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GPU Photon Transport Simulation Studies Mary Murphy Undergraduate, UW-Madison Dmitry Chirkin IceCube at UW-Madison Tareq AbuZayyad IceCube at UW-River.

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Presentation on theme: "GPU Photon Transport Simulation Studies Mary Murphy Undergraduate, UW-Madison Dmitry Chirkin IceCube at UW-Madison Tareq AbuZayyad IceCube at UW-River."— Presentation transcript:

1 GPU Photon Transport Simulation Studies Mary Murphy Undergraduate, UW-Madison Dmitry Chirkin IceCube at UW-Madison Tareq AbuZayyad IceCube at UW-River Falls

2 Objectives Comparison of i3mcml and ppc-gpu Check for muon and flasher simulation output agreement Compare performance with time trials Test simulation parameters in ppc-gpu Vary light yield, ice properties, muon track generator, sensitivity parameters, etc. to observe and analyze response

3 Comparison of i3mcml and ppc-gpu SimulationI3mcml v0.9.6.2I3mcml v0.9.8.2Ppc-gpu v8Ppc-gpu v31 Real Time (s)53.523.1535.118.0 CPU Process Time (s) 53.22.906.422.20 CPU System Time (s) 0.290.390.830.69 GPU Time (s)--19.8627.8014.51 Number of Hits 41,39641,20241,40340,556 Time trials run with same input f2k muons, same GPU device In both simulations, subsequent versions reduced run time Latest version of ppc-gpu is 123 times faster than CPU version Muon Simulation Run Time Comparison

4 Comparison of i3mcml and ppc-gpu SimulationI3mcml v0.9.6.2I3mcml v0.9.8.2Ppc-gpu v8Ppc-gpu v31 Real Time (s)12.585.119.184.46 CPU Process Time (s) 12.230.560.610.30 CPU System Time (s) 0.210.340.180.24 GPU Time (s)--4.218.613.97 Number of Hits 150,778150,164152,294150,060 Flasher Simulation Run Time Comparison Time trials run flashing 1.e8 photons on dom 20, string 20 Similar time trials run on different locations around detector to eliminate any variations due possibly to which dom is flashing

5 Comparison of i3mcml and ppc-gpu Demonstrates strong agreement! DOM Occupancy plot for flasher run down string 83

6 Simulation parameters in ppc-gpu Comparison of Assembly and GPU versions of PPC

7 Simulation parameters in ppc-gpu Cascade light yield parameterization new M. Kowalski ’ s vs. older Ch. Wiebusch cascade parametrizations: up to 20% difference; same bare muon parametrization

8 Simulation parameters in ppc-gpu AHA ice properties bulk ice properties Angular Sensitivity

9 Simulation parameters in ppc-gpu Angular Sensitivity AHA ice properties Simulation parameters in ppc-gpu Angular Sensitivity bulk ice properties

10 Simulation parameters in ppc-gpu Angular Sensitivity AHA ice properties bulk ice properties

11 Simulation parameters in ppc-gpu Muon Track Generator

12 COG distribution for MMC / CORSIKA muons after Simple Majority Triggering Multiplicity 8 applied

13 Simulation parameters in ppc-gpu Muon Track Generator

14 Simulation parameters in ppc-gpu OM Sensitivity

15 The End Back-up slides follow.

16 Output comparison of ppc-gpu and i3mcml

17 MKOW (red) vs. old default (black) COG distribution

18 DOM Occupancy with input CORSIKA muon bundles, in bulk and aha model ice

19 COG distribution for various OM sensitivity levels

20 COG distribution for various OM sensitivity levels, in bulk ice


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