当前位置: X-MOL 学术Int. J. Comput. Sci. Eng. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Search by triplet: An efficient local track reconstruction algorithm for parallel architectures
Journal of Computational Science ( IF 3.3 ) Pub Date : 2021-07-15 , DOI: 10.1016/j.jocs.2021.101422
Daniel Hugo Cámpora Pérez 1, 2 , Niko Neufeld 3 , Agustín Riscos Núñez 4, 5
Affiliation  

Millions of particles are collided every second at the LHCb detector placed inside the Large Hadron Collider at CERN. The particles produced as a result of these collisions pass through various detecting devices which will produce a combined raw data rate of up to 40 Tbps by 2021. These data will be fed through a data acquisition system which reconstructs individual particles and filters the collision events in real time. This process will occur in a heterogeneous farm employing exclusively off-the-shelf CPU and GPU hardware, in a two stage process known as High Level Trigger.

The reconstruction of charged particle trajectories in physics detectors, also referred to as track reconstruction or tracking, determines the position, charge and momentum of particles as they pass through detectors. The Vertex Locator subdetector (VELO) is the closest such detector to the beamline, placed outside of the region where the LHCb magnet produces a sizable magnetic field. It is used to reconstruct straight particle trajectories which serve as seeds for reconstruction of other subdetectors and to locate collision vertices. The VELO subdetector will detect up to 109 particles every second, which need to be reconstructed in real time in the High Level Trigger.

We present Search by triplet, an efficient track reconstruction algorithm. Our algorithm is designed to run efficiently across parallel architectures. We extend on previous work and explain the algorithm evolution since its inception. We show the scaling of our algorithm under various situations, and analyse its amortized time in terms of complexity for each of its constituent parts and profile its performance. Our algorithm is the current state-of-the-art in VELO track reconstruction on SIMT architectures, and we qualify its improvements over previous results.



中文翻译:

按三元组搜索:一种高效的并行架构局部轨迹重建算法

欧洲核子研究中心的大型强子对撞机内的 LHCb 探测器每秒钟都有数百万个粒子发生碰撞。这些碰撞产生的粒子通过各种检测设备,到 2021 年将产生高达 40 Tbps 的组合原始数据速率。 这些数据将通过数据采集系统馈送,该系统重建单个粒子并过滤碰撞事件即时的。此过程将发生在一个完全采用现成 CPU 和 GPU 硬件的异构农场中,采用称为高级触发的两阶段过程。

物理探测器中带电粒子轨迹的重建,也称为轨迹重建或跟踪,确定粒子通过探测器时的位置、电荷和动量。顶点定位子探测器 (VELO) 是距离光束线最近的探测器,位于 LHCb 磁铁产生相当大磁场的区域之外。它用于重建直线粒子轨迹,作为其他子探测器重建的种子并定位碰撞顶点。VELO 子检测器将检测到109 粒子每秒,需要在高级触发器中实时重建。

我们提出了三元组搜索,这是一种有效的轨迹重建算法。我们的算法旨在跨并行架构高效运行。我们扩展了以前的工作,并解释了算法自成立以来的演变。我们展示了我们算法在各种情况下的缩放比例,并根据其每个组成部分的复杂性分析其摊销时间并分析其性能。我们的算法是 SIMT 架构上 VELO 轨迹重建的当前最先进的算法,并且我们证明了其对先前结果的改进。

更新日期:2021-07-30
down
wechat
bug