标题： 大型强子对撞机的计算未来 显示英文标题

标题： Future of computing at the Large Hadron Collider

摘要： 高能物理（HEP）实验在大型强子对撞机（LHC）上以每秒$\mathcal{O}(10)$太比特的数据速率生成数据。 预计随着未来实验升级以实现更高的碰撞能量，这一数据速率将呈指数增长。 粒子物理数据集的增大以及单核CPU性能的停滞，预计到2030年将导致计算能力出现四倍的短缺。 这使得有必要研究替代的计算架构以应对下一代HEP实验。 本研究概述了LHCb实验中使用的不同计算技术（触发、轨迹重建、顶点重建、粒子识别）。 此外，这项研究促成了为LHCb实验创建的三种事件重建算法。 这些算法在各种计算架构上进行了基准测试，如CPU、GPU和一种新型处理器称为IPU，分别大致包含$\mathcal{O}(10)$、$\mathcal{O}(1000)$和$\mathcal{O}(1000)$个核心。 这项研究表明，多核架构如GPU和IPU更适合HEP实验中的计算密集型任务。 显示英文摘要

摘要： High energy physics (HEP) experiments at the LHC generate data at a rate of $\mathcal{O}(10)$ Terabits per second. This data rate is expected to exponentially increase as experiments will be upgraded in the future to achieve higher collision energies. The increasing size of particle physics datasets combined with the plateauing single-core CPU performance is expected to create a four-fold shortage in computing power by 2030. This makes it necessary to investigate alternate computing architectures to cope with the next generation of HEP experiments. This study provides an overview of different computing techniques used in the LHCb experiment (trigger, track reconstruction, vertex reconstruction, particle identification). Furthermore, this research led to the creation of three event reconstruction algorithms for the LHCb experiment. These algorithms are benchmarked on various computing architectures such as the CPU, GPU, and a new type of processor called the IPU, each roughly containing $\mathcal{O}(10)$, $\mathcal{O}(1000)$, and $\mathcal{O}(1000)$ cores respectively. This research indicates that multi-core architectures such as GPUs and IPUs are better suited for computationally intensive tasks within HEP experiments.