GPU-based reconstruction and data compression at ALICE during LHC Run 3
GPU-based reconstruction and data compression at ALICE during LHC Run 3
复制标题
LHC Run 3 期间 ALICE 基于 GPU 的重建和数据压缩
作者：
D. Rohr
在LHC Run 3中，ALICE将在最小偏置Pb-Pb碰撞下显著提高数据采集速率至50 kHz连续读取。在线离线计算升级的重建策略预测了在数据获取过程中允许检测器校准的第一个同步在线重建阶段，以及后验校准的异步重建阶段。数据速率的显著提高对在线和离线重建以及数据压缩提出了挑战。与Run 2相比，在线农场每秒必须处理50倍以上的事件，并实现更高的数据压缩系数。ALICE将依靠gpu实时执行对数据速率贡献最大的时间投影室（TPC）探测器的实时处理和数据压缩。随着在线农场中可用的gpu，我们正在评估它们在硅内部跟踪系统（ITS）和过渡辐射探测器（TRD）的异步重建期间对整个跟踪链的使用情况。该软件以通用方式编写，因此它也可以在WLCG上的处理器上运行，具有相同的重建输出。我们概述了重建的现状和当前性能，以及GPU上用于TPC和全局重建的数据压缩实现。
In LHC Run 3, ALICE will increase the data taking rate significantly to 50 kHz continuous read out of minimum bias Pb-Pb collisions. The reconstruction strategy of the online offline computing upgrade foresees a first synchronous online reconstruction stage during data taking enabling detector calibration, and a posterior calibrated asynchronous reconstruction stage. The significant increase in the data rate poses challenges for online and offline reconstruction as well as for data compression. Compared to Run 2, the online farm must process 50 times more events per second and achieve a higher data compression factor. ALICE will rely on GPUs to perform real time processing and data compression of the Time Projection Chamber (TPC) detector in real time, the biggest contributor to the data rate. With GPUs available in the online farm, we are evaluating their usage also for the full tracking chain during the asynchronous reconstruction for the silicon Inner Tracking System (ITS) and Transition Radiation Detector (TRD). The software is written in a generic way, such that it can also run on processors on the WLCG with the same reconstruction output. We give an overview of the status and the current performance of the reconstruction and the data compression implementations on the GPU for the TPC and for the global reconstruction.