The LHCb experiment is one of the particle physics detector experiments located at the LHC at CERN. At the collision points at the LHC, millions of particle collisions happen every second. Due to limitations in computing power and storage capacity, so far not every one of these events could be recorded and processed. Rather, only a fraction of the events were picked out to be processed by so called triggers. From 2020, the LHCb experiment plans to proceed to a trigger-free readout, where all of the events can be processed, thereby increasing the amount of data available to physicists. This requires an update of the LHCb Data Acquisition (DAQ) systems, which are responsible for the recording and processing of the events. DAQPIPE (Data Acquisition Protocol Independent Performance Evaluator) is a tool to simulate and evaluate the performance of such a DAQ system.
The aim of this 10-week summer student project was to implement network monitoring for a more detailed performance evaluation of different transport protocols and to spot potential bottlenecks. First, several existing performance monitors were tested. To that end DAQPIPE was run together with Tau and the obtained performance data was plotted with ParaProf, JumpShot and Vampir. In the second stage of the project, a light-weight performance analysis tool was written from scratch in C++.
In 2020 the Data Acquisition (DAQ) of the LHCb experiment will be updated to feature a trigger-free readout. This requires an event builder network consisting of about 500 nodes with a total network capacity of 4 TBytes/s. DAQPIPE (Data Acquisition Protocol Independent Performance Evaluator) is a tool to simulate and evaluate the performance of such a DAQ system. The current implementation of DAQPIPE only gives rough feedback about the event building rate.
The aim of this 10-week summer student project was to implement network monitoring for a more detailed performance evaluation of different transport protocols and to spot potential bottlenecks. First, several existing performance monitors were tested. To that end DAQPIPE was run together with Tau and the obtained performance data was plotted with ParaProf, JumpShot and Vampir. In the second stage of the project, a light-weight performance analysis tool was written from scratch by wrapping around the C++ MPI communication library to collect data.
Monitoring the data sent by two readout units (RUs). RUs collect incoming data fragments from different subdetectors and send it to builder units (BUs), which process the information.