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.

7

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?