1. IceCube Institutional Memorandum Of Understanding (MOU)
    2. Summary:
    3. Faculty:
    4. Scientists and Post Docs:
    5. Students:
    6. Computing Resources:

Last updated on: August 18, 2009

 

 

Last updated on: August 18, 2009

 



IceCube Institutional Memorandum Of Understanding (MOU)

 

  

  Pennsylvania State University
(Doug Cowen)
6 (3 3 2)
2.1 Program Management
2.2 Detector Operations & Maintenance
2.3 Computing & Data Management
2.4 Triggering & Filtering
2.5 Data Quality, Reconstruction & Simulation Tools
Total

 
0.30
0.21
0.58
0.70
0.47
2.26

 
 
Note 1
note 2
note 3
note 4
note 5
 
 

 
 
(1). ExecCom member (Cowen, 0.2); outreach (Cowen 0.05, DeYoung 0.05)  
    (2). Trigger software (Toale, 0.15 core); monitoring shifts (0.06)  
    (3). Maintain distributed computing (Lafebre, 0.25 core); simulation production (Lafebre + Dunkman, 0.33)  
    (4). Tau working group lead (Cowen, 0.25); TFT Board member (Cowen, 0.1); develop and verify Deep Core filters (Koskinen + Adams, 0.35)  
    (5). Development of starting track reconstruction (Lafebre + Dunkman, 0.25); coordinate Deep Core reconstruction for production (Lafebre + Adams, 0.12); maintain tau simulation tools (Toale, 0.1)    

 

 


Summary:

Penn State contributions to the maintenance and operations of IceCube include:

•  Major responsibility for the trigger systems and trigger configuration database

•  Support for execution of simulation production and data processing (L2) on the PSU “lion” clusters, comprising a total of 2176 computin


g cores (discussed in more detail below)

•  Development of filtering and reconstruction software for the Deep Core data stream

•  Support for the tau analysis effort, including MC software tools and leadership of the working group

 


Faculty:

Doug Cowen (L,+) - ExecComm member, TFT board member, Tau WG leader,  outreach, 100% IceCube

Peter Mészáros - theory, 10% IceCube

Tyce DeYoung - Deep Core filters, coordination with HAWC, outreach, 50%  IceCube


Scientists and Post Docs:

Patrick Toale - DAQ Trigger, Tau simulation/analysis, 50% IceCube

       Simulation modules: I3MCTagger, I3EventSummary

  Reconstruction modules: CLast, Cascade-gulliver, Taudp-gulliver,

   Tau-double-pulse

Sven Lafèbre – Python event display framework, develop starting track (hybrid) reconstruction, maintain distributed computing, simulation production, 100% IceCube

       Reconstruction modules: downgoing-pulsecombiner, distance-to-track,

   python-event-viewer, I3HybridReco

Jason Koskinen – Develop and verify Deep Core filters, 100% IceCube

        Reconstruction modules: DeepCoreVeto, fillRatio      


Students:

Laura Adams – Deep Core filter verification, coordination of production  reconstructions, 100% IceCube

Matt Dunkman – Simulation production, starting track reconstruction development,  100% IceCube

 


Computing Resources:

The Penn State IceCube group has access to several large computing clusters maintained and administered by the Penn State High Performance Computing group, comprising a total of 2176 computing cores. Of these, the Penn State group has priority on 48 cores. Our historical average utilization for the past year has been 100-200 cores, with peak usage levels around 500 cores for several weeks at a time.

We have contributed substantially to simulation production, including the entire collaboration-wide simulation of tau neutrinos, all Deep Core and IC+TWR simulation of electron, muon, and tau neutrinos, and a substantial amount of downgoing muon simulation for IC, IC+TWR, IC+Deep Core, and IC+HEE. These resources have also been used to run large amounts of the collaboration Level 2 IC40 filtering at Penn State under the direction of Martin Merck.

 

Note: The activities and staffing levels in this MoU are appropriate for the year beginning April 1, 2010. The staffing level of 6 (3 3 2) with 6.1 FTE on IceCube represents a considerable reduction from the previously assumed level of 7 (3 4 4) with 9.1 FTE, due to lower than expected levels of NSF base grant funding. As a result we have been forced to reduce our M&O level of effort from the original 3.94 FTE to the present 2.26 FTE, by reducing the level of effort in DAQ trigger support, eliminating support for verification and flasher calibration activities, and eliminating contributions to the selection of science-ready data. The reduction of 1.68 FTE in M&O breaks down as a 0.75 FTE reduction in core support and a 0.93 FTE reduction in in-kind support.

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