Data processing and online reconstruction

In the upcoming upgrades for Run 3 and 4, the LHC will significantly increase Pb--Pb and pp interaction rates. This goes along with upgrades of all experiments, ALICE, ATLAS, CMS, and LHCb, related to both the detectors and the computing. The online processing farms must employ faster, more efficient reconstruction algorithms to cope with the increased data rates, and data compression factors must increase to fit the data in the affordable capacity for permanent storage. Due to different operating conditions and aims, the experiments follow different approaches, but there are several common trends like more extensive online computing and the adoption of hardware accelerators. This paper gives an overview and compares the data processing approaches and the online computing farms of the LHC experiments today in Run 2 and for the upcoming LHC Run 3 and 4.Comment: 6 pages, 0 figures, contribution to LHCP2018 conferenc

Online Personal Data Processing and EU Data Protection Reform. CEPS Task Force Report, April 2013

This report sheds light on the fundamental questions and underlying tensions between current policy objectives, compliance strategies and global trends in online personal data processing, assessing the existing and future framework in terms of effective regulation and public policy. Based on the discussions among the members of the CEPS Digital Forum and independent research carried out by the rapporteurs, policy conclusions are derived with the aim of making EU data protection policy more fit for purpose in today’s online technological context. This report constructively engages with the EU data protection framework, but does not provide a textual analysis of the EU data protection reform proposal as such

Data Workflow - A Workflow Model for Continuous Data Processing

Online data or streaming data are getting more and more important for enterprise information systems, e.g. by integrating sensor data and workflows. The continuous flow of data provided e.g. by sensors requires new workflow models addressing the data perspective of these applications, since continuous data is potentially infinite while business process instances are always finite.\ud In this paper a formal workflow model is proposed with data driven coordination and explicating properties of the continuous data processing. These properties can be used to optimize data workflows, i.e., reducing the computational power for processing the workflows in an engine by reusing intermediate processing results in several workflows

Fast TPC Online Tracking on GPUs and Asynchronous Data Processing in the ALICE HLT to facilitate Online Calibration

ALICE (A Large Heavy Ion Experiment) is one of the four major experiments at the Large Hadron Collider (LHC) at CERN, which is today the most powerful particle accelerator worldwide. The High Level Trigger (HLT) is an online compute farm of about 200 nodes, which reconstructs events measured by the ALICE detector in real-time. The HLT uses a custom online data-transport framework to distribute data and workload among the compute nodes. ALICE employs several calibration-sensitive subdetectors, e.g. the TPC (Time Projection Chamber). For a precise reconstruction, the HLT has to perform the calibration online. Online-calibration can make certain Offline calibration steps obsolete and can thus speed up Offline analysis. Looking forward to ALICE Run III starting in 2020, online calibration becomes a necessity. The main detector used for track reconstruction is the TPC. Reconstructing the trajectories in the TPC is the most compute-intense step during event reconstruction. Therefore, a fast tracking implementation is of great importance. Reconstructed TPC tracks build the basis for the calibration making a fast online-tracking mandatory. We present several components developed for the ALICE High Level Trigger to perform fast event reconstruction and to provide features required for online calibration. As first topic, we present our TPC tracker, which employs GPUs to speed up the processing, and which bases on a Cellular Automaton and on the Kalman filter. Our TPC tracking algorithm has been successfully used in 2011 and 2012 in the lead-lead and the proton-lead runs. We have improved it to leverage features of newer GPUs and we have ported it to support OpenCL, CUDA, and CPUs with a single common source code. This makes us vendor independent. As second topic, we present framework extensions required for online calibration. ...Comment: 8 pages, 6 figures, contribution to CHEP 2015 conferenc

Remote controlled partial discharge acquisition unit

Online partial discharge (PD) analysis for underground high voltage cables has major advantages over the offline techniques. Online techniques usually involve PD data acquisition, storage and post-processing of the data. However, the data acquisition process can be time consuming and troublesome because of design procedures and protocols required before commencement of data acquisition. This paper presents a robust remote controlled partial discharge acquisition unit for underground high voltage cable networks. This system is uniquely designed to incorporate the difficulties of accessibility, especially for remotely located substations. Real field data from a 33kV network is included in the paper