IceCube simulation with PPC

Dmitry Chirkin, UW Madison

photon propagation code

Direct photon tracking with PPC

• simulating flasher/standard candle photons• same code for muon/cascade simulation

• using precise scattering function: linear combination of HG+SAM• using tabulated (in 10 m depth slices) layered ice structure• employing 6-parameter ice model to extrapolate in wavelength

• tilt in the ice layer structure is properly taken into account

• transparent folding of acceptance and efficiencies• precise tracking through layers of ice, no interpolation needed

• precise simulation of the longitudinal development of cascades and• angular distribution of particles emitting Cherenkov photons

photon propagation code

Updates to ppc since last meetingPPC:

• LONG: simulate longitudinal cascade development• ANGW: smear cherenkov cone due to shower development• Corrected ice density to average at detector center• Made the code scalable with the number of GPU multiprocessors• The flasher simulation now uses the wavelength profile read from file wv.dat• Randomized the simulation based on system time (with us resolution)• Modified code to run CPU and GPU parts concurrently• Added option to disable a multiprocessor• Added the implementation of the simple approximate Mie scattering function• Added a configuration file "cfg.txt"• New oversized DOM treatment (designed for minimum bias compared to oversize=1):

oversize only in direction perpendicular to the photon time needed to reach the nominal (non-oversized) DOM surface is added re-use the photon after it hits a DOM and ensure the causality in the flasher simulation

nominal DOMoversized DOM

oversized ~ 5 times

phot

on

Timing of oversized DOM MC

xR=1defaultdo not track back to detected DOMdo not track after detectionno ovesize delta correction!do not check causalitydel=(sqrtf(b*b+(1/(e.zR*e.zR-1)*c)-D)*e.zR-hdel=e.R-OMR

Flashing 63-50 63-48

64-48

64-52

xR=1

default

Photon angular profile

from thesis of Christopher Wiebusch

New ice density: 0.9216 mwe

handbook of chemistry and physics

T.Gow's data of density near the surface

T=221.5-0.00045319*d+5.822e-6*d2-273.15 (fit to AMANDA data)

Fit to (1-p1*exp(-p2*d))*f(T(d))*(1+0.94e-12*9.8*917*d)

Simplified Mie Scattering

Single radius particles, described better as smaller angles by SAM

Also known as the Liu scattering function

Introduced by Jon Miller

New approximation to Mie

fSAM

ppc icetray module

• at http://code.icecube.wisc.edu/svn/projects/ppc/trunk/

• uses a wrapper: private/ppc/i3ppc.cxx, which compiles by cmake system into the libppc.so

• it is necessary to compile an additional library libxppc.so by running make in private/ppc/gpu:

“make glib” compiles gpu-accelerated version (needs cuda tools) “make clib” compiles cpu version (from the same sources!)

• link to libxppc.so and libcudart.so (if gpu version) from build/lib directory

• this library file must be loaded before the libppc.so wrapper library

These steps are automated with a resouces/make.sh script

ppc example script run.pyif(len(sys.argv)!=6): print "Use: run.py [corsika/nugen/flasher] [gpu] [seed] [infile/num of flasher events] [outfile]" sys.exit()…det = "ic86"detector = False…os.putenv("PPCTABLESDIR", expandvars("$I3_BUILD/ppc/resources/ice/mie"))…if(mode == "flasher"): … str=63 dom=20 nph=8.e9

tray.AddModule("I3PhotoFlash", "photoflash")(…)

os.putenv("WFLA", "405") # flasher wavelength; set to 337 for standard candles os.putenv("FLDR", "-1") # direction of the first flasher LED … # Set FLDR=x+(n-1)*360, where 0<=x<360 and n>0 to simulate n LEDs in a # symmetrical n-fold pattern, with first LED centered in the direction x. # Negative or unset FLDR simulates a symmetric in azimuth pattern of light.

tray.AddModule("i3ppc", "ppc")( ("gpu", gpu), ("bad", bad), ("nph", nph*0.1315/25), # corrected for efficiency and DOM oversize factor; eff(337)=0.0354 ("fla", OMKey(str, dom)), # set str=-str for tilted flashers, str=0 and dom=1,2 for SC1 and 2 )

else:

ppc-pick and ppc-eff

ppc-pick: restrict to primaries below MaxEpri

load("libppc-pick")

tray.AddModule("I3IcePickModule<I3EpriFilt>","emax")( ("DiscardEvents", True), ("MaxEpri", 1.e9*I3Units.GeV) )

ppc-eff: reduce efficiency from 1.0 to eff

load("libppc-eff")

tray.AddModule("AdjEff", "eff")( ("eff", eff) )

Todo list from the last meeting

• need to: verify that it works for V02-04-00 of simulation add code to treat high-efficient DOMs correctly verify that it works for IC59 improve flasher simulation (interface with photoflash) figure out the best way to compile

All done!

Done?

ppc homepage

http://icecube.wisc.edu/~dima/work/WISC/ppc

GPU scalingOriginal: 1/2.08 1/2.70CPU c++: 1.00 1.00Assembly: 1.25 1.37GTX 295: 147 157GTX/Ori: 307 424C1060: 104 112C2050: 157 150GTX 480: 210 204

On GTX 295: 1.296 GHzRunning on 30 MPs x 448 threadsKernel uses: l=0 r=35 s=8176 c=62400

On GTX 480: 1.401 GHzRunning on 15 MPs x 768 threadsKernel uses: l=0 r=40 s=3960 c=62400

On C1060: 1.296 GHzRunning on 30 MPs x 448 threadsKernel uses: l=0 r=35 s=3992 c=62400

On C2050: 1.147 GHzRunning on 14 MPs x 768 threadsKernel uses: l=0 r=41 s=3960 c=62400

Uses cudaGetDeviceProperties() to get the number of multiprocessors,Uses cudaFuncGetAttributes() to get the maximum number of threads

Kernel time calculationRun 3232 (corsika) IC86 processing on cuda002 (per file):

GTX 295: Device time: 1123741.1 (in-kernel: 1115487.9...1122539.1) [ms]GTX 480: Device time: 693447.8 (in-kernel: 691775.9...693586.2) [ms]

If more than 1 thread is running using same GPU:

Device time: 1417203.1 (in-kernel: 1072643.6...1079405.0) [ms]

3 counters: 1. time difference before/after kernel launch in host code2. in-kernel, using cycle counter: min thread time3. max thread time

Also, real/user/sys times of top:

gpus 6cpus 1cores 8files 693Real 749m4.693sUser 3456m10.888ssys 39m50.369sDevice time: 245312940.1 216887330.9 218253017.2 [ms]

files: 693 real: 64.8553 user: 37.8357 gpu: 58.9978 kernel: 52.4899 [seconds]

81%-91% GPU utilization

Concurrent execution

time

CPU GPU CPU GPUThread 1:

CPU GPU CPUGPUThread 2:

CPU

GPU

CPU

GPU

CPU

GPU

CPU

GPUOne thread:

Create track segments

Copy track segments to GPU

Process photon hits

Copy photon hits from GPU

Need 2 buffers for track segments and photon hits

However: have 2 buffers:1 on host and 1 on GPU!Just need to synchronize

before the buffers are re-used

BAD multiprocessors (MPs)clistcudatest 0 1 2 3 4 5cuda001 0 1 2 3 4 5cuda002 0 1 2 3 4 5cuda003 0 1 2 3 4 5

#badmpscuda001 3 22cuda002 2 20cuda002 4 10

Disable 3 bad GPUs out of 24: 12.5%Disable 3 bad MPs out of 720: 0.4%!

Configured: xR=5 eff=0.95 sf=0.2 g=0.943Loaded 12 angsens coefficientsLoaded 6x170 dust layer pointsLoaded 16028 random multipliersLoaded 42 wavelenth pointsLoaded 171 ice layersLoaded 3540 DOMs (19x19)Processing f2k muons from stdin on device 2Total GPU memory usage: 83053520photons: 13762560 hits: 991Error: TOT was a nan or an inf 1 times! Bad MP #20photons: 13762560 hits: 393photons: 13762560 hits: 570photons: 13762560 hits: 501photons: 13762560 hits: 832photons: 13762560 hits: 717CUDA Error: unspecified launch failure

Total GPU memory usage: 83053520photons: 13762560 hits: 938Error: TOT was a nan or an inf 9 times! Bad MP #20 #20 #20 #20photons: 13762560 hits: 442photons: 13762560 hits: 627CUDA Error: unspecified launch failure

[dima@cuda002 gpu]$ cat mmc.1.f2k | BADMP=20 ./ppc 2 > /dev/nullConfigured: xR=5 eff=0.95 sf=0.2 g=0.943Loaded 12 angsens coefficientsLoaded 6x170 dust layer pointsLoaded 16028 random multipliersLoaded 42 wavelenth pointsLoaded 171 ice layersLoaded 3540 DOMs (19x19)Processing f2k muons from stdin on device 2Not using MP #20Total GPU memory usage: 83053520photons: 13762560 hits: 871…photons: 1813560 hits: 114

Device time: 31970.7 (in-kernel: 31725.6...31954.8) [ms]

Failure rates:

Typical run times

corsika: run 3232: 10493 10.0345 sec filesic86/spx/3232 on cuda00[123] (53.4 seconds per job)1.2 days of real detector time in 6.5 days

nugen: run 2972: 9993 200000-event files; E^-2 weightedic86/spx/2972 on cudatest (25.1 seconds per job)entire 10k set of files in 2.9 days this is enough for an atmnu/diffuse analysis!

Considerations:

• Maximize GPU utilization by running only mmc+ppc parts on the GPU nodes• still, IC40 mmc+ppc+detector was run with ~80% GPU utilization

• run with 100% DOM efficiency, save all ppc events with at least 1 MC hit• apply a range of allowed efficiencies (70-100%) later with ppc-eff module