Speaker
Dr
Stuart Paterson
(CERN)
Description
The LHCb DIRAC Workload and Data Management System employs advanced optimization
techniques in order to dynamically allocate resources. The paradigms realized by
DIRAC, such as late binding through the Pilot Agent approach, have proven to be
highly successful. For example, this has allowed the principles of workload
management to be applied not only at the time of user job submission to the Grid but
also to optimize the use of computing resources once jobs have been acquired. Along
with the central application of job priorities, DIRAC minimizes the system response
time for high priority tasks. This paper will describe the recent developments to
support Monte Carlo simulation, data processing and distributed user analysis in a
consistent way across disparate compute resources including individual PCs, local
batch systems, and the Worldwide LHC Computing Grid. The Grid environment is
inherently unpredictable and whilst short-term studies have proven to deliver high
job efficiencies, the system performance over an extended period of time will be
considered here in order to convey the experience gained so far.
Primary author
Dr
Stuart Paterson
(CERN)
