论文标题
LHCB的前进跟踪算法，用于运行3个基于CPU的在线跟踪重建序列
LHCb's Forward Tracking algorithm for the Run 3 CPU-based online track-reconstruction sequence
论文作者
论文摘要
在LHC的运行3中，LHCB实验面临的数据速率很高，其中包含美丽和魅力强子衰变。因此，触发器的任务不是选择任何美容和魅力事件，而是为LHCB物理程序选择包含腐烂的腐烂。因此，LHCB实施了实时数据处理策略，以直接触发重建事件。纯粹基于软件的触发器的第一阶段是在执行部分事件重建的GPU上实现的。在软件触发器的第二阶段中，在CPU上进行了完整的离线质量事件重建，其中关键部分是跟踪重建，平衡轨道查找效率，假轨道速率和事件吞吐量。提出了LHCB的基于CPU的基于CPU的轨道重建序列，并强调了“正向跟踪”，该算法是重建横穿LHCB所有跟踪检测器的带电粒子的轨迹的算法。为了满足事件吞吐量要求，“前向跟踪”使用算法的多个核心部分中的SIMD指令，例如Hough Transform和cluster搜索。这些变化导致该算法的事件吞吐量提高了60％。
In Run 3 of the LHC the LHCb experiment faces very high data rates containing beauty and charm hadron decays. Thus the task of the trigger is not to select any beauty and charm events, but to select those containing decays interesting for the LHCb physics programme. LHCb has therefore implemented a real-time data processing strategy to trigger directly on reconstructed events. The first stage of the purely software-based trigger is implemented on GPUs performing a partial event reconstruction. In the second stage of the software trigger, the full, offline-quality event reconstruction is performed on CPUs, with a crucial part being track reconstruction, balancing track finding efficiency, fake track rate and event throughput. LHCb's CPU-based track reconstruction sequence for Run 3 is presented, highlighting the "Forward Tracking", which is the algorithm that reconstructs trajectories of charged particles traversing all of LHCb's tracking detectors. To meet event throughput requirements, the "Forward Tracking" uses SIMD instructions in several core parts of the algorithm, such as the Hough transform and the cluster search. These changes led to an improvement of the algorithm's event throughput by 60%.
