GPU acceleration and performance of the particle-beam-dynamics code Elegant

TL;DR

This paper presents a GPU-accelerated version of the Elegant particle-beam dynamics code, achieving 6-10x performance improvements on supercomputers while maintaining accuracy and ease of maintenance.

Contribution

The paper introduces a GPU framework for Elegant that significantly enhances simulation performance and ensures accuracy, simplifying implementation of core kernel types.

Findings

GPU version achieves 6-10x speedup on Titan supercomputer.

Framework simplifies implementation of core kernels.

Accuracy matches CPU-based results across multiple methods.

Abstract

Elegant is an accelerator physics and particle-beam dynamics code widely used for modeling and design of a variety of high-energy particle accelerators and accelerator-based systems. In this paper we discuss a recently developed version of the code that can take advantage of CUDA-enabled graphics processing units (GPUs) to achieve significantly improved performance for a large class of simulations that are important in practice. The GPU version is largely defined by a framework that simplifies implementations of the fundamental kernel types that are used by Elegant: particle operations, reductions, particle loss, histograms, array convolutions and random number generation. Accelerated performance on the Titan Cray XK-7 supercomputer is approximately 6-10 times better with the GPU than all the CPU cores associated with the same node count. In addition to performance, the maintainability of the GPU-accelerated version of the code was considered a key design objective. Accuracy with respect to the CPU implementation is also a core consideration. Four different methods are used to ensure that the accelerated code faithfully reproduces the CPU results.