1. Online monitoring and filtering Graham July 2009 Graham July 2009

2. 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.

3. CODA v2 system

4. Simplified ET

5. ✦ 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.

6. ✦ 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. 7 Hall B ET1 ET2 ET3 EB ER ECAL TOF CerDTagger DC LA-CAL

8. Online farm ✦ Distributed ✦ Need processing cycles ✦ Need high bandwidth ✦ Must survive node problems ✦ Two modes: ✦ Filter ✦ Monitor

9. Reminder of EB architecture

10. Online farm proposal

11. 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.

12. 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.

13. 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?