Measuring Intrinsic Value - Hasan Bakhshi, Alan Freeman + Graham Hitchen (2009)
Online monitoring and filtering Graham July 2009 Graham July 2009.
Transcript of Online monitoring and filtering Graham July 2009 Graham July 2009.
Online monitoringand filtering
Online monitoringand filtering
GrahamJuly 2009Graham
July 2009
Monitoring and filtering in CODA v2✦ Up to 32 ROCs.✦ A single event builder (EB)✦ EB output is a stream of single events.✦ EB is connected to Event Transport (ET)
system.✦ ET has one or more online analysis, filter and
monitor programs attached. ✦ Event recorder attaches to ET and takes all
events that survive filtering.
CODA v2 systemCODA v2 system
Simplified ETSimplified ET
✦ ET has following features:✦ Can be more than one data producer per
ET.✦ Each station can have a user provided
filter algorithm that looks at the data tags.✦ Can be more than one data consumer per
station but algorithm is shared.✦ System has “fair play” algorithms.
✦ round robin vs first free etc.✦ Stations can be configured to accept all
events, a sample of events or be skipped when their fifo is full.
✦ Since data moves “on a track” programs attached to stations after the producers but before data recorder can modify or filter data.
✦ Similarly programs attached to stations after the data recorder can monitor the data and if configured to skip events when their input is full do not introduce dead time.
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Hall B
ET1
ET2 ET3
EB
ER
ECAL TOF CerD Tagger DC
LA-CAL
Online farm✦ Distributed
✦ Need processing cycles✦ Need high bandwidth
✦ Must survive node problems✦ Two modes:
✦ Filter✦ Monitor
Reminder of EB architectureReminder of EB architecture
Online farm proposalOnline farm proposal
Proposal✦ Each EMU in the final stage of the EB writes to an
ET.✦ provides one station per farm node.✦ configured to load balance between nodes.✦ EMU has one or more backup ETs if preferred
full.✦ Each node has a local ET and several jobs.
✦ Local ET gets data from the remote ET.✦ Each job gets data from and puts to local ET.
✦ After filter/monitor local ET puts to a remote ET.✦ One or more event recorders pull data from this
ET.
How it works✦ First ET is a source of data for one or more nodes.
✦ Load balance and fault tolerance between nodes.
✦ Second ET, local to node is source for several jobs.✦ Load balance and fault tolerance between jobs.
✦ Last ET has data sources from one or more nodes.✦ Control nodes and jobs using AFECS.✦ Why it works
✦ Distributed and parallel✦ Only requires configuration of ET systems
✦ can tune parameters to alter behavior.
Issues✦ What does the data look like at this stage?
✦ Events?✦ Blocks of events?✦ Does it matter?
✦ What do we do with “non-physics” events?✦ Does it matter if event N appears before or
after event N+1?