2. Introduction. Offline algorithm timing/memory performance is linked directly to the efficiency of doing physics analysesThink of it as sort of
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1. 1 Algorithm Timing and Performance Issues (with emphasis on HLT algorithm online timing) Xin Wu (University of Geneva)
On behalf of TDAQ
TP Week, June 7, 2007
2. 2 Introduction Offline algorithm timing/memory performance is linked directly to the efficiency of doing physics analyses Think of it as sort of ‘luminosity’ Faster algorithms = earlier results or with larger data sample HLT algorithms timing/memory performance are even more critical Slow algorithms or crashed processes contribute to DAQ dead time DAQ dead time = loss of luminosity The issue is serious for offline Offline Performance Task Force is formed to tackle it globally The issue is serious for HLT High LVL1 rate and limited budget (and space!) for HLT farms Up to 100 kHz LVL1 rate, up to 3 kHz LVL2/EB rate HLT algorithm timing are being optimized individually offline Great progresses have been achieved in the past year Global optimization done online with actual TDAQ hardware and “realistic mixture” of input events in Technical Runs