel computing efficiency. Using two codes, PICADOR and hi- (the latter being free and publicly available), we demonstrate significant reduction in computation time due to these improvements. We hope that the proposed approach can be applied in other codes for the numerical simulation of SFQED processes.
Paper Structure (12 sections, 1 figure, 1 table, 3 algorithms)

This paper contains 12 sections, 1 figure, 1 table, 3 algorithms.

Table of Contents

  1. Introduction
  2. Related Works
  3. Models and Algorithms
  4. Optimization
  5. Data structures
  6. Multi-threading
  7. Vectorization
  8. Experiments
  9. Test Problem
  10. Validation
  11. Performance
  12. Conclusion

Figures (1)

  • Figure 1: (a) Cascade growth for the test problem of cascade development. Results are shown for two QED implementations: baseline and optimized. (b,c) Particle density is given at $t=5T$. We only demonstrate a quarter wavelength along the $x$-axis due to the symmetry of the distribution. Colored solid lines show electron and photon densities for a series of 100 simulations. Positron density is similar to electron density, so it is not displayed here. Dashed lines show the mean density $\mu(x)$ and the maximal deviation according to the empirical rule $3\sigma$.