Efficient Time Frame Building for Online Data Reconstruction in ALICE Experiment

21st International Conference on Computing in High Energy and Nuclear Physics

物理学;计算机科学

Rybalchenko, A.^1 ; Al-Turany, M.^1,2 ; Kouzinopoulos, C.^2 ; Winckler, N.^1

GSI Helmholtzzentrum Fr Schwerionenforschung GmbH, Planckstrae 1, Darmstadt

64291, Germany^1

CERN, European Laboratory for Particle Physics, Geneve

1211-23, Switzerland^2

关键词: Computing clusters;    Efficient time;    Event Processing;    Online data;    Performance measurements;    Processor nodes;    Time information;    Traffic-shaping;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/664/8/082048/pdf
DOI  :  10.1088/1742-6596/664/8/082048

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

After the Long Shutdown 2 period, the upgraded ALICE detector at the LHC will produce more than a terabyte of data per second. The data, constituted from a continuous un-triggered stream data, have to be distributed from about 250 First Level Processor nodes (FLPs) to about 1500 Event Processing Nodes (EPNs). Each FLP receives a small subset of the detector data that is chopped in sub-time frames. One EPN needs all the fragments from the 250 FLPs to build a full time frame. An algorithm has been implemented on the FLPs with the aim of optimizing the usage of the network connecting the FLPs and EPNs. The algorithm minimizes contention when several FLPs are sending to the same EPN. An adequate traffic shaping is implemented by delaying the sending time of each FLP by a unique offset. The payloads are stored in a buffer large enough to accommodate the delay provoked by the maximum number of FLPs. As the buffers are queued for sending, the FLPs can operate with the highest efficiency. Using the time information embedded in the data any further FLP synchronization can be avoided. Moreover, zero-copy and multipart messages of ZeroMQ are used to create full time frames on the EPNs without the overhead of copying the payloads. The concept and the performance measurement of the implementation on a reference computing cluster are presented.