DocumentCode
2310398
Title
Controlling a large CPU farm using industrial tools
Author
Sambade, Alba ; Frank, Markus ; Galli, Domenico ; Gaspar, Clara ; Jost, Beat ; Neufeld, Niko ; van Herwijnen, E.
Author_Institution
CERN (Eur. Organ. for Nucl. Res.), Geneva, Switzerland
fYear
2009
fDate
10-15 May 2009
Firstpage
220
Lastpage
223
Abstract
The LHCb experiment at CERN will have an event filter farm (EFF) composed of 2000 CPUs. These machines will form a pool of 50 sub-farms with 30 to 40 nodes each, running a large amount of high level trigger (HLT) tasks in parallel. Although these tasks are identical algorithms, they can run at the same time being configured with different parameters, such as run type (physics, cosmics, test, etc) or with different subdetectors (partitions). The HLT is the second of the two trigger levels in LHCb. Its selection algorithms reduce the incoming data rate of 1 MHz to an output rate of 2 kHz. Selected events are sent for mass storage and subsequent offline reconstruction and analysis. These trigger processes running online are based on the same software framework as the algorithms for offline analysis (Gaudi). The control of the trigger farm was developed with an industrial SCADA system (PVSS) which is used throughout the experiment control system (ECS). The HLT algorithms are handled by the ECS like hardware devices, for instance, high voltage channels. The integration of the HLT controls in the overall ECS, which is modeled as finite state machines, will be presented.
Keywords
SCADA systems; finite state machines; high energy physics instrumentation computing; CERN; CPU farm; LHCb experiment; event filter farm; finite state machine; frequency 1 MHz; frequency 2 kHz; high level trigger; industrial SCADA system; industrial tool; mass storage; Algorithm design and analysis; Control systems; Electrical equipment industry; Filters; Industrial control; Partitioning algorithms; Physics; SCADA systems; Software algorithms; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Real Time Conference, 2009. RT '09. 16th IEEE-NPSS
Conference_Location
Beijing
Print_ISBN
978-1-4244-4454-0
Type
conf
DOI
10.1109/RTC.2009.5321887
Filename
5321887
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