Difference between revisions of "35t Test"

From DUNE
Jump to navigation Jump to search
Line 22: Line 22:
 
|5||Wide-window burst mode||TPC in burst mode with the longest window possible (512MB buffer = 0.5s).||Special run mode for offline ZS studies
 
|5||Wide-window burst mode||TPC in burst mode with the longest window possible (512MB buffer = 0.5s).||Special run mode for offline ZS studies
 
|-
 
|-
|6||Burst mode||Collect data in certain time window|| foo
+
|6||Burst mode||Collect data in certain time window (could either determine this from a Nova time hash function, or using Penn board trigger input||Fallback before ZS works in RCE, this is also the mode for measuring noise, i.e. this is  the  mode for November vertical slice test
 
|}
 
|}
 
  
 
= Issues that need to be clarified =
 
= Issues that need to be clarified =

Revision as of 20:23, 9 October 2014

Recent documents

Run Modes (per DocDB 9677)

No. Mode Description Comment
1 Continuous main DAQ mode Similar to final 'triggerless' far detector running mode, i.e. parallel trigger farm looks for nice muons in real time. Needs ZS of TPC data to work. ---
2 Triggered main DAQ mode Main selection is external trigger counter ---
3 Immediate triggered mode Use TOC triggered mode (only outputs data in window) or SSP triggered mode to avoid bottleneck. This is a fallback option of there is bottleneck in either RCE or SSP data.
4 Triggered window mode TPC in triggered non-zero suppressed mode Use before we are happy with ZS in RC
5 Wide-window burst mode TPC in burst mode with the longest window possible (512MB buffer = 0.5s). Special run mode for offline ZS studies
6 Burst mode Collect data in certain time window (could either determine this from a Nova time hash function, or using Penn board trigger input Fallback before ZS works in RCE, this is also the mode for measuring noise, i.e. this is the mode for November vertical slice test

Issues that need to be clarified

  • Purposes and architecture of the proposed online farm
  • Design of the metadata
  • Handling TPC stream data within the framework which is trigger-oriented, issues of timing and multiple interaction in temporally close slices
  • Possible necessity to duplicate parts of raw data to create overlaps, in order to make practical operation of the online farm