GPU Photon Transport Simulation StudiesMary Murphy Undergraduate, UW-Madison

Dmitry Chirkin IceCube at UW-Madison

Tareq AbuZayyad IceCube at UW-River Falls

ObjectivesComparison of i3mcml and ppc-gpu Check for muon and flasher simulation

output agreement Compare performance with time trialsTest simulation parameters in ppc-gpu Vary light yield, ice properties, muon track

generator, sensitivity parameters, etc. to observe and analyze response

Comparison of i3mcml and ppc-gpu

Simulation I3mcml v0.9.6.2

I3mcml v0.9.8.2

Ppc-gpu v8 Ppc-gpu v31

Real Time (s) 53.5 23.15 35.1 18.0CPU Process Time (s)

53.2 2.90 6.42 2.20

CPU System Time (s)

0.29 0.39 0.83 0.69

GPU Time (s) -- 19.86 27.80 14.51Number of Hits

41,396 41,202 41,403 40,556

•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

Comparison of i3mcml and ppc-gpu

Simulation I3mcml v0.9.6.2

I3mcml v0.9.8.2

Ppc-gpu v8 Ppc-gpu v31

Real Time (s) 12.58 5.11 9.18 4.46CPU Process Time (s)

12.23 0.56 0.61 0.30

CPU System Time (s)

0.21 0.34 0.18 0.24

GPU Time (s) -- 4.21 8.61 3.97Number of Hits

150,778 150,164 152,294 150,060

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

Comparison of i3mcml and ppc-gpu

Demonstrates strong agreement!

DOM Occupancy plot for flasher run down string 83

Simulation parameters in ppc-gpuComparison of Assembly and GPU versions of PPC

Simulation parameters in ppc-gpuCascade light yield parameterization

•new M. Kowalski’s vs. older Ch. Wiebusch cascade parametrizations: up to 20% difference; same bare muon parametrization

Simulation parameters in ppc-gpu

AHA ice properties bulk ice

properties

Angular Sensitivity

Simulation parameters in ppc-gpuAngular Sensitivity

AHA ice properties

Simulation parameters in ppc-gpuAngular Sensitivity

bulk ice properties

Simulation parameters in ppc-gpuAngular Sensitivity

AHA ice properties bulk ice

properties

Simulation parameters in ppc-gpuMuon Track Generator

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

Simulation parameters in ppc-gpuMuon Track Generator

Simulation parameters in ppc-gpuOM Sensitivity

The End

Back-up slides follow.

Output comparison of ppc-gpu and i3mcml

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

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

COG distribution for various OM sensitivity levels

COG distribution for various OM sensitivity levels, in bulk ice