heterogeneity (#27)

Prepare things to work with heterogeneity, make things work on GPU

Reviewed-on: Rubydragon/MetagraphOptimization.jl#27
Co-authored-by: Anton Reinhard <anton.reinhard@proton.me>
Co-committed-by: Anton Reinhard <anton.reinhard@proton.me>
This commit is contained in:
Anton Reinhard 2023-12-18 14:31:52 +01:00 committed by Anton Reinhard
parent c90346e948
commit 92e0eeaaef
42 changed files with 1631 additions and 238 deletions

View File

@ -22,7 +22,9 @@ jobs:
version: '1.9.2'
- name: Instantiate
run: julia --project=./ -e 'using Pkg; Pkg.instantiate()'
run: |
julia --project=./ -e 'using Pkg; Pkg.instantiate()'
julia --project=./ -e 'using Pkg; Pkg.add(url="https://github.com/QEDjl-project/QEDprocesses.jl/")'
- name: Format check
run: |
@ -32,7 +34,7 @@ jobs:
if out == ""
exit(0)
else
@error "Some files have not been formatted !!!"
@error "Some files have not been formatted!!!"
write(stdout, out)
exit(1)
end'

View File

@ -15,6 +15,7 @@ QEDbase = "10e22c08-3ccb-4172-bfcf-7d7aa3d04d93"
QEDprocesses = "46de9c38-1bb3-4547-a1ec-da24d767fdad"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
Roots = "f2b01f46-fcfa-551c-844a-d8ac1e96c665"
StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
[extras]

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@ -0,0 +1,16 @@
operations,graph_nodes,graph_edges,graph_ce,graph_dt,graph_ci,gen_func_t,cpu_compile_t,cpu_st_t,cpu_mt_t,gpu_compile_t,gpu_t
0,77,101,252.0,6240.0,0.04038461538461539,0.02087051,8.691e-6,3.405098066,0.244763721,1.565749515,0.936213163
1,76,99,246.0,6240.0,0.03942307692307692,0.020658734,9.36e-6,3.244313848,0.230460257,1.548012602,0.887605389
2,75,97,240.0,6240.0,0.038461538461538464,0.045333482,8.74e-6,3.163679857,0.217614064,1.52780456,0.816496837
3,74,95,234.0,6240.0,0.0375,0.020314034,9.081e-6,2.956421016,0.183415997,1.524262179,0.793770075
4,73,93,228.0,6240.0,0.03653846153846154,0.033579409,8.52e-6,2.845414866,0.19168374,1.50907807,0.742734411
5,72,92,228.0,6144.0,0.037109375,0.019736718,8.87e-6,2.827109937,0.207452606,1.497203204,0.719774022
6,71,90,222.0,6144.0,0.0361328125,0.043612693,1.01e-5,2.62776692,0.166492497,1.602060948,0.668929854
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14,63,81,205.0,5568.0,0.03681752873563218,0.029946916,8.93e-6,2.469922022,0.179443854,1.485935831,0.651804318
1 operations graph_nodes graph_edges graph_ce graph_dt graph_ci gen_func_t cpu_compile_t cpu_st_t cpu_mt_t gpu_compile_t gpu_t
2 0 77 101 252.0 6240.0 0.04038461538461539 0.02087051 8.691e-6 3.405098066 0.244763721 1.565749515 0.936213163
3 1 76 99 246.0 6240.0 0.03942307692307692 0.020658734 9.36e-6 3.244313848 0.230460257 1.548012602 0.887605389
4 2 75 97 240.0 6240.0 0.038461538461538464 0.045333482 8.74e-6 3.163679857 0.217614064 1.52780456 0.816496837
5 3 74 95 234.0 6240.0 0.0375 0.020314034 9.081e-6 2.956421016 0.183415997 1.524262179 0.793770075
6 4 73 93 228.0 6240.0 0.03653846153846154 0.033579409 8.52e-6 2.845414866 0.19168374 1.50907807 0.742734411
7 5 72 92 228.0 6144.0 0.037109375 0.019736718 8.87e-6 2.827109937 0.207452606 1.497203204 0.719774022
8 6 71 90 222.0 6144.0 0.0361328125 0.043612693 1.01e-5 2.62776692 0.166492497 1.602060948 0.668929854
9 7 70 89 222.0 6048.0 0.03670634920634921 0.042731148 1.053e-5 2.631288029 0.185812224 1.514154792 0.694503947
10 8 69 87 216.0 6048.0 0.03571428571428571 0.042148711 8.19e-6 2.493343257 0.183595081 1.506478504 0.652420896
11 9 68 86 216.0 5952.0 0.036290322580645164 0.041568955 8.571e-6 2.487317627 0.147773078 1.472141844 0.653143947
12 10 67 85 216.0 5856.0 0.036885245901639344 0.041307868 9.13e-6 2.491634709 0.175728138 1.482162906 0.63058774
13 11 66 84 216.0 5760.0 0.0375 0.041265756 8.43e-6 2.516916643 0.180420842 1.463053866 0.650627815
14 12 65 83 205.0 5760.0 0.035590277777777776 0.039711293 9.22e-6 2.479664249 0.178013433 1.459566956 0.652477867
15 13 64 82 205.0 5664.0 0.03619350282485876 0.030866093 8.87e-6 2.485424881 0.179983608 1.564961227 0.647932468
16 14 63 81 205.0 5568.0 0.03681752873563218 0.029946916 8.93e-6 2.469922022 0.179443854 1.485935831 0.651804318

View File

@ -0,0 +1,176 @@
operations,graph_nodes,graph_edges,graph_ce,graph_dt,graph_ci,gen_func_t,cpu_compile_t,cpu_st_t,cpu_mt_t,gpu_compile_t,gpu_t
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5,346,483,1399.0,30048.0,0.04655883919062833,0.076034997,4.3191e-5,17.766336956,0.967055891,2.187609178,4.922574669
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78,200,301,1399.0,23040.0,0.06072048611111111,0.155978707,2.4051e-5,17.624250437,0.794935481,2.247188963,4.940403894
79,198,298,1399.0,22944.0,0.06097454672245467,0.158377905,2.5091e-5,17.634938402,0.754743461,2.245248812,4.919902064
80,196,296,1399.0,22848.0,0.061230742296918765,0.158750786,2.4511e-5,17.6360904,0.750867213,2.200032233,4.942215648
81,194,293,1399.0,22752.0,0.061489099859353025,0.161152794,2.4831e-5,17.780761042,0.765338482,2.204873372,4.939655562
82,192,290,1399.0,22656.0,0.061749646892655365,0.160175486,2.318e-5,17.798147683,0.76168194,2.230891056,4.955801153
83,190,287,1399.0,22560.0,0.06201241134751773,0.159868767,2.4791e-5,17.764165058,0.796377137,2.239618185,4.928054627
84,188,283,1399.0,22464.0,0.06227742165242165,0.160933577,2.4221e-5,17.798426962,0.848255338,2.218112612,4.932433146
85,186,280,1399.0,22368.0,0.06254470672389127,0.163393917,2.4371e-5,17.808464853,0.765692696,2.213490844,4.943298137
86,184,277,1399.0,22272.0,0.06281429597701149,0.163792118,2.4261e-5,17.805783627,0.761027705,2.232891092,4.919454211
87,182,275,1399.0,22176.0,0.06308621933621934,0.162177953,2.43e-5,17.797665375,0.761040026,2.236586089,4.951072155
88,180,271,1399.0,22080.0,0.06336050724637682,0.165377424,2.557e-5,17.805099359,0.763146286,2.212611436,4.921150887
89,178,268,1399.0,21984.0,0.06363719068413391,0.166754373,2.5141e-5,17.770997205,0.764361801,2.199943181,4.934748884
90,176,266,1399.0,21888.0,0.06391630116959064,0.167241957,2.4571e-5,17.770223198,0.759580227,2.247867501,4.935730147
91,174,264,1399.0,21792.0,0.06419787077826726,0.169623073,2.5e-5,17.771153368,0.750276145,2.243455929,4.939933808
92,172,261,1399.0,21696.0,0.06448193215339233,0.168358288,2.5181e-5,17.799224982,0.760906435,2.210000929,4.943923374
93,170,259,1399.0,21600.0,0.06476851851851852,0.170287483,2.529e-5,17.79271252,0.763151029,2.205444892,4.924953813
94,168,254,1399.0,21504.0,0.06505766369047619,0.168986856,2.5021e-5,17.775583682,0.760237647,2.222811993,4.951301097
95,166,250,1399.0,21408.0,0.06534940209267563,0.171662521,2.4401e-5,17.636022254,0.749599438,2.234944605,4.958431762
96,164,246,1399.0,21312.0,0.06564376876876876,0.170911431,2.4481e-5,17.633556045,0.788097892,2.198060879,4.922871993
97,162,244,1399.0,21216.0,0.06594079939668175,0.172387252,2.4781e-5,17.620254381,0.799269067,2.202436673,4.936411908
98,160,241,1399.0,21120.0,0.0662405303030303,0.171830017,2.581e-5,17.656653806,0.750275098,2.200933622,4.94776375
99,158,238,1399.0,21024.0,0.06654299847792998,0.174560093,2.447e-5,17.625724723,0.756745741,2.249721096,4.958786002
100,156,235,1399.0,20928.0,0.06684824159021406,0.178996759,2.453e-5,17.669194606,0.749422535,2.218089817,4.960858653
101,154,231,1399.0,20832.0,0.0671562980030722,0.175032127,2.3871e-5,17.642586975,0.754643863,2.194675279,4.944134534
102,152,229,1399.0,20736.0,0.06746720679012345,0.176393906,2.4731e-5,17.592973556,0.749943551,2.229565622,4.927935661
103,150,225,1399.0,20640.0,0.06778100775193799,0.178017631,2.412e-5,17.630568322,0.755272802,2.221125776,4.952348991
104,148,223,1399.0,20544.0,0.0680977414330218,0.175897841,2.36e-5,17.661766307,0.749293633,2.2201698,4.963634779
105,146,221,1399.0,20448.0,0.06841744913928012,0.178367362,2.5001e-5,17.654508999,0.755361234,2.185187066,4.938710949
106,144,218,1399.0,20352.0,0.06874017295597484,0.178791594,2.502e-5,17.649520916,0.749748217,2.238645461,4.955141284
107,142,216,1399.0,20256.0,0.06906595576619273,0.175900502,2.3291e-5,17.648252045,0.755157659,2.250102545,4.948078116
108,140,212,1399.0,20160.0,0.06939484126984127,0.180050739,2.3901e-5,17.642556024,0.751139061,2.195233955,4.92102672
109,138,210,1399.0,20064.0,0.06972687400318979,0.182587052,2.492e-5,17.631301401,0.754040144,2.177296385,4.948297571
110,136,207,1399.0,19968.0,0.07006209935897435,0.181449712,2.4401e-5,17.618787463,0.748940439,2.251932822,4.950366155
111,134,203,1399.0,19872.0,0.07040056360708534,0.183466877,2.407e-5,17.658532693,0.756589176,2.240568188,4.97337861
112,132,201,1399.0,19776.0,0.0707423139158576,0.181545084,2.485e-5,17.63441504,0.751343023,2.183033772,4.975534251
113,130,199,1399.0,19680.0,0.07108739837398374,0.177809314,2.417e-5,17.627163359,0.754577307,2.211080446,4.977438563
114,128,195,1399.0,19584.0,0.07143586601307189,0.183038393,2.5541e-5,17.63366534,0.751510139,2.237832092,4.969644912
115,126,191,1399.0,19488.0,0.07178776683087028,0.186344151,2.4971e-5,17.711808739,0.759177,2.236586017,4.951292022
116,124,187,1399.0,19392.0,0.07214315181518152,0.184833587,2.475e-5,17.648467279,0.749564641,2.179772409,4.97017709
117,122,183,1399.0,19296.0,0.07250207296849089,0.193249355,2.3811e-5,17.639230223,0.755564354,2.195109482,4.982434629
118,120,180,1399.0,19200.0,0.07286458333333333,0.186818046,2.372e-5,17.635977046,0.750626058,2.243877912,4.972608068
119,118,177,1399.0,19104.0,0.07323073701842546,0.189204719,2.4961e-5,17.791522288,0.766082656,2.242948358,4.980365418
120,116,173,1399.0,19008.0,0.07360058922558922,0.186391669,2.4181e-5,17.645956891,0.750893368,2.197914806,4.98745469
121,114,171,1399.0,18912.0,0.07397419627749577,0.19060573,2.4701e-5,17.771140583,0.765197694,2.20643796,4.959618561
122,112,169,1399.0,18816.0,0.0743516156462585,0.188466188,2.381e-5,17.795228145,0.759434429,2.26208531,4.965068853
123,110,165,1399.0,18720.0,0.07473290598290598,0.191524927,2.3841e-5,17.779734215,0.767242896,2.242967333,4.950554681
124,108,161,1399.0,18624.0,0.07511812714776632,0.189450326,2.3601e-5,17.807849571,0.762371273,2.196711688,4.966122065
125,106,157,1399.0,18528.0,0.0755073402417962,0.191473057,2.357e-5,17.632877767,0.755845465,2.188474891,4.977562868
126,104,153,1399.0,18432.0,0.0759006076388889,0.191382079,2.3851e-5,17.775729988,0.758861116,2.278116886,4.979965119
127,102,151,1399.0,18336.0,0.07629799301919721,0.192296369,2.394e-5,17.777918793,0.764981303,2.224818047,4.949944943
128,100,149,1399.0,18240.0,0.07669956140350877,0.191424719,2.4331e-5,17.856475915,0.76057459,2.201588049,4.941974925
129,98,146,1399.0,18144.0,0.07710537918871252,0.194280932,2.3951e-5,17.779963845,0.766401736,2.223182601,4.961465017
130,96,142,1399.0,18048.0,0.07751551418439716,0.192850597,2.3861e-5,17.765033828,0.760509569,2.250897799,4.967399083
131,94,138,1399.0,17952.0,0.07793003565062388,0.194741823,2.38e-5,17.778261696,0.764271609,2.248898068,4.975998565
132,92,136,1399.0,17856.0,0.07834901433691756,0.193567295,2.5281e-5,17.791322862,0.759809249,2.216694812,4.962092553
133,90,132,1399.0,17760.0,0.07877252252252252,0.196949912,2.4641e-5,17.775924767,0.766636532,2.192664527,4.943809886
134,88,129,1399.0,17664.0,0.07920063405797101,0.19423328,2.4491e-5,17.775940481,0.759698903,2.241454301,4.965419114
135,86,125,1399.0,17568.0,0.07963342440801457,0.196021362,2.4541e-5,17.749824568,0.77002309,2.244133161,4.973507276
136,84,123,1399.0,17472.0,0.08007097069597069,0.195945063,2.4791e-5,17.793381264,0.758984676,2.223761942,4.967845004
137,82,120,1399.0,17376.0,0.0805133517495396,0.196404909,2.5491e-5,17.781126567,0.76777764,2.208548873,4.942758101
138,80,116,1399.0,17280.0,0.08096064814814814,0.197313346,2.469e-5,17.785944557,0.814271788,2.200296465,4.939179018
139,78,114,1399.0,17184.0,0.08141294227188083,0.155633427,2.5181e-5,17.79491891,0.767423131,2.233213884,4.963944358
140,76,111,1399.0,17088.0,0.08187031835205992,0.194686919,2.4311e-5,17.835512877,0.761171578,2.216772786,4.968370761
141,74,108,1399.0,16992.0,0.0823328625235405,0.19895497,2.4301e-5,17.80769545,0.768202031,2.212642548,4.971369432
142,72,106,1399.0,16896.0,0.08280066287878787,0.197589165,2.4241e-5,17.817799582,0.760097766,2.219367009,4.967751237
143,70,102,1399.0,16800.0,0.08327380952380953,0.200103786,2.425e-5,17.804210307,0.767108387,2.264925155,4.965506236
144,68,99,1399.0,16704.0,0.08375239463601533,0.196633322,2.5371e-5,17.822197608,0.762852947,2.20877412,4.971541033
145,66,97,1399.0,16608.0,0.08423651252408478,0.200144552,2.4801e-5,17.823667792,0.766965999,2.209992675,4.969252216
146,64,93,1399.0,16512.0,0.08472625968992248,0.199816644,2.4901e-5,17.838429006,0.764432365,2.241092809,4.961995819
147,62,89,1399.0,16416.0,0.08522173489278752,0.187325579,2.5321e-5,17.811923957,0.767393244,2.227406228,4.960056608
148,60,85,1399.0,16320.0,0.08572303921568628,0.198893612,2.4451e-5,17.82940565,0.760747136,2.209815727,4.971563658
149,58,83,1399.0,16224.0,0.08623027613412229,0.201039293,2.4651e-5,17.817639935,0.767607352,2.210546374,4.97066195
150,56,81,1399.0,16128.0,0.08674355158730158,0.199841932,2.414e-5,17.82203287,0.760048809,2.243550629,4.954439346
151,54,79,1399.0,16032.0,0.0872629740518962,0.2011596,2.4741e-5,17.804574042,0.767800679,2.250206119,4.955980994
152,52,75,1399.0,15936.0,0.08778865461847389,0.19971389,2.4331e-5,17.829821975,0.762018993,2.205143141,4.970086548
153,50,73,1399.0,15840.0,0.08832070707070708,0.201368798,2.4881e-5,17.836101646,0.767371477,2.218711432,4.96364023
154,48,71,1399.0,15744.0,0.08885924796747967,0.200798594,2.4491e-5,17.830384655,0.765407907,2.286796949,4.939295093
155,46,67,1399.0,15648.0,0.08940439672801637,0.202551163,2.5121e-5,17.827221721,0.768466657,2.262575248,4.943430916
156,44,65,1399.0,15552.0,0.08995627572016461,0.198816901,2.578e-5,17.840506569,0.760760306,2.220630133,4.952844324
157,42,63,1399.0,15456.0,0.09051501035196688,0.201424744,2.5021e-5,17.814439397,0.767553139,2.196934945,4.958506547
158,40,59,1399.0,15360.0,0.09108072916666667,0.202145126,2.565e-5,17.808712307,0.76137146,2.235801178,4.949559042
159,38,55,1399.0,15264.0,0.0916535639412998,0.201663393,2.4591e-5,17.784477195,0.766209648,2.249329555,4.964028527
160,36,53,1399.0,15168.0,0.09223364978902954,0.199579456,2.5461e-5,17.900752023,0.761934363,2.209582978,4.950507063
161,34,48,1399.0,15072.0,0.09282112526539278,0.159541692,2.5211e-5,17.769415534,0.935609132,2.216664395,4.962977201
162,32,44,1399.0,14976.0,0.09341613247863248,0.201979445,2.5581e-5,17.802148727,0.758630938,2.257162782,4.954367291
163,30,40,1399.0,14880.0,0.09401881720430108,0.203381244,2.5411e-5,17.808584074,0.768160516,2.239967841,4.949515694
164,28,35,1399.0,14784.0,0.09462932900432901,0.200707381,2.5071e-5,17.811958674,0.765546396,2.222827481,4.962523474
165,26,31,1399.0,14688.0,0.09524782135076253,0.203476579,2.4431e-5,17.791537057,0.759747517,2.210172596,4.96717851
166,24,29,1399.0,14592.0,0.09587445175438597,0.38619058,2.5161e-5,17.784565893,0.765981903,2.205094732,4.970469758
167,22,25,1399.0,14496.0,0.09650938189845475,0.209174268,2.6071e-5,17.886396985,0.762283972,2.251379768,4.9348063
168,20,21,1399.0,14400.0,0.09715277777777778,0.184182012,2.5331e-5,17.791795342,0.760972528,2.229551257,4.941190792
169,18,17,1399.0,14304.0,0.09780480984340045,0.203935864,2.572e-5,17.823665061,0.762353868,2.199132836,4.965200905
170,16,15,1399.0,14208.0,0.09846565315315316,0.200164969,2.4631e-5,17.792385586,0.76804392,2.174965407,4.972074439
171,14,13,1399.0,14112.0,0.09913548752834467,0.204567903,2.5071e-5,17.806154396,0.759505453,2.2340466,4.972671228
172,12,11,1399.0,14016.0,0.09981449771689498,0.201861418,2.5971e-5,18.529840195,0.789347616,2.23167521,4.947890089
173,10,9,1399.0,13920.0,0.1005028735632184,0.202902727,2.4951e-5,17.865867105,0.761004999,2.194876208,4.93177029
174,8,7,1399.0,13824.0,0.10120081018518519,0.198079003,2.4651e-5,17.791197743,0.767399089,2.226370372,4.951979965
1 operations graph_nodes graph_edges graph_ce graph_dt graph_ci gen_func_t cpu_compile_t cpu_st_t cpu_mt_t gpu_compile_t gpu_t
2 0 356 493 1399.0 30528.0 0.0458267819706499 0.077070556 2.6761e-5 17.804336617 0.960385595 10.618577031 4.95440474
3 1 354 491 1399.0 30432.0 0.04597134595162986 1.030851104 2.37e-5 17.726472964 0.933074463 2.174912444 4.959474851
4 2 352 489 1399.0 30336.0 0.04611682489451477 0.376282553 2.3861e-5 17.935912907 0.968087391 2.238665483 4.912705328
5 3 350 487 1399.0 30240.0 0.04626322751322751 0.076651194 4.2451e-5 17.976779783 0.977130996 2.246167674 4.954520005
6 4 348 485 1399.0 30144.0 0.04641056263269639 0.223709216 2.8031e-5 17.67129111 0.97799748 2.175788856 4.923999491
7 5 346 483 1399.0 30048.0 0.04655883919062833 0.076034997 4.3191e-5 17.766336956 0.967055891 2.187609178 4.922574669
8 6 344 481 1399.0 29952.0 0.04670806623931624 0.398917781 4.3422e-5 17.709032771 0.971142926 2.170963978 4.917191185
9 7 342 479 1399.0 29856.0 0.04685825294748124 0.352569343 4.3801e-5 17.690255833 0.952966242 2.159295978 4.945842152
10 8 340 477 1399.0 29760.0 0.04700940860215054 0.117620751 4.2992e-5 17.905787431 0.749896479 2.19940915 4.922882222
11 9 338 475 1399.0 29664.0 0.04716154261057174 0.318053898 2.3481e-5 17.522775542 0.745113955 2.202366151 4.928734427
12 10 336 473 1399.0 29568.0 0.047314664502164504 0.184069985 2.3381e-5 17.529935879 0.74637911 2.238397648 4.919919125
13 11 334 471 1399.0 29472.0 0.047468783930510315 0.086029218 2.365e-5 17.560859257 0.75559668 2.249242933 4.956561058
14 12 332 469 1399.0 29376.0 0.04762391067538126 0.077326472 2.4361e-5 17.559317648 0.746726769 2.1818156 4.938490196
15 13 330 467 1399.0 29280.0 0.047780054644808743 0.169738661 2.342e-5 17.517109121 0.751453942 2.187781478 4.923659727
16 14 328 465 1399.0 29184.0 0.047937225877192985 0.077817676 2.315e-5 17.533304215 0.745481303 2.209343496 4.960503415
17 15 326 463 1399.0 29088.0 0.04809543454345434 0.171584444 2.352e-5 17.579912576 0.754778436 2.210370024 4.934281254
18 16 324 461 1399.0 28992.0 0.04825469094922737 0.084223667 2.305e-5 17.570464754 0.751290178 2.22797709 4.939806799
19 17 322 459 1399.0 28896.0 0.04841500553709856 0.123005102 2.3661e-5 17.605650973 0.756929676 2.269940175 4.937928844
20 18 320 457 1399.0 28800.0 0.04857638888888889 0.086677986 2.37e-5 17.5539199 0.746367967 2.264938904 4.959258096
21 19 318 455 1399.0 28704.0 0.04873885172798216 0.12293158 2.3711e-5 17.609395222 0.755783994 2.264754078 4.92827168
22 20 316 453 1399.0 28608.0 0.04890240492170023 0.124475123 2.4281e-5 17.597716228 0.75106304 2.20218749 4.933120236
23 21 314 451 1399.0 28512.0 0.04906705948372615 0.112172177 2.6391e-5 17.623178954 0.755694751 2.186417905 4.921509117
24 22 312 449 1399.0 28416.0 0.04923282657657658 0.219362642 2.321e-5 17.593459902 0.747914841 2.168628993 4.952994795
25 23 310 447 1399.0 28320.0 0.049399717514124294 0.080729209 2.358e-5 17.571675834 0.755489634 2.209531477 4.951190234
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160 158 40 59 1399.0 15360.0 0.09108072916666667 0.202145126 2.565e-5 17.808712307 0.76137146 2.235801178 4.949559042
161 159 38 55 1399.0 15264.0 0.0916535639412998 0.201663393 2.4591e-5 17.784477195 0.766209648 2.249329555 4.964028527
162 160 36 53 1399.0 15168.0 0.09223364978902954 0.199579456 2.5461e-5 17.900752023 0.761934363 2.209582978 4.950507063
163 161 34 48 1399.0 15072.0 0.09282112526539278 0.159541692 2.5211e-5 17.769415534 0.935609132 2.216664395 4.962977201
164 162 32 44 1399.0 14976.0 0.09341613247863248 0.201979445 2.5581e-5 17.802148727 0.758630938 2.257162782 4.954367291
165 163 30 40 1399.0 14880.0 0.09401881720430108 0.203381244 2.5411e-5 17.808584074 0.768160516 2.239967841 4.949515694
166 164 28 35 1399.0 14784.0 0.09462932900432901 0.200707381 2.5071e-5 17.811958674 0.765546396 2.222827481 4.962523474
167 165 26 31 1399.0 14688.0 0.09524782135076253 0.203476579 2.4431e-5 17.791537057 0.759747517 2.210172596 4.96717851
168 166 24 29 1399.0 14592.0 0.09587445175438597 0.38619058 2.5161e-5 17.784565893 0.765981903 2.205094732 4.970469758
169 167 22 25 1399.0 14496.0 0.09650938189845475 0.209174268 2.6071e-5 17.886396985 0.762283972 2.251379768 4.9348063
170 168 20 21 1399.0 14400.0 0.09715277777777778 0.184182012 2.5331e-5 17.791795342 0.760972528 2.229551257 4.941190792
171 169 18 17 1399.0 14304.0 0.09780480984340045 0.203935864 2.572e-5 17.823665061 0.762353868 2.199132836 4.965200905
172 170 16 15 1399.0 14208.0 0.09846565315315316 0.200164969 2.4631e-5 17.792385586 0.76804392 2.174965407 4.972074439
173 171 14 13 1399.0 14112.0 0.09913548752834467 0.204567903 2.5071e-5 17.806154396 0.759505453 2.2340466 4.972671228
174 172 12 11 1399.0 14016.0 0.09981449771689498 0.201861418 2.5971e-5 18.529840195 0.789347616 2.23167521 4.947890089
175 173 10 9 1399.0 13920.0 0.1005028735632184 0.202902727 2.4951e-5 17.865867105 0.761004999 2.194876208 4.93177029
176 174 8 7 1399.0 13824.0 0.10120081018518519 0.198079003 2.4651e-5 17.791197743 0.767399089 2.226370372 4.951979965

View File

@ -0,0 +1,82 @@
operations,graph_nodes,graph_edges,graph_ce,graph_dt,graph_ci,gen_func_t,cpu_compile_t,cpu_st_t,cpu_mt_t,gpu_compile_t,gpu_t
0,356,493,1399.0,30528.0,0.0458267819706499,0.084389903,2.4971e-5,17.802549835,0.960409581,2.406448706,4.927079076
1,351,483,1369.0,30528.0,0.044844077568134175,0.126855933,2.9211e-5,16.868735557,0.927387188,2.257632484,4.697683068
2,346,478,1369.0,30048.0,0.04556043663471779,0.08319682,3.5431e-5,16.871399152,0.834869326,2.264361993,4.701280771
3,341,473,1314.0,30048.0,0.04373003194888179,0.124422234,2.392e-5,16.454231193,0.856669072,2.271991539,4.68580348
4,336,463,1284.0,30048.0,0.042731629392971246,0.121696991,2.2921e-5,15.881542683,0.816430136,2.213686135,4.449106524
5,331,458,1284.0,29568.0,0.04342532467532467,0.124024888,2.314e-5,15.879200155,0.799333453,2.194093083,4.435654931
6,326,448,1254.0,29568.0,0.04241071428571429,0.121610951,2.2e-5,15.325702423,0.833341953,2.203843882,4.199677306
7,321,438,1224.0,29568.0,0.041396103896103896,0.118972208,2.1631e-5,14.367273685,0.711553932,2.16189756,3.948872646
8,316,433,1224.0,29088.0,0.04207920792079208,0.074826839,2.2031e-5,14.367107152,0.792981221,2.169096496,3.961630969
9,311,428,1169.0,29088.0,0.04018839383938394,0.116237162,2.15e-5,14.416973472,0.788583102,2.092186151,3.946339564
10,306,418,1139.0,29088.0,0.03915704070407041,0.114647398,2.031e-5,13.671420757,0.745657392,2.037551329,3.657411205
11,301,408,1109.0,29088.0,0.03812568756875687,0.11434652,1.951e-5,13.093103664,0.686554396,2.065489584,3.441139671
12,296,403,1109.0,28608.0,0.03876538031319911,0.112282663,1.8991e-5,13.11525848,0.705183633,2.0639299,3.422598036
13,291,398,1109.0,28128.0,0.039426905574516495,0.111549203,1.9661e-5,13.08100601,0.700772882,2.065935946,3.41679234
14,286,388,1079.0,28128.0,0.0383603526734926,0.109881396,1.907e-5,11.871746271,0.665244638,2.063828106,3.187580585
15,281,378,1049.0,28128.0,0.037293799772468716,0.108444747,1.7961e-5,10.963517612,0.62180291,2.037926216,2.935137574
16,276,373,1049.0,27648.0,0.03794126157407408,0.107959773,1.874e-5,11.021594456,0.541779823,2.003876106,2.931304737
17,271,368,1049.0,27168.0,0.03861160188457008,0.105629068,1.8241e-5,11.017450178,0.581974375,2.017201027,2.952118903
18,266,363,1049.0,26688.0,0.0393060551558753,0.107303406,1.8301e-5,11.028597789,0.556078309,2.037535226,2.911405619
19,261,358,994.0,26688.0,0.03724520383693045,0.106584986,1.7111e-5,10.789192026,0.525275525,2.011931363,2.931360979
20,256,353,939.0,26688.0,0.035184352517985615,0.105743463,1.7521e-5,10.50283261,0.535253087,1.962456949,2.941274646
21,255,351,933.0,26688.0,0.03495953237410072,0.105189187,1.7471e-5,10.739591259,0.555102576,2.013201521,2.896175037
22,254,350,933.0,26592.0,0.035085740072202165,0.105895137,1.6631e-5,10.68514711,0.571809578,1.974934611,2.890503396
23,253,348,927.0,26592.0,0.0348601083032491,0.104181459,1.817e-5,10.344271645,0.572483889,2.002875753,2.842241926
24,252,347,927.0,26496.0,0.034986413043478264,0.103568232,1.7471e-5,10.363216025,0.602207417,1.943794016,2.811132729
25,247,342,927.0,26016.0,0.035631918819188195,0.102006829,1.669e-5,10.360319761,0.588967585,1.942523675,2.838431844
26,246,340,921.0,26016.0,0.03540129151291513,0.103244544,1.672e-5,10.140255758,0.565172778,1.980058606,2.776594151
27,245,339,921.0,25920.0,0.03553240740740741,0.102991317,1.723e-5,10.166352736,0.588556746,2.025713505,2.754827976
28,244,337,915.0,25920.0,0.03530092592592592,0.102527335,1.6261e-5,9.965044496,0.527648944,1.966870364,2.708992883
29,243,335,909.0,25920.0,0.035069444444444445,0.101020632,1.6541e-5,9.899918186,0.530837495,1.99964346,2.686936268
30,242,334,909.0,25824.0,0.03519981412639405,0.099846559,1.614e-5,9.924451078,0.532149983,1.992832633,2.667590089
31,241,333,909.0,25728.0,0.035331156716417914,0.103293156,1.634e-5,9.893503718,0.500188044,1.971455575,2.661440862
32,236,328,909.0,25248.0,0.036002851711026615,0.110948742,1.5851e-5,9.916889596,0.515528547,2.014256204,2.691654688
33,235,326,903.0,25248.0,0.03576520912547528,0.099799239,1.658e-5,9.667648582,0.561210643,1.981308261,2.647665444
34,234,324,897.0,25248.0,0.035527566539923956,0.099455409,1.6561e-5,9.588166052,0.544847505,1.932560182,2.56349283
35,233,323,897.0,25152.0,0.035663167938931296,0.103335368,1.6271e-5,9.590387462,0.542413718,1.965145602,2.559435691
36,232,321,891.0,25152.0,0.03542461832061069,0.097770562,1.6571e-5,9.362808632,0.543288523,2.017894491,2.498672404
37,231,320,891.0,25056.0,0.03556034482758621,0.100428616,1.5941e-5,9.340302395,0.548822639,1.994799194,2.525394
38,230,319,891.0,24960.0,0.03569711538461538,0.056667955,1.5341e-5,9.356871677,0.537041949,1.921246656,2.507595034
39,225,314,891.0,24480.0,0.036397058823529414,0.099323026,1.636e-5,9.383625024,0.506403697,1.972101141,2.529248938
40,220,309,836.0,24480.0,0.03415032679738562,0.096789665,1.645e-5,9.524601658,0.473707387,1.980933173,2.524768525
41,215,304,836.0,24000.0,0.034833333333333334,0.053463925,1.671e-5,9.520567128,0.487585179,1.942542795,2.535491481
42,214,302,830.0,24000.0,0.034583333333333334,0.096303802,1.6011e-5,9.137262758,0.4297148,1.950560163,2.478408276
43,213,301,830.0,23904.0,0.034722222222222224,0.070596338,1.6901e-5,9.143790565,0.492842898,1.949332161,2.476752284
44,212,299,824.0,23904.0,0.034471218206157964,0.09696925,1.612e-5,9.089211511,0.456930617,2.022026121,2.419473874
45,211,297,818.0,23904.0,0.03422021419009371,0.052526649,1.536e-5,8.807671694,0.471203239,1.970488502,2.372441242
46,210,296,818.0,23808.0,0.03435819892473118,0.096716114,1.5701e-5,8.806210783,0.451452844,1.960073481,2.387451098
47,209,295,818.0,23712.0,0.034497300944669365,0.05145174,1.6061e-5,8.867215342,0.450895098,1.968012818,2.394204111
48,204,290,818.0,23232.0,0.03521005509641873,0.093248236,1.9521e-5,8.844517253,0.476030278,1.963827031,2.389413849
49,203,288,812.0,23232.0,0.034951790633608815,0.093881584,1.527e-5,8.849095772,0.446415074,1.974782212,2.332439097
50,202,287,812.0,23136.0,0.03509681881051176,0.050473481,1.5851e-5,8.784636116,0.469233287,1.953068913,2.321316886
51,201,285,806.0,23136.0,0.034837482710926695,0.092750242,1.5541e-5,8.632088328,0.491467054,1.945455141,2.29300329
52,200,284,806.0,23040.0,0.03498263888888889,0.092540087,1.7161e-5,8.637677414,0.471865872,1.975464118,2.259260411
53,199,282,800.0,23040.0,0.034722222222222224,0.092944049,1.5261e-5,8.624992966,0.478249573,1.931707577,2.232058939
54,198,281,800.0,22944.0,0.03486750348675035,0.091660013,1.575e-5,8.680034605,0.429976994,2.022314921,2.224544849
55,197,279,794.0,22944.0,0.03460599721059972,0.092591389,1.582e-5,8.266084761,0.442472956,1.949268775,2.165130527
56,196,278,794.0,22848.0,0.03475140056022409,0.090376966,1.529e-5,8.26930839,0.438461132,1.960119483,2.169387658
57,191,273,739.0,22848.0,0.03234418767507003,0.090398736,1.589e-5,8.061516101,0.468233752,1.825342557,2.144808638
58,186,268,739.0,22368.0,0.03303826895565093,0.090566151,1.5781e-5,8.051685873,0.472555774,1.827021946,2.175475243
59,185,266,733.0,22368.0,0.03277002861230329,0.046301524,1.4931e-5,7.809555195,0.466519375,1.819191936,2.095906173
60,184,264,727.0,22368.0,0.03250178826895565,0.087977349,1.4771e-5,7.825535183,0.452072238,1.820734702,2.06485156
61,183,263,727.0,22272.0,0.032641882183908046,0.08908488,1.4591e-5,7.77560322,0.445728609,1.804235078,2.06763398
62,182,262,727.0,22176.0,0.03278318903318903,0.076517376,1.461e-5,7.754359737,0.421063625,1.812681957,2.076417548
63,181,260,721.0,22176.0,0.032512626262626264,0.088983767,1.4091e-5,7.616158878,0.422402602,1.868182992,2.016601005
64,180,259,721.0,22080.0,0.03265398550724638,0.089172453,1.467e-5,7.63910266,0.402654247,1.844390793,2.031385412
65,175,254,666.0,22080.0,0.03016304347826087,0.091971222,1.3851e-5,7.35822511,0.443635961,1.719023302,2.007792679
66,170,249,666.0,21600.0,0.030833333333333334,0.073480651,1.3871e-5,7.291999508,0.434965958,1.750073777,1.999358953
67,169,247,660.0,21600.0,0.030555555555555555,0.085309774,1.7211e-5,7.245192983,0.412650069,1.744681817,1.962798523
68,168,245,654.0,21600.0,0.03027777777777778,0.089043539,1.367e-5,7.024436477,0.421292773,1.722710908,1.890918459
69,167,243,648.0,21600.0,0.03,0.084353527,1.428e-5,6.8832018,0.415786727,1.715216258,1.830282141
70,166,242,648.0,21504.0,0.030133928571428572,0.084367977,1.3441e-5,6.899982477,0.419080281,1.707637056,1.843529005
71,165,241,648.0,21408.0,0.030269058295964126,0.085701815,1.4031e-5,6.936174291,0.377346024,1.704252961,1.85218872
72,164,240,648.0,21312.0,0.030405405405405407,0.083910355,1.3601e-5,6.9051589,0.389477478,1.75740328,1.867258596
73,159,235,593.0,21312.0,0.0278246996996997,0.082135195,1.3351e-5,7.031037571,0.356084586,1.631072,1.797434919
74,154,230,593.0,20832.0,0.028465821812596007,0.080356395,1.358e-5,7.040766129,0.405151789,1.620631997,1.781269114
75,153,228,587.0,20832.0,0.02817780337941628,0.066967517,1.3391e-5,6.644186555,0.395240289,1.641155866,1.743666486
76,152,226,581.0,20832.0,0.02788978494623656,0.080763676,1.298e-5,6.633937959,0.388869331,1.630064054,1.701302723
77,151,225,581.0,20736.0,0.028018904320987654,0.080671833,1.2781e-5,6.622133299,0.392564435,1.625932508,1.711411428
78,150,224,581.0,20640.0,0.02814922480620155,0.080368195,1.358e-5,6.599986437,0.397419271,1.657700695,1.694756709
79,149,222,575.0,20640.0,0.027858527131782947,0.080015475,1.298e-5,6.281191715,0.37819019,1.622522233,1.656839741
80,148,221,575.0,20544.0,0.027988707165109036,0.065331671,1.334e-5,6.313635402,0.380955078,1.627111603,1.638795233
1 operations graph_nodes graph_edges graph_ce graph_dt graph_ci gen_func_t cpu_compile_t cpu_st_t cpu_mt_t gpu_compile_t gpu_t
2 0 356 493 1399.0 30528.0 0.0458267819706499 0.084389903 2.4971e-5 17.802549835 0.960409581 2.406448706 4.927079076
3 1 351 483 1369.0 30528.0 0.044844077568134175 0.126855933 2.9211e-5 16.868735557 0.927387188 2.257632484 4.697683068
4 2 346 478 1369.0 30048.0 0.04556043663471779 0.08319682 3.5431e-5 16.871399152 0.834869326 2.264361993 4.701280771
5 3 341 473 1314.0 30048.0 0.04373003194888179 0.124422234 2.392e-5 16.454231193 0.856669072 2.271991539 4.68580348
6 4 336 463 1284.0 30048.0 0.042731629392971246 0.121696991 2.2921e-5 15.881542683 0.816430136 2.213686135 4.449106524
7 5 331 458 1284.0 29568.0 0.04342532467532467 0.124024888 2.314e-5 15.879200155 0.799333453 2.194093083 4.435654931
8 6 326 448 1254.0 29568.0 0.04241071428571429 0.121610951 2.2e-5 15.325702423 0.833341953 2.203843882 4.199677306
9 7 321 438 1224.0 29568.0 0.041396103896103896 0.118972208 2.1631e-5 14.367273685 0.711553932 2.16189756 3.948872646
10 8 316 433 1224.0 29088.0 0.04207920792079208 0.074826839 2.2031e-5 14.367107152 0.792981221 2.169096496 3.961630969
11 9 311 428 1169.0 29088.0 0.04018839383938394 0.116237162 2.15e-5 14.416973472 0.788583102 2.092186151 3.946339564
12 10 306 418 1139.0 29088.0 0.03915704070407041 0.114647398 2.031e-5 13.671420757 0.745657392 2.037551329 3.657411205
13 11 301 408 1109.0 29088.0 0.03812568756875687 0.11434652 1.951e-5 13.093103664 0.686554396 2.065489584 3.441139671
14 12 296 403 1109.0 28608.0 0.03876538031319911 0.112282663 1.8991e-5 13.11525848 0.705183633 2.0639299 3.422598036
15 13 291 398 1109.0 28128.0 0.039426905574516495 0.111549203 1.9661e-5 13.08100601 0.700772882 2.065935946 3.41679234
16 14 286 388 1079.0 28128.0 0.0383603526734926 0.109881396 1.907e-5 11.871746271 0.665244638 2.063828106 3.187580585
17 15 281 378 1049.0 28128.0 0.037293799772468716 0.108444747 1.7961e-5 10.963517612 0.62180291 2.037926216 2.935137574
18 16 276 373 1049.0 27648.0 0.03794126157407408 0.107959773 1.874e-5 11.021594456 0.541779823 2.003876106 2.931304737
19 17 271 368 1049.0 27168.0 0.03861160188457008 0.105629068 1.8241e-5 11.017450178 0.581974375 2.017201027 2.952118903
20 18 266 363 1049.0 26688.0 0.0393060551558753 0.107303406 1.8301e-5 11.028597789 0.556078309 2.037535226 2.911405619
21 19 261 358 994.0 26688.0 0.03724520383693045 0.106584986 1.7111e-5 10.789192026 0.525275525 2.011931363 2.931360979
22 20 256 353 939.0 26688.0 0.035184352517985615 0.105743463 1.7521e-5 10.50283261 0.535253087 1.962456949 2.941274646
23 21 255 351 933.0 26688.0 0.03495953237410072 0.105189187 1.7471e-5 10.739591259 0.555102576 2.013201521 2.896175037
24 22 254 350 933.0 26592.0 0.035085740072202165 0.105895137 1.6631e-5 10.68514711 0.571809578 1.974934611 2.890503396
25 23 253 348 927.0 26592.0 0.0348601083032491 0.104181459 1.817e-5 10.344271645 0.572483889 2.002875753 2.842241926
26 24 252 347 927.0 26496.0 0.034986413043478264 0.103568232 1.7471e-5 10.363216025 0.602207417 1.943794016 2.811132729
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View File

@ -0,0 +1,79 @@
operations,graph_nodes,graph_edges,graph_ce,graph_dt,graph_ci,gen_func_t,cpu_compile_t,cpu_st_t,cpu_mt_t,gpu_compile_t,gpu_t
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10,14676,19713,60656.0,1.279776e6,0.0473957942639962,5.993535435,0.000745961,7.192805963,0.417393835,0.0,0.0
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30,13352,17940,53276.0,1.236672e6,0.04308013765978368,5.169906767,0.000675318,6.370526843,0.313517861,0.0,0.0
40,12714,17168,51163.0,1.199712e6,0.042646068389746876,4.845906388,0.000634457,6.124306725,0.311820244,0.0,0.0
50,12004,16270,48473.0,1.163232e6,0.04167096503534978,4.433653313,0.000596017,5.760561483,0.320897852,0.0,0.0
60,11750,15983,48022.0,1.144224e6,0.04196905501020779,4.316924709,0.000596237,5.738809149,0.283214404,0.0,0.0
70,11538,15697,47325.0,1.133184e6,0.04176285581158929,4.201152631,0.000554855,5.438337093,0.313985744,0.0,0.0
80,11434,15550,46814.0,1.129536e6,0.04144533684628024,4.216359254,0.000553545,5.429706297,0.268223845,0.0,0.0
90,11066,15085,46232.0,1.10352e6,0.041895026823256486,3.924567625,0.000560535,5.412444055,0.274917428,0.0,0.0
100,10848,14847,44297.0,1.100352e6,0.04025711772232885,3.848048388,0.000527955,5.127227854,0.294706757,0.0,0.0
110,10462,14382,42261.0,1.084512e6,0.038967756926617685,3.674674179,0.000509054,4.922064369,0.276530272,0.0,0.0
120,10304,14191,41810.0,1.07472e6,0.038903156170909635,3.58233155,0.000516074,5.02371138,0.266906519,0.0,0.0
130,10200,14067,41437.0,1.068864e6,0.03876732680677804,3.529160319,0.000501634,4.863804478,0.24639169,0.0,0.0
140,10042,13871,40956.0,1.059552e6,0.03865407266467337,3.346890818,0.000488403,4.753116119,0.254509861,0.0,0.0
150,9956,13765,40583.0,1.055424e6,0.038451844945727974,3.41847396,0.000500654,4.756966153,0.255966291,0.0,0.0
160,9906,13690,40433.0,1.053024e6,0.03839703558513386,3.405093274,0.000496774,4.812050085,0.24421971,0.0,0.0
170,9838,13597,40283.0,1.048896e6,0.038405142168527674,3.348340057,0.000481363,4.669473296,0.234701411,0.0,0.0
180,9242,12790,37708.0,1.02336e6,0.03684724828017511,3.063089187,0.000449352,4.335668832,0.228471471,0.0,0.0
190,9120,12648,37082.0,1.017984e6,0.03642689865459575,2.994073054,0.000429002,4.181894908,0.224361729,0.0,0.0
200,9052,12555,36932.0,1.013856e6,0.03642726383233911,3.046147594,0.000427282,4.151250123,0.212513705,0.0,0.0
210,8912,12405,36366.0,1.005792e6,0.03615658108237091,2.937579863,0.000433982,4.261727394,0.214012817,0.0,0.0
220,8808,12281,35993.0,999936.0,0.035995303699436765,2.892146284,0.000432382,4.198423468,0.219749812,0.0,0.0
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270,7838,11100,32153.0,949536.0,0.0338618019748593,2.456319106,0.000383211,3.635092003,0.187908484,0.0,0.0
280,7716,10940,31672.0,943680.0,0.033562224482875554,2.402192681,0.00037687,3.594882506,0.194062713,0.0,0.0
290,7576,10772,30745.0,939552.0,0.032723042471305475,2.338714319,0.00037334,3.556085038,0.194369971,0.0,0.0
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420,6014,8740,25901.0,852384.0,0.030386539400082593,1.774576254,0.000288998,2.694176581,0.173939173,0.0,0.0
430,5928,8629,25498.0,848736.0,0.030042321758473777,1.7065974,0.000284277,2.675798329,0.170062674,0.0,0.0
440,5842,8523,25125.0,844608.0,0.029747527847238008,1.685087395,0.000287118,2.688215586,0.166480549,0.0,0.0
450,5738,8399,24752.0,838752.0,0.02951051085422151,1.673553823,0.000274969,2.523253333,0.167824913,0.0,0.0
460,5670,8316,24662.0,833664.0,0.02958266159987717,1.625105871,0.000272178,2.52817126,0.164730041,0.0,0.0
470,5548,8161,24211.0,827328.0,0.029264088729016785,1.583826656,0.000262318,2.419247276,0.160768733,0.0,0.0
480,5426,8006,23760.0,820992.0,0.028940598690364826,1.58433006,0.000264708,2.454129792,0.155746163,0.0,0.0
490,5358,7918,23640.0,816384.0,0.028956961429915332,1.520887155,0.000253268,2.329551174,0.153813499,0.0,0.0
500,5272,7807,23237.0,812736.0,0.02859108000629971,1.488167166,0.000248837,2.282665244,0.154234105,0.0,0.0
510,5150,7647,22756.0,806880.0,0.028202458853856832,1.448681065,0.000247727,2.275316917,0.149501885,0.0,0.0
520,5028,7487,22022.0,803232.0,0.02741673638500458,1.43939862,0.000236057,2.14942739,0.146771977,0.0,0.0
530,4906,7350,21679.0,795168.0,0.02726342106322186,1.367826149,0.000242258,2.188588822,0.148076932,0.0,0.0
540,4838,7257,21529.0,791040.0,0.027216069983818772,1.341798982,0.000230357,2.096237881,0.141709174,0.0,0.0
550,4752,7151,21156.0,786912.0,0.02688483591557887,1.339939443,0.000227267,2.062687036,0.13782156,0.0,0.0
560,4684,7068,21066.0,781824.0,0.026944683202357565,1.327848904,0.000222317,2.00294804,0.139508498,0.0,0.0
570,4634,6993,20916.0,779424.0,0.02683520137948023,1.276183945,0.000224717,2.021180753,0.13573571,0.0,0.0
580,4548,6882,20766.0,773568.0,0.026844440307768676,1.235522514,0.000212457,1.917354147,0.128401984,0.0,0.0
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610,4326,6582,20045.0,761952.0,0.026307431439250767,1.18887911,0.000203196,1.819359467,0.129183977,0.0,0.0
620,4204,6422,19564.0,756096.0,0.02587502116133401,1.172245936,0.000212366,1.757557943,0.125887084,0.0,0.0
630,3836,5980,17558.0,741504.0,0.02367890126014155,1.043747354,0.000175996,1.554965777,0.115650062,0.0,0.0
640,3732,5856,17438.0,733440.0,0.023775632635253053,1.010298683,0.000174715,1.562411059,0.113877446,0.0,0.0
650,3628,5714,16957.0,729312.0,0.023250680093019175,0.985957627,0.000170445,1.474744854,0.110990727,0.0,0.0
660,3506,5549,16446.0,723936.0,0.022717477788091765,0.948042334,0.000161975,1.420057878,0.106426767,0.0,0.0
670,3420,5448,16103.0,719328.0,0.0223861715378798,0.921840457,0.000156765,1.356400004,0.10491163,0.0,0.0
680,3316,5319,15700.0,713952.0,0.021990273855945496,0.892707383,0.000162605,1.335548894,0.100909488,0.0,0.0
690,3212,5200,15357.0,707616.0,0.02170244878578212,0.89578919,0.000149085,1.299462304,0.099173414,0.0,0.0
700,2916,4871,13850.0,693792.0,0.019962755407960886,0.781393124,0.000134984,1.179737113,0.096642976,0.0,0.0
710,2722,4598,13123.0,684960.0,0.019158782994627425,0.725161332,0.000122213,1.056813282,0.08619269,0.0,0.0
720,2636,4492,12750.0,680832.0,0.018727086858432038,0.701632434,0.000128984,1.019551067,0.085388434,0.0,0.0
730,2532,4373,12407.0,674496.0,0.018394475282284845,0.675037355,0.000119134,0.993660466,0.082709493,0.0,0.0
740,2428,4231,11926.0,670368.0,0.017790228650532244,0.6435086,0.000109403,0.927737064,0.078423743,0.0,0.0
750,2342,4125,11553.0,666240.0,0.017340597982708934,0.619218823,0.000106693,0.883708241,0.075467284,0.0,0.0
760,2274,4032,11403.0,662112.0,0.017222161809482384,0.635081649,0.000103493,0.919860114,0.074058132,0.0,0.0
770,2234,3977,11313.0,659712.0,0.017148392025611175,0.593953439,0.000110543,0.84404911,0.077019298,0.0,0.0
1 operations graph_nodes graph_edges graph_ce graph_dt graph_ci gen_func_t cpu_compile_t cpu_st_t cpu_mt_t gpu_compile_t gpu_t
2 0 15866 21617 66249.0 1.314048e6 0.050415966540035065 6.468999136 0.001398329 8.478099553 0.43958521 0.0 0.0
3 10 14676 19713 60656.0 1.279776e6 0.0473957942639962 5.993535435 0.000745961 7.192805963 0.417393835 0.0 0.0
4 20 13774 18527 56334.0 1.243296e6 0.04531020770596865 5.489738392 0.000682889 6.652182167 0.336339503 0.0 0.0
5 30 13352 17940 53276.0 1.236672e6 0.04308013765978368 5.169906767 0.000675318 6.370526843 0.313517861 0.0 0.0
6 40 12714 17168 51163.0 1.199712e6 0.042646068389746876 4.845906388 0.000634457 6.124306725 0.311820244 0.0 0.0
7 50 12004 16270 48473.0 1.163232e6 0.04167096503534978 4.433653313 0.000596017 5.760561483 0.320897852 0.0 0.0
8 60 11750 15983 48022.0 1.144224e6 0.04196905501020779 4.316924709 0.000596237 5.738809149 0.283214404 0.0 0.0
9 70 11538 15697 47325.0 1.133184e6 0.04176285581158929 4.201152631 0.000554855 5.438337093 0.313985744 0.0 0.0
10 80 11434 15550 46814.0 1.129536e6 0.04144533684628024 4.216359254 0.000553545 5.429706297 0.268223845 0.0 0.0
11 90 11066 15085 46232.0 1.10352e6 0.041895026823256486 3.924567625 0.000560535 5.412444055 0.274917428 0.0 0.0
12 100 10848 14847 44297.0 1.100352e6 0.04025711772232885 3.848048388 0.000527955 5.127227854 0.294706757 0.0 0.0
13 110 10462 14382 42261.0 1.084512e6 0.038967756926617685 3.674674179 0.000509054 4.922064369 0.276530272 0.0 0.0
14 120 10304 14191 41810.0 1.07472e6 0.038903156170909635 3.58233155 0.000516074 5.02371138 0.266906519 0.0 0.0
15 130 10200 14067 41437.0 1.068864e6 0.03876732680677804 3.529160319 0.000501634 4.863804478 0.24639169 0.0 0.0
16 140 10042 13871 40956.0 1.059552e6 0.03865407266467337 3.346890818 0.000488403 4.753116119 0.254509861 0.0 0.0
17 150 9956 13765 40583.0 1.055424e6 0.038451844945727974 3.41847396 0.000500654 4.756966153 0.255966291 0.0 0.0
18 160 9906 13690 40433.0 1.053024e6 0.03839703558513386 3.405093274 0.000496774 4.812050085 0.24421971 0.0 0.0
19 170 9838 13597 40283.0 1.048896e6 0.038405142168527674 3.348340057 0.000481363 4.669473296 0.234701411 0.0 0.0
20 180 9242 12790 37708.0 1.02336e6 0.03684724828017511 3.063089187 0.000449352 4.335668832 0.228471471 0.0 0.0
21 190 9120 12648 37082.0 1.017984e6 0.03642689865459575 2.994073054 0.000429002 4.181894908 0.224361729 0.0 0.0
22 200 9052 12555 36932.0 1.013856e6 0.03642726383233911 3.046147594 0.000427282 4.151250123 0.212513705 0.0 0.0
23 210 8912 12405 36366.0 1.005792e6 0.03615658108237091 2.937579863 0.000433982 4.261727394 0.214012817 0.0 0.0
24 220 8808 12281 35993.0 999936.0 0.035995303699436765 2.892146284 0.000432382 4.198423468 0.219749812 0.0 0.0
25 230 8626 12061 35765.0 986112.0 0.03626869970145379 2.752333211 0.000414672 4.035044142 0.241721263 0.0 0.0
26 240 8426 11841 34336.0 980256.0 0.03502758463095355 2.714773746 0.000414522 4.036870861 0.235365769 0.0 0.0
27 250 8118 11464 33416.0 961728.0 0.03474579090969588 2.579966689 0.000402461 3.870568035 0.20937257 0.0 0.0
28 260 7942 11242 32634.0 953664.0 0.034219599355747934 2.520293442 0.000391581 3.72881432 0.191238985 0.0 0.0
29 270 7838 11100 32153.0 949536.0 0.0338618019748593 2.456319106 0.000383211 3.635092003 0.187908484 0.0 0.0
30 280 7716 10940 31672.0 943680.0 0.033562224482875554 2.402192681 0.00037687 3.594882506 0.194062713 0.0 0.0
31 290 7576 10772 30745.0 939552.0 0.032723042471305475 2.338714319 0.00037334 3.556085038 0.194369971 0.0 0.0
32 300 7376 10529 30487.0 924480.0 0.0329774575977847 2.279512925 0.00036552 3.504723807 0.191079171 0.0 0.0
33 310 7218 10310 29868.0 917376.0 0.03255807869401423 2.207692656 0.000355539 3.30937664 0.181261073 0.0 0.0
34 320 7078 10137 29417.0 909312.0 0.03235083227759009 2.147511905 0.000352659 3.30461376 0.18005858 0.0 0.0
35 330 6860 9848 28991.0 895200.0 0.032384941912421805 2.078259266 0.00033941 3.211808988 0.172834084 0.0 0.0
36 340 6702 9611 28264.0 889824.0 0.03176358470888625 2.069880378 0.000318959 3.033092324 0.154811992 0.0 0.0
37 350 6616 9505 27891.0 885696.0 0.03149048883589855 2.005510172 0.000326369 3.008426711 0.173417779 0.0 0.0
38 360 6512 9391 27325.0 881088.0 0.03101279327377061 1.968347618 0.000315789 2.921325386 0.168873786 0.0 0.0
39 370 6426 9280 27175.0 875232.0 0.03104891046031224 1.92734893 0.000315548 2.990437001 0.181187901 0.0 0.0
40 380 6358 9187 27025.0 871104.0 0.031023850194695467 1.889258172 0.000308689 2.846738111 0.181651873 0.0 0.0
41 390 6272 9081 26652.0 866976.0 0.030741335400287898 1.840892272 0.000329279 2.825270586 0.177422669 0.0 0.0
42 400 6204 8993 26532.0 862368.0 0.03076644773460982 1.820608708 0.000296329 2.759355249 0.175583708 0.0 0.0
43 410 6118 8864 26274.0 858240.0 0.030613814317673377 1.783961229 0.000290708 2.707626007 0.172954176 0.0 0.0
44 420 6014 8740 25901.0 852384.0 0.030386539400082593 1.774576254 0.000288998 2.694176581 0.173939173 0.0 0.0
45 430 5928 8629 25498.0 848736.0 0.030042321758473777 1.7065974 0.000284277 2.675798329 0.170062674 0.0 0.0
46 440 5842 8523 25125.0 844608.0 0.029747527847238008 1.685087395 0.000287118 2.688215586 0.166480549 0.0 0.0
47 450 5738 8399 24752.0 838752.0 0.02951051085422151 1.673553823 0.000274969 2.523253333 0.167824913 0.0 0.0
48 460 5670 8316 24662.0 833664.0 0.02958266159987717 1.625105871 0.000272178 2.52817126 0.164730041 0.0 0.0
49 470 5548 8161 24211.0 827328.0 0.029264088729016785 1.583826656 0.000262318 2.419247276 0.160768733 0.0 0.0
50 480 5426 8006 23760.0 820992.0 0.028940598690364826 1.58433006 0.000264708 2.454129792 0.155746163 0.0 0.0
51 490 5358 7918 23640.0 816384.0 0.028956961429915332 1.520887155 0.000253268 2.329551174 0.153813499 0.0 0.0
52 500 5272 7807 23237.0 812736.0 0.02859108000629971 1.488167166 0.000248837 2.282665244 0.154234105 0.0 0.0
53 510 5150 7647 22756.0 806880.0 0.028202458853856832 1.448681065 0.000247727 2.275316917 0.149501885 0.0 0.0
54 520 5028 7487 22022.0 803232.0 0.02741673638500458 1.43939862 0.000236057 2.14942739 0.146771977 0.0 0.0
55 530 4906 7350 21679.0 795168.0 0.02726342106322186 1.367826149 0.000242258 2.188588822 0.148076932 0.0 0.0
56 540 4838 7257 21529.0 791040.0 0.027216069983818772 1.341798982 0.000230357 2.096237881 0.141709174 0.0 0.0
57 550 4752 7151 21156.0 786912.0 0.02688483591557887 1.339939443 0.000227267 2.062687036 0.13782156 0.0 0.0
58 560 4684 7068 21066.0 781824.0 0.026944683202357565 1.327848904 0.000222317 2.00294804 0.139508498 0.0 0.0
59 570 4634 6993 20916.0 779424.0 0.02683520137948023 1.276183945 0.000224717 2.021180753 0.13573571 0.0 0.0
60 580 4548 6882 20766.0 773568.0 0.026844440307768676 1.235522514 0.000212457 1.917354147 0.128401984 0.0 0.0
61 590 4498 6807 20616.0 771168.0 0.026733474418025645 1.267249751 0.000212506 1.899792552 0.133449083 0.0 0.0
62 600 4376 6657 20195.0 764352.0 0.0264210730134807 1.209891149 0.000205326 1.850663451 0.129490109 0.0 0.0
63 610 4326 6582 20045.0 761952.0 0.026307431439250767 1.18887911 0.000203196 1.819359467 0.129183977 0.0 0.0
64 620 4204 6422 19564.0 756096.0 0.02587502116133401 1.172245936 0.000212366 1.757557943 0.125887084 0.0 0.0
65 630 3836 5980 17558.0 741504.0 0.02367890126014155 1.043747354 0.000175996 1.554965777 0.115650062 0.0 0.0
66 640 3732 5856 17438.0 733440.0 0.023775632635253053 1.010298683 0.000174715 1.562411059 0.113877446 0.0 0.0
67 650 3628 5714 16957.0 729312.0 0.023250680093019175 0.985957627 0.000170445 1.474744854 0.110990727 0.0 0.0
68 660 3506 5549 16446.0 723936.0 0.022717477788091765 0.948042334 0.000161975 1.420057878 0.106426767 0.0 0.0
69 670 3420 5448 16103.0 719328.0 0.0223861715378798 0.921840457 0.000156765 1.356400004 0.10491163 0.0 0.0
70 680 3316 5319 15700.0 713952.0 0.021990273855945496 0.892707383 0.000162605 1.335548894 0.100909488 0.0 0.0
71 690 3212 5200 15357.0 707616.0 0.02170244878578212 0.89578919 0.000149085 1.299462304 0.099173414 0.0 0.0
72 700 2916 4871 13850.0 693792.0 0.019962755407960886 0.781393124 0.000134984 1.179737113 0.096642976 0.0 0.0
73 710 2722 4598 13123.0 684960.0 0.019158782994627425 0.725161332 0.000122213 1.056813282 0.08619269 0.0 0.0
74 720 2636 4492 12750.0 680832.0 0.018727086858432038 0.701632434 0.000128984 1.019551067 0.085388434 0.0 0.0
75 730 2532 4373 12407.0 674496.0 0.018394475282284845 0.675037355 0.000119134 0.993660466 0.082709493 0.0 0.0
76 740 2428 4231 11926.0 670368.0 0.017790228650532244 0.6435086 0.000109403 0.927737064 0.078423743 0.0 0.0
77 750 2342 4125 11553.0 666240.0 0.017340597982708934 0.619218823 0.000106693 0.883708241 0.075467284 0.0 0.0
78 760 2274 4032 11403.0 662112.0 0.017222161809482384 0.635081649 0.000103493 0.919860114 0.074058132 0.0 0.0
79 770 2234 3977 11313.0 659712.0 0.017148392025611175 0.593953439 0.000110543 0.84404911 0.077019298 0.0 0.0

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@ -1,3 +1,9 @@
[deps]
BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
MetagraphOptimization = "3e869610-d48d-4942-ba70-c1b702a33ca4"
Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
QEDprocesses = "46de9c38-1bb3-4547-a1ec-da24d767fdad"
StatsPlots = "f3b207a7-027a-5e70-b257-86293d7955fd"

148
examples/qed_bench.jl Normal file
View File

@ -0,0 +1,148 @@
using MetagraphOptimization
using LIKWID
using CUDA
using UUIDs
function cpu_bench(compute_function, inputs)
compute_function.(inputs[begin:10]) # make sure it's compiled
time = @elapsed Threads.@threads for i in eachindex(inputs)
@invokelatest compute_function(inputs[i])
end
rate = length(inputs) / time
return (time, rate)
end
function gpu_bench(compute_function, inputs)
CUDA.@sync compute_function.(inputs[begin:10]) # make sure it's compiled
time = @elapsed CUDA.@sync compute_function.(inputs)
rate = length(inputs) / time
return (time, rate)
end
function bench_process(
process::MetagraphOptimization.AbstractProcessDescription,
func,
io::IO = stdout;
use_likwid = true,
)
println(io, "\n--- Benchmarking $(process) ---")
NFLOPs = GraphProperties(graph).computeEffort
if use_likwid
input = gen_process_input(process)
func(input) # compile first
_, events = @perfmon "FLOPS_DP" func(input)
NFLOPs = first(events["FLOPS_DP"])["RETIRED_SSE_AVX_FLOPS_ALL"]
end
nInputs = 10000000 # ten million
println(io, "Generating $nInputs inputs with $(Threads.nthreads()) threads...")
inputs = Vector{typeof(gen_process_input(process))}()
resize!(inputs, nInputs)
processes = Vector{typeof(process)}()
for i in 1:Threads.nthreads()
push!(processes, copy(process))
end
Threads.@threads for i in eachindex(inputs)
inputs[i] = gen_process_input(processes[Threads.nthreads()])
end
println(io, "Benchmarking CPU with $(Threads.nthreads()) threads...")
(time_cpu, rate_cpu) = cpu_bench(func, inputs)
flops_cpu = (rate_cpu * NFLOPs) / 1024^3
println(io, "Benchmarking GPU...")
cuInputs = CuArray(inputs)
(time_gpu, rate_gpu) = gpu_bench(func, cuInputs)
flops_gpu = (rate_gpu * NFLOPs) / 1024^3
println(io, "\nBenchmark Summary for $(process):")
if use_likwid
println(io, "Measured FLOPS by LIKWID: $NFLOPs")
else
println(io, "Total graph compute effort: $NFLOPs")
end
println(io, "Total input size: $(bytes_to_human_readable(Base.summarysize(inputs)))")
println(io, "CPU, $(Threads.nthreads()) threads")
println(io, " Time: $time_cpu")
println(io, " Rate: $rate_cpu")
println(io, " GFLOPS: $flops_cpu")
println(io, "GPU, $(name(first(CUDA.devices())))")
println(io, " Time: $time_gpu")
println(io, " Rate: $rate_gpu")
return println(io, " GFLOPS: $flops_gpu")
end
# use "mock" machine that only uses cpu
machine = Machine(
[
MetagraphOptimization.NumaNode(
0,
1,
MetagraphOptimization.default_strategy(MetagraphOptimization.NumaNode),
-1.0,
UUIDs.uuid1(),
),
],
[-1.0;;],
)
optimizer = ReductionOptimizer()
# sadly cannot put these in functions because the world age must increase after the function is created which happens only in the global scope
# compton
process = parse_process("ke->ke", QEDModel())
graph = gen_graph(process)
optimize_to_fixpoint!(optimizer, graph)
compute_func = get_compute_function(graph, process, machine)
bench_process(process, compute_func)
# 2-photon compton
process = parse_process("ke->kke", QEDModel())
graph = gen_graph(process)
optimize_to_fixpoint!(optimizer, graph)
compute_func = get_compute_function(graph, process, machine)
bench_process(process, compute_func)
# 3-photon compton
process = parse_process("ke->kkke", QEDModel())
graph = gen_graph(process)
optimize_to_fixpoint!(optimizer, graph)
compute_func = get_compute_function(graph, process, machine)
bench_process(process, compute_func)
# AB->AB
process = parse_process("AB->AB", ABCModel())
graph = parse_dag("input/AB->AB.txt", ABCModel())
optimize_to_fixpoint!(optimizer, graph)
compute_func = get_compute_function(graph, process, machine)
bench_process(process, compute_func)
# AB->AB^3
process = parse_process("AB->ABBB", ABCModel())
graph = parse_dag("input/AB->ABBB.txt", ABCModel())
optimize_to_fixpoint!(optimizer, graph)
compute_func = get_compute_function(graph, process, machine)
bench_process(process, compute_func)
exit(0)
# 4-photon compton
process = parse_process("ke->kkkke", QEDModel())
graph = gen_graph(process)
optimize_to_fixpoint!(optimizer, graph)
compute_func = get_compute_function(graph, process, machine)
bench_process(process, compute_func)
# AB->AB^5
process = parse_process("AB->ABBBBB", ABCModel())
graph = parse_dag("input/AB->ABBBBB.txt", ABCModel())
optimize_to_fixpoint!(optimizer, graph)
compute_func = get_compute_function(graph, process, machine)
bench_process(process, compute_func)

542
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@ -391,7 +391,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Julia 1.9.3",
"display_name": "Julia 1.9.4",
"language": "julia",
"name": "julia-1.9"
},
@ -399,7 +399,7 @@
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
"version": "1.9.3"
"version": "1.9.4"
}
},
"nbformat": 4,

View File

@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 1,
"metadata": {},
"outputs": [
{
@ -31,13 +31,13 @@
"data": {
"text/plain": [
"Graph:\n",
" Nodes: Total: 131069, DataTask: 65539, ComputeTaskQED_Sum: 1, \n",
" ComputeTaskQED_V: 35280, ComputeTaskQED_S2: 5040, ComputeTaskQED_U: 9, \n",
" ComputeTaskQED_S1: 25200\n",
" Edges: 176419\n",
" Total Compute Effort: 549370.0\n",
" Total Data Transfer: 1.0645344e7\n",
" Total Compute Intensity: 0.05160659909158408\n"
" Nodes: Total: 15866, DataTask: 7937, ComputeTaskQED_S2: 720, \n",
" ComputeTaskQED_Sum: 1, ComputeTaskQED_V: 4320, ComputeTaskQED_S1: 2880, \n",
" ComputeTaskQED_U: 8\n",
" Edges: 21617\n",
" Total Compute Effort: 66249.0\n",
" Total Data Transfer: 1.314048e6\n",
" Total Compute Intensity: 0.050415966540035065\n"
]
},
"metadata": {},
@ -47,7 +47,7 @@
"source": [
"machine = get_machine_info()\n",
"model = QEDModel()\n",
"process = parse_process(\"ke->kkkkkke\", model)\n",
"process = parse_process(\"ke->kkkkke\", model)\n",
"\n",
"inputs = [gen_process_input(process) for _ in 1:1e3];\n",
"graph = gen_graph(process)"
@ -62,13 +62,13 @@
"data": {
"text/plain": [
"Graph:\n",
" Nodes: Total: 14783, DataTask: 7396, ComputeTaskQED_Sum: 1, \n",
" ComputeTaskQED_V: 1819, ComputeTaskQED_S2: 5040, ComputeTaskQED_U: 9, \n",
" ComputeTaskQED_S1: 518\n",
" Edges: 26672\n",
" Total Compute Effort: 77102.0\n",
" Total Data Transfer: 5.063616e6\n",
" Total Compute Intensity: 0.015226668056977465\n"
" Nodes: Total: 2234, DataTask: 1121, ComputeTaskQED_S2: 720, \n",
" ComputeTaskQED_Sum: 1, ComputeTaskQED_V: 312, ComputeTaskQED_S1: 72, \n",
" ComputeTaskQED_U: 8\n",
" Edges: 3977\n",
" Total Compute Effort: 11313.0\n",
" Total Data Transfer: 659712.0\n",
" Total Compute Intensity: 0.017148392025611175\n"
]
},
"metadata": {},
@ -78,6 +78,7 @@
"source": [
"optimizer = ReductionOptimizer()\n",
"\n",
"compute_compton = get_compute_function(graph, process, machine)\n",
"optimize_to_fixpoint!(optimizer, graph)\n",
"graph"
]
@ -91,7 +92,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Calculated 15537.0 results/s, 1295.0 results/s per thread for QED Process: 'ke->kkkkkke' (12 threads)\n"
"Calculated 133942.0 results/s, 11162.0 results/s per thread for QED Process: 'ke->kkkkke' (12 threads)\n"
]
}
],
@ -109,6 +110,31 @@
"rate_per_thread = rate / Threads.nthreads()\n",
"println(\"Calculated $(round(rate)) results/s, $(round(rate_per_thread)) results/s per thread for $(process) ($(Threads.nthreads()) threads)\")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Calculated 17124.0 results/s, 1427.0 results/s per thread for QED Process: 'ke->kkkkke' (12 threads)\n"
]
}
],
"source": [
"bench_result = @benchmark begin\n",
" Threads.@threads :static for i in eachindex(inputs)\n",
" outputs[i] = compute_compton(inputs[i])\n",
" end\n",
"end\n",
"\n",
"rate = length(inputs) / (mean(bench_result.times) / 1.0e9)\n",
"rate_per_thread = rate / Threads.nthreads()\n",
"println(\"Calculated $(round(rate)) results/s, $(round(rate_per_thread)) results/s per thread for $(process) ($(Threads.nthreads()) threads)\")"
]
}
],
"metadata": {

62
results/FWK8999_QED.txt Normal file
View File

@ -0,0 +1,62 @@
CPU: AMD EPYC 7452 32 Cores, 64 Threads | 122.8 GFLOPS (?, source: https://www.cpubenchmark.net/cpu.php?cpu=AMD+EPYC+7452)
GPU: A30 24GB | 5.161 TFLOPS (source: https://www.techpowerup.com/gpu-specs/a30-pcie.c3792)
Benchmark Summary for QED Process: 'ke->ke':
Measured FLOPS by LIKWID: 5657.0
Total input size: 1.394 GiB
CPU, 64 threads
Time: 0.594810558
Rate: 1.681207548437632e7
GFLOPS: 88.57428190774921
GPU, NVIDIA A30
Time: 1.547648257
Rate: 6.461416510353748e6
GFLOPS: 34.041919930904314
Benchmark Summary for QED Process: 'ke->kke':
Measured FLOPS by LIKWID: 16256.0
Total input size: 1.768 GiB
CPU, 64 threads
Time: 1.294064702
Rate: 7.7275888790914565e6
GFLOPS: 116.99244828756034
GPU, NVIDIA A30
Time: 4.973188906
Rate: 2.0107822544072892e6
GFLOPS: 30.442398346629826
Benchmark Summary for QED Process: 'ke->kkke':
Measured FLOPS by LIKWID: 43433.0
Total input size: 2.632 GiB
CPU, 64 threads
Time: 3.232029091
Rate: 3.094031556784648e6
GFLOPS: 125.15398916399816
GPU, NVIDIA A30
Time: 14.597070187
Rate: 685068.9810963502
GFLOPS: 27.711131662091034
Benchmark Summary for ABC Process: 'AB->AB':
Measured FLOPS by LIKWID: 41.0
Total input size: 2.201 GiB
CPU, 64 threads
Time: 0.688079611
Rate: 1.453320203089116e7
GFLOPS: 0.5549390644454747
GPU, NVIDIA A30
Time: 0.013803574
Rate: 7.244500590933913e8
GFLOPS: 27.662564462822903
Benchmark Summary for ABC Process: 'AB->ABBB':
Measured FLOPS by LIKWID: 899.0
Total input size: 3.079 GiB
CPU, 64 threads
Time: 0.855687624
Rate: 1.1686507692204276e7
GFLOPS: 9.784633680518386
GPU, NVIDIA A30
Time: 0.014804518
Rate: 6.754694749265056e8
GFLOPS: 565.542893445984

View File

@ -62,21 +62,12 @@ function gen_input_assignment_code(
assignInputs = Vector{Expr}()
for (name, symbols) in inputSymbols
(type, index) = type_index_from_name(model(processDescription), name)
p = nothing
if (index > get(in_particles(processDescription), type, 0))
index -= get(in_particles(processDescription), type, 0)
@assert index <= out_particles(processDescription)[type] "Too few particles of type $type in input particles for this process"
p = "filter(x -> typeof(x) <: $type, out_particles($(processInputSymbol)))[$(index)]"
else
p = "filter(x -> typeof(x) <: $type, in_particles($(processInputSymbol)))[$(index)]"
end
p = "get_particle($(processInputSymbol), $(type), $(index))"
for symbol in symbols
device = entry_device(machine)
evalExpr = eval(gen_access_expr(device, symbol))
push!(assignInputs, Meta.parse("$(evalExpr)::ParticleValue{$type} = ParticleValue($p, one(ComplexF64))"))
push!(assignInputs, Meta.parse("$(evalExpr) = ParticleValue{$type, ComplexF64}($p, one(ComplexF64))"))
end
end
@ -111,10 +102,12 @@ end
Execute the code of the given `graph` on the given input particles.
This is essentially shorthand for
```julia
compute_graph = get_compute_function(graph, process)
result = compute_graph(particles)
```
```julia
compute_graph = get_compute_function(graph, process)
result = compute_graph(particles)
```
If an exception occurs during the execution of the generated code, it will be printed for investigation.
See also: [`parse_dag`](@ref), [`parse_process`](@ref), [`gen_process_input`](@ref)
"""
@ -135,6 +128,8 @@ function execute(graph::DAG, process::AbstractProcessDescription, machine::Machi
result = 0
try
result = @eval $func($input)
#functionStr = string(expr)
#println("Function:\n$functionStr")
catch e
println("Error while evaluating: $e")

View File

@ -75,3 +75,7 @@ function operation_effect(estimator::GlobalMetricEstimator, graph::DAG, operatio
ce::Float64 = s * compute_effort(task(operation.input))
return (data = d, computeEffort = ce, computeIntensity = ce / d)::CDCost
end
function String(::GlobalMetricEstimator)
return "global_metric"
end

View File

@ -1,4 +1,5 @@
using AccurateArithmetic
using StaticArrays
"""
compute(::ComputeTaskABC_P, data::ABCParticleValue)
@ -75,14 +76,14 @@ function compute(::ComputeTaskABC_S1, data::ABCParticleValue{P})::ABCParticleVal
end
"""
compute(::ComputeTaskABC_Sum, data::Vector{Float64})
compute(::ComputeTaskABC_Sum, data::StaticVector)
Compute a sum over the vector. Use an algorithm that accounts for accumulated errors in long sums with potentially large differences in magnitude of the summands.
Linearly many FLOP with growing data.
"""
function compute(::ComputeTaskABC_Sum, data::Vector{Float64})::Float64
return sum_kbn(data)
function compute(::ComputeTaskABC_Sum, data::StaticVector)::Float64
return sum(data)
end
"""
@ -159,5 +160,7 @@ function get_expression(::ComputeTaskABC_Sum, device::AbstractDevice, inExprs::V
in = eval.(inExprs)
out = eval(outExpr)
return Meta.parse("$out = compute(ComputeTaskABC_Sum(), [$(unroll_symbol_vector(in))])")
return Meta.parse(
"$out = compute(ComputeTaskABC_Sum(), SVector{$(length(inExprs)), Float64}($(unroll_symbol_vector(in))))",
)
end

View File

@ -5,6 +5,20 @@ using ForwardDiff
ComputeTaskABC_Sum() = ComputeTaskABC_Sum(0)
function _svector_from_type_in(processDescription::ABCProcessDescription, type, particles)
if haskey(in_particles(processDescription), type)
return SVector{in_particles(processDescription)[type], type}(filter(x -> typeof(x) <: type, particles))
end
return SVector{0, type}()
end
function _svector_from_type_out(processDescription::ABCProcessDescription, type, particles)
if haskey(out_particles(processDescription), type)
return SVector{out_particles(processDescription)[type], type}(filter(x -> typeof(x) <: type, particles))
end
return SVector{0, type}()
end
"""
gen_process_input(processDescription::ABCProcessDescription)
@ -58,7 +72,15 @@ function gen_process_input(processDescription::ABCProcessDescription)
end
end
processInput = ABCProcessInput(processDescription, inputParticles, outputParticles)
inA = _svector_from_type_in(processDescription, ParticleA, inputParticles)
inB = _svector_from_type_in(processDescription, ParticleB, inputParticles)
inC = _svector_from_type_in(processDescription, ParticleC, inputParticles)
outA = _svector_from_type_out(processDescription, ParticleA, outputParticles)
outB = _svector_from_type_out(processDescription, ParticleB, outputParticles)
outC = _svector_from_type_out(processDescription, ParticleC, outputParticles)
processInput = ABCProcessInput(processDescription, inA, inB, inC, outA, outB, outC)
return return processInput
end

View File

@ -1,3 +1,5 @@
using StaticArrays
import QEDbase.mass
"""
@ -60,27 +62,30 @@ Input for a ABC Process. Contains the [`ABCProcessDescription`](@ref) of the pro
See also: [`gen_process_input`](@ref)
"""
struct ABCProcessInput <: AbstractProcessInput
struct ABCProcessInput{N1, N2, N3, N4, N5, N6} <: AbstractProcessInput
process::ABCProcessDescription
inParticles::Vector{ABCParticle}
outParticles::Vector{ABCParticle}
inA::SVector{N1, ParticleA}
inB::SVector{N2, ParticleB}
inC::SVector{N3, ParticleC}
outA::SVector{N4, ParticleA}
outB::SVector{N5, ParticleB}
outC::SVector{N6, ParticleC}
end
ABCParticleValue{ParticleType <: ABCParticle} = ParticleValue{ParticleType, ComplexF64}
"""
PARTICLE_MASSES
A constant dictionary containing the masses of the different [`ABCParticle`](@ref)s.
"""
const PARTICLE_MASSES = Dict{Type, Float64}(ParticleA => 1.0, ParticleB => 1.0, ParticleC => 0.0)
"""
mass(t::Type{T}) where {T <: ABCParticle}
Return the mass (at rest) of the given particle type.
"""
mass(t::Type{T}) where {T <: ABCParticle} = PARTICLE_MASSES[t]
mass(::ParticleA) = 1.0
mass(::ParticleB) = 1.0
mass(::ParticleC) = 0.0
mass(::Type{ParticleA}) = 1.0
mass(::Type{ParticleB}) = 1.0
mass(::Type{ParticleC}) = 0.0
"""
interaction_result(t1::Type{T1}, t2::Type{T2}) where {T1 <: ABCParticle, T2 <: ABCParticle}
@ -126,7 +131,7 @@ Return the factor of the inner edge with the given (virtual) particle.
Takes 10 effective FLOP. (3 here + 7 in square(p))
"""
function ABC_inner_edge(p::ABCParticle)
return 1.0 / (square(p) - mass(typeof(p)) * mass(typeof(p)))
return 1.0 / (square(p) - mass(p)^2)
end
"""
@ -166,6 +171,10 @@ function ABC_conserve_momentum(p1::ABCParticle, p2::ABCParticle)
return p3
end
function copy(process::ABCProcessDescription)
return ABCProcessDescription(copy(process.inParticles), copy(process.outParticles))
end
model(::ABCProcessDescription) = ABCModel()
model(::ABCProcessInput) = ABCModel()
@ -195,14 +204,29 @@ function in_particles(process::ABCProcessDescription)
return process.inParticles
end
function in_particles(input::ABCProcessInput)
return input.inParticles
end
function out_particles(process::ABCProcessDescription)
return process.outParticles
end
function out_particles(input::ABCProcessInput)
return input.outParticles
function get_particle(input::ABCProcessInput, t::Type{Particle}, n::Int)::Particle where {Particle}
if (t <: ParticleA)
if (n > length(input.inA))
return input.outA[n - length(input.inA)]
else
return input.inA[n]
end
elseif (t <: ParticleB)
if (n > length(input.inB))
return input.outB[n - length(input.inB)]
else
return input.inB[n]
end
elseif (t <: ParticleC)
if (n > length(input.inC))
return input.outC[n - length(input.inC)]
else
return input.inC[n]
end
end
@assert false "Invalid type given"
end

View File

@ -36,15 +36,26 @@ Pretty print an [`ABCProcessInput`](@ref) (with newlines).
"""
function show(io::IO, processInput::ABCProcessInput)
println(io, "Input for $(processInput.process):")
println(io, " $(length(processInput.inParticles)) Incoming particles:")
for particle in processInput.inParticles
println(io, " $particle")
println(io, "Incoming particles:")
if !isempty(processInput.inA)
println(io, " $(processInput.inA)")
end
println(io, " $(length(processInput.outParticles)) Outgoing Particles:")
for particle in processInput.outParticles
println(io, " $particle")
if !isempty(processInput.inB)
println(io, " $(processInput.inB)")
end
if !isempty(processInput.inC)
println(io, " $(processInput.inC)")
end
println(io, "Outgoing particles:")
if !isempty(processInput.outA)
println(io, " $(processInput.outA)")
end
if !isempty(processInput.outB)
println(io, " $(processInput.outB)")
end
if !isempty(processInput.outC)
println(io, " $(processInput.outC)")
end
return nothing
end
"""

View File

@ -80,6 +80,14 @@ Returns a `<: Vector{AbstractParticle}` object with the values of all outgoing p
"""
function out_particles end
"""
get_particle(::AbstractProcessInput, t::Type, n::Int)
Interface function that must be implemented for every subtype of [`AbstractProcessInput`](@ref).
Returns the `n`th particle of type `t`.
"""
function get_particle end
"""
parse_process(::AbstractString, ::AbstractPhysicsModel)

View File

@ -1,12 +1,13 @@
using StaticArrays
"""
compute(::ComputeTaskQED_P, data::QEDParticleValue)
Return the particle as is and initialize the Value.
"""
function compute(::ComputeTaskQED_P, data::QEDParticleValue{P})::QEDParticleValue{P} where {P <: QEDParticle}
function compute(::ComputeTaskQED_P, data::QEDParticleValue{P}) where {P <: QEDParticle}
# TODO do we actually need this for anything?
return QEDParticleValue{P}(data.p, one(DiracMatrix))
return ParticleValue{P, DiracMatrix}(data.p, one(DiracMatrix))
end
"""
@ -15,7 +16,8 @@ end
Compute an outer edge. Return the particle value with the same particle and the value multiplied by an outer_edge factor.
"""
function compute(::ComputeTaskQED_U, data::PV) where {P <: QEDParticle, PV <: QEDParticleValue{P}}
state = base_state(particle(data.p), direction(data.p), momentum(data.p), spin_or_pol(data.p))
part::P = data.p
state = base_state(particle(part), direction(part), momentum(part), spin_or_pol(part))
return ParticleValue{P, typeof(state)}(
data.p,
state, # will return a SLorentzVector{ComplexF64}, BiSpinor or AdjointBiSpinor
@ -34,7 +36,6 @@ function compute(
) where {P1 <: QEDParticle, P2 <: QEDParticle, PV1 <: QEDParticleValue{P1}, PV2 <: QEDParticleValue{P2}}
p3 = QED_conserve_momentum(data1.p, data2.p)
P3 = interaction_result(P1, P2)
state = QED_vertex()
if (typeof(data1.v) <: AdjointBiSpinor)
state = data1.v * state
@ -47,7 +48,7 @@ function compute(
state = state * data2.v
end
dataOut = ParticleValue{P3, typeof(state)}(P3(p3), state)
dataOut = ParticleValue{P3, typeof(state)}(P3(momentum(p3)), state)
return dataOut
end
@ -64,13 +65,10 @@ function compute(
::ComputeTaskQED_S2,
data1::ParticleValue{P1},
data2::ParticleValue{P2},
)::ComplexF64 where {
P1 <: Union{AntiFermionStateful, FermionStateful},
P2 <: Union{AntiFermionStateful, FermionStateful},
}
@assert isapprox(data1.p.momentum, data2.p.momentum, rtol = sqrt(eps()), atol = sqrt(eps())) "$(data1.p.momentum) vs. $(data2.p.momentum)"
) where {P1 <: Union{AntiFermionStateful, FermionStateful}, P2 <: Union{AntiFermionStateful, FermionStateful}}
#@assert isapprox(data1.p.momentum, data2.p.momentum, rtol = sqrt(eps()), atol = sqrt(eps())) "$(data1.p.momentum) vs. $(data2.p.momentum)"
inner = QED_inner_edge(propagation_result(P1)(data1.p))
inner = QED_inner_edge(propagation_result(P1)(momentum(data1.p)))
# inner edge is just a "scalar", data1 and data2 are bispinor/adjointbispinnor, need to keep correct order
if typeof(data1.v) <: BiSpinor
@ -80,12 +78,11 @@ function compute(
end
end
# TODO: S2 when the particles are photons?
function compute(
::ComputeTaskQED_S2,
data1::ParticleValue{P1},
data2::ParticleValue{P2},
)::ComplexF64 where {P1 <: PhotonStateful, P2 <: PhotonStateful}
) where {P1 <: PhotonStateful, P2 <: PhotonStateful}
# TODO: assert that data1 and data2 are opposites
inner = QED_inner_edge(data1.p)
# inner edge is just a scalar, data1 and data2 are photon states that are just Complex numbers here
@ -97,9 +94,9 @@ end
Compute inner edge (1 input particle, 1 output particle).
"""
function compute(::ComputeTaskQED_S1, data::QEDParticleValue{P})::QEDParticleValue where {P <: QEDParticle}
function compute(::ComputeTaskQED_S1, data::QEDParticleValue{P}) where {P <: QEDParticle}
newP = propagation_result(P)
new_p = newP(data.p)
new_p = newP(momentum(data.p))
# inner edge is just a scalar, can multiply from either side
if typeof(data.v) <: BiSpinor
return ParticleValue(new_p, QED_inner_edge(new_p) * data.v)
@ -109,13 +106,13 @@ function compute(::ComputeTaskQED_S1, data::QEDParticleValue{P})::QEDParticleVal
end
"""
compute(::ComputeTaskQED_Sum, data::Vector{ComplexF64})
compute(::ComputeTaskQED_Sum, data::StaticVector)
Compute a sum over the vector. Use an algorithm that accounts for accumulated errors in long sums with potentially large differences in magnitude of the summands.
Linearly many FLOP with growing data.
"""
function compute(::ComputeTaskQED_Sum, data::Vector{ComplexF64})::ComplexF64
function compute(::ComputeTaskQED_Sum, data::StaticVector)::ComplexF64
# TODO: want to use sum_kbn here but it doesn't seem to support ComplexF64, do it element-wise?
return sum(data)
end
@ -194,5 +191,7 @@ function get_expression(::ComputeTaskQED_Sum, device::AbstractDevice, inExprs::V
in = eval.(inExprs)
out = eval(outExpr)
return Meta.parse("$out = compute(ComputeTaskQED_Sum(), [$(unroll_symbol_vector(in))])")
return Meta.parse(
"$out = compute(ComputeTaskQED_Sum(), SVector{$(length(inExprs)), ComplexF64}($(unroll_symbol_vector(in))))",
)
end

View File

@ -1,6 +1,16 @@
ComputeTaskQED_Sum() = ComputeTaskQED_Sum(0)
function _svector_from_type(processDescription::QEDProcessDescription, type, particles)
if haskey(in_particles(processDescription), type)
return SVector{in_particles(processDescription)[type], type}(filter(x -> typeof(x) <: type, particles))
end
if haskey(out_particles(processDescription), type)
return SVector{out_particles(processDescription)[type], type}(filter(x -> typeof(x) <: type, particles))
end
return SVector{0, type}()
end
"""
gen_process_input(processDescription::QEDProcessDescription)
@ -29,30 +39,37 @@ function gen_process_input(processDescription::QEDProcessDescription)
massSum += rand(rng[threadid()]) * (length(inputMasses) + length(outputMasses))
inputParticles = Vector{QEDParticle}()
particles = Vector{QEDParticle}()
initialMomenta = generate_initial_moms(massSum, inputMasses)
index = 1
for (particle, n) in processDescription.inParticles
for _ in 1:n
mom = initialMomenta[index]
push!(inputParticles, particle(mom))
push!(particles, particle(mom))
index += 1
end
end
outputParticles = Vector{QEDParticle}()
final_momenta = generate_physical_massive_moms(rng[threadid()], massSum, outputMasses)
index = 1
for (particle, n) in processDescription.outParticles
for _ in 1:n
push!(outputParticles, particle(final_momenta[index]))
push!(particles, particle(final_momenta[index]))
index += 1
end
end
processInput = QEDProcessInput(processDescription, inputParticles, outputParticles)
inFerms = _svector_from_type(processDescription, FermionStateful{Incoming, SpinUp}, particles)
outFerms = _svector_from_type(processDescription, FermionStateful{Outgoing, SpinUp}, particles)
inAntiferms = _svector_from_type(processDescription, AntiFermionStateful{Incoming, SpinUp}, particles)
outAntiferms = _svector_from_type(processDescription, AntiFermionStateful{Outgoing, SpinUp}, particles)
inPhotons = _svector_from_type(processDescription, PhotonStateful{Incoming, PolX}, particles)
outPhotons = _svector_from_type(processDescription, PhotonStateful{Outgoing, PolX}, particles)
return return processInput
processInput =
QEDProcessInput(processDescription, inFerms, outFerms, inAntiferms, outAntiferms, inPhotons, outPhotons)
return processInput
end
"""

View File

@ -82,7 +82,7 @@ end
function particle_after_tie(p::FeynmanParticle, t::FeynmanTie)
if p == t.in1 || p == t.in2
return FeynmanParticle(FermionStateful{Incoming}, -1) # placeholder particle and id for tied particles
return FeynmanParticle(FermionStateful{Incoming, SpinUp}, -1) # placeholder particle and id for tied particles
end
return p
end

View File

@ -1,4 +1,5 @@
using QEDprocesses
using StaticArrays
import QEDbase.mass
# TODO check
@ -34,19 +35,6 @@ struct QEDProcessDescription <: AbstractProcessDescription
outParticles::Dict{Type{<:QEDParticle{Outgoing}}, Int}
end
"""
QEDProcessInput <: AbstractProcessInput
Input for a QED Process. Contains the [`QEDProcessDescription`](@ref) of the process it is an input for, and the values of the in and out particles.
See also: [`gen_process_input`](@ref)
"""
struct QEDProcessInput <: AbstractProcessInput
process::QEDProcessDescription
inParticles::Vector{QEDParticle}
outParticles::Vector{QEDParticle}
end
QEDParticleValue{ParticleType <: QEDParticle} = Union{
ParticleValue{ParticleType, BiSpinor},
ParticleValue{ParticleType, AdjointBiSpinor},
@ -60,51 +48,44 @@ QEDParticleValue{ParticleType <: QEDParticle} = Union{
A photon of the [`QEDModel`](@ref) with its state.
"""
struct PhotonStateful{Direction <: ParticleDirection} <: QEDParticle{Direction}
struct PhotonStateful{Direction <: ParticleDirection, Pol <: AbstractDefinitePolarization} <: QEDParticle{Direction}
momentum::SFourMomentum
# this will maybe change to the full polarization vector? or do i need both
polarization::AbstractDefinitePolarization
end
PhotonStateful{Direction}(mom::SFourMomentum) where {Direction <: ParticleDirection} =
PhotonStateful{Direction}(mom, PolX()) # TODO: make allpol possible
PhotonStateful{Direction, PolX}(mom)
PhotonStateful{Dir1}(ph::PhotonStateful{Dir2}) where {Dir1 <: ParticleDirection, Dir2 <: ParticleDirection} =
PhotonStateful{Dir1}(ph.momentum, ph.polarization)
PhotonStateful{Dir, Pol}(ph::PhotonStateful) where {Dir, Pol} = PhotonStateful{Dir, Pol}(ph.momentum)
"""
FermionStateful <: QEDParticle
A fermion of the [`QEDModel`](@ref) with its state.
"""
struct FermionStateful{Direction <: ParticleDirection} <: QEDParticle{Direction}
struct FermionStateful{Direction <: ParticleDirection, Spin <: AbstractDefiniteSpin} <: QEDParticle{Direction}
momentum::SFourMomentum
spin::AbstractDefiniteSpin
# TODO: mass for electron/muon/tauon representation?
end
FermionStateful{Direction}(mom::SFourMomentum) where {Direction <: ParticleDirection} =
FermionStateful{Direction}(mom, SpinUp()) # TODO: make allspin possible
FermionStateful{Direction, SpinUp}(mom)
FermionStateful{Dir1}(f::FermionStateful{Dir2}) where {Dir1 <: ParticleDirection, Dir2 <: ParticleDirection} =
FermionStateful{Dir1}(f.momentum, f.spin)
FermionStateful{Dir, Spin}(f::FermionStateful) where {Dir, Spin} = FermionStateful{Dir, Spin}(f.momentum)
"""
AntiFermionStateful <: QEDParticle
An anti-fermion of the [`QEDModel`](@ref) with its state.
"""
struct AntiFermionStateful{Direction <: ParticleDirection} <: QEDParticle{Direction}
struct AntiFermionStateful{Direction <: ParticleDirection, Spin <: AbstractDefiniteSpin} <: QEDParticle{Direction}
momentum::SFourMomentum
spin::AbstractDefiniteSpin
# TODO: mass for electron/muon/tauon representation?
end
AntiFermionStateful{Direction}(mom::SFourMomentum) where {Direction <: ParticleDirection} =
AntiFermionStateful{Direction}(mom, SpinUp()) # TODO: make allspin possible
AntiFermionStateful{Direction, SpinUp}(mom)
AntiFermionStateful{Dir1}(f::AntiFermionStateful{Dir2}) where {Dir1 <: ParticleDirection, Dir2 <: ParticleDirection} =
AntiFermionStateful{Dir1}(f.momentum, f.spin)
AntiFermionStateful{Dir, Spin}(f::AntiFermionStateful) where {Dir, Spin} = AntiFermionStateful{Dir, Spin}(f.momentum)
"""
interaction_result(t1::Type{T1}, t2::Type{T2}) where {T1 <: QEDParticle, T2 <: QEDParticle}
@ -115,19 +96,33 @@ function interaction_result(t1::Type{T1}, t2::Type{T2}) where {T1 <: QEDParticle
@assert false "Invalid interaction between particles of types $t1 and $t2"
end
interaction_result(::Type{FermionStateful{Incoming}}, ::Type{FermionStateful{Outgoing}}) = PhotonStateful{Incoming}
interaction_result(::Type{FermionStateful{Incoming}}, ::Type{AntiFermionStateful{Incoming}}) = PhotonStateful{Incoming}
interaction_result(::Type{FermionStateful{Incoming}}, ::Type{<:PhotonStateful}) = FermionStateful{Outgoing}
interaction_result(
::Type{FermionStateful{Incoming, Spin1}},
::Type{FermionStateful{Outgoing, Spin2}},
) where {Spin1, Spin2} = PhotonStateful{Incoming, PolX}
interaction_result(
::Type{FermionStateful{Incoming, Spin1}},
::Type{AntiFermionStateful{Incoming, Spin2}},
) where {Spin1, Spin2} = PhotonStateful{Incoming, PolX}
interaction_result(::Type{FermionStateful{Incoming, Spin1}}, ::Type{<:PhotonStateful}) where {Spin1} =
FermionStateful{Outgoing, SpinUp}
interaction_result(::Type{FermionStateful{Outgoing}}, ::Type{FermionStateful{Incoming}}) = PhotonStateful{Incoming}
interaction_result(::Type{FermionStateful{Outgoing}}, ::Type{AntiFermionStateful{Outgoing}}) = PhotonStateful{Incoming}
interaction_result(::Type{FermionStateful{Outgoing}}, ::Type{<:PhotonStateful}) = FermionStateful{Incoming}
interaction_result(
::Type{FermionStateful{Outgoing, Spin1}},
::Type{FermionStateful{Incoming, Spin2}},
) where {Spin1, Spin2} = PhotonStateful{Incoming, PolX}
interaction_result(
::Type{FermionStateful{Outgoing, Spin1}},
::Type{AntiFermionStateful{Outgoing, Spin2}},
) where {Spin1, Spin2} = PhotonStateful{Incoming, PolX}
interaction_result(::Type{FermionStateful{Outgoing, Spin1}}, ::Type{<:PhotonStateful}) where {Spin1} =
FermionStateful{Incoming, SpinUp}
# antifermion mirror
interaction_result(::Type{AntiFermionStateful{Incoming}}, t2::Type{<:QEDParticle}) =
interaction_result(FermionStateful{Outgoing}, t2)
interaction_result(::Type{AntiFermionStateful{Outgoing}}, t2::Type{<:QEDParticle}) =
interaction_result(FermionStateful{Incoming}, t2)
interaction_result(::Type{AntiFermionStateful{Incoming, Spin}}, t2::Type{<:QEDParticle}) where {Spin} =
interaction_result(FermionStateful{Outgoing, Spin}, t2)
interaction_result(::Type{AntiFermionStateful{Outgoing, Spin}}, t2::Type{<:QEDParticle}) where {Spin} =
interaction_result(FermionStateful{Incoming, Spin}, t2)
# photon commutativity
interaction_result(t1::Type{<:PhotonStateful}, t2::Type{<:QEDParticle}) = interaction_result(t2, t1)
@ -142,12 +137,18 @@ end
Return the type of the inverted direction. E.g.
"""
propagation_result(::Type{FermionStateful{Incoming}}) = FermionStateful{Outgoing}
propagation_result(::Type{FermionStateful{Outgoing}}) = FermionStateful{Incoming}
propagation_result(::Type{AntiFermionStateful{Incoming}}) = AntiFermionStateful{Outgoing}
propagation_result(::Type{AntiFermionStateful{Outgoing}}) = AntiFermionStateful{Incoming}
propagation_result(::Type{PhotonStateful{Incoming}}) = PhotonStateful{Outgoing}
propagation_result(::Type{PhotonStateful{Outgoing}}) = PhotonStateful{Incoming}
propagation_result(::Type{FermionStateful{Incoming, Spin}}) where {Spin <: AbstractDefiniteSpin} =
FermionStateful{Outgoing, Spin}
propagation_result(::Type{FermionStateful{Outgoing, Spin}}) where {Spin <: AbstractDefiniteSpin} =
FermionStateful{Incoming, Spin}
propagation_result(::Type{AntiFermionStateful{Incoming, Spin}}) where {Spin <: AbstractDefiniteSpin} =
AntiFermionStateful{Outgoing, Spin}
propagation_result(::Type{AntiFermionStateful{Outgoing, Spin}}) where {Spin <: AbstractDefiniteSpin} =
AntiFermionStateful{Incoming, Spin}
propagation_result(::Type{PhotonStateful{Incoming, Pol}}) where {Pol <: AbstractDefinitePolarization} =
PhotonStateful{Outgoing, Pol}
propagation_result(::Type{PhotonStateful{Outgoing, Pol}}) where {Pol <: AbstractDefinitePolarization} =
PhotonStateful{Incoming, Pol}
"""
types(::QEDModel)
@ -156,12 +157,12 @@ Return a Vector of the possible types of particle in the [`QEDModel`](@ref).
"""
function types(::QEDModel)
return [
PhotonStateful{Incoming},
PhotonStateful{Outgoing},
FermionStateful{Incoming},
FermionStateful{Outgoing},
AntiFermionStateful{Incoming},
AntiFermionStateful{Outgoing},
PhotonStateful{Incoming, PolX},
PhotonStateful{Outgoing, PolX},
FermionStateful{Incoming, SpinUp},
FermionStateful{Outgoing, SpinUp},
AntiFermionStateful{Incoming, SpinUp},
AntiFermionStateful{Outgoing, SpinUp},
]
end
@ -190,17 +191,23 @@ end
@inline momentum(p::FermionStateful)::SFourMomentum = p.momentum
@inline momentum(p::AntiFermionStateful)::SFourMomentum = p.momentum
@inline spin_or_pol(p::PhotonStateful)::AbstractPolarization = p.polarization
@inline spin_or_pol(p::FermionStateful)::AbstractSpin = p.spin
@inline spin_or_pol(p::AntiFermionStateful)::AbstractSpin = p.spin
@inline spin_or_pol(p::PhotonStateful{Dir, Pol}) where {Dir, Pol <: AbstractDefinitePolarization} = Pol()
@inline spin_or_pol(p::FermionStateful{Dir, Spin}) where {Dir, Spin <: AbstractDefiniteSpin} = Spin()
@inline spin_or_pol(p::AntiFermionStateful{Dir, Spin}) where {Dir, Spin <: AbstractDefiniteSpin} = Spin()
@inline direction(::PhotonStateful{Dir}) where {Dir <: ParticleDirection} = Dir()
@inline direction(::FermionStateful{Dir}) where {Dir <: ParticleDirection} = Dir()
@inline direction(::AntiFermionStateful{Dir}) where {Dir <: ParticleDirection} = Dir()
@inline direction(
::Type{P},
) where {P <: Union{FermionStateful{Incoming}, AntiFermionStateful{Incoming}, PhotonStateful{Incoming}}} = Incoming()
@inline direction(
::Type{P},
) where {P <: Union{FermionStateful{Outgoing}, AntiFermionStateful{Outgoing}, PhotonStateful{Outgoing}}} = Outgoing()
@inline direction(::Type{PhotonStateful{Dir}}) where {Dir <: ParticleDirection} = Dir()
@inline direction(::Type{FermionStateful{Dir}}) where {Dir <: ParticleDirection} = Dir()
@inline direction(::Type{AntiFermionStateful{Dir}}) where {Dir <: ParticleDirection} = Dir()
@inline direction(
::P,
) where {P <: Union{FermionStateful{Incoming}, AntiFermionStateful{Incoming}, PhotonStateful{Incoming}}} = Incoming()
@inline direction(
::P,
) where {P <: Union{FermionStateful{Outgoing}, AntiFermionStateful{Outgoing}, PhotonStateful{Outgoing}}} = Outgoing()
@inline isincoming(::QEDParticle{Incoming}) = true
@inline isincoming(::QEDParticle{Outgoing}) = false
@ -216,12 +223,12 @@ end
@inline mass(::Type{<:AntiFermionStateful}) = 1.0
@inline mass(::Type{<:PhotonStateful}) = 0.0
@inline invert_momentum(p::FermionStateful{Dir}) where {Dir <: ParticleDirection} =
FermionStateful{Dir}(-p.momentum, p.spin)
@inline invert_momentum(p::AntiFermionStateful{Dir}) where {Dir <: ParticleDirection} =
AntiFermionStateful{Dir}(-p.momentum, p.spin)
@inline invert_momentum(k::PhotonStateful{Dir}) where {Dir <: ParticleDirection} =
PhotonStateful{Dir}(-k.momentum, k.polarization)
@inline invert_momentum(p::FermionStateful{Dir, Spin}) where {Dir, Spin} =
FermionStateful{Dir, Spin}(-p.momentum, p.spin)
@inline invert_momentum(p::AntiFermionStateful{Dir, Spin}) where {Dir, Spin} =
AntiFermionStateful{Dir, Spin}(-p.momentum, p.spin)
@inline invert_momentum(k::PhotonStateful{Dir, Spin}) where {Dir, Spin} =
PhotonStateful{Dir, Spin}(-k.momentum, k.polarization)
"""
@ -240,10 +247,10 @@ function caninteract(T1::Type{<:QEDParticle}, T2::Type{<:QEDParticle})
end
for (P1, P2) in [(T1, T2), (T2, T1)]
if (P1 == FermionStateful{Incoming} && P2 == AntiFermionStateful{Outgoing})
if (P1 <: FermionStateful{Incoming} && P2 <: AntiFermionStateful{Outgoing})
return false
end
if (P1 == FermionStateful{Outgoing} && P2 == AntiFermionStateful{Incoming})
if (P1 <: FermionStateful{Outgoing} && P2 <: AntiFermionStateful{Incoming})
return false
end
end
@ -253,17 +260,17 @@ end
function type_index_from_name(::QEDModel, name::String)
if startswith(name, "ki")
return (PhotonStateful{Incoming}, parse(Int, name[3:end]))
return (PhotonStateful{Incoming, PolX}, parse(Int, name[3:end]))
elseif startswith(name, "ko")
return (PhotonStateful{Outgoing}, parse(Int, name[3:end]))
return (PhotonStateful{Outgoing, PolX}, parse(Int, name[3:end]))
elseif startswith(name, "ei")
return (FermionStateful{Incoming}, parse(Int, name[3:end]))
return (FermionStateful{Incoming, SpinUp}, parse(Int, name[3:end]))
elseif startswith(name, "eo")
return (FermionStateful{Outgoing}, parse(Int, name[3:end]))
return (FermionStateful{Outgoing, SpinUp}, parse(Int, name[3:end]))
elseif startswith(name, "pi")
return (AntiFermionStateful{Incoming}, parse(Int, name[3:end]))
return (AntiFermionStateful{Incoming, SpinUp}, parse(Int, name[3:end]))
elseif startswith(name, "po")
return (AntiFermionStateful{Outgoing}, parse(Int, name[3:end]))
return (AntiFermionStateful{Outgoing, SpinUp}, parse(Int, name[3:end]))
else
throw("Invalid name for a particle in the QED model")
end
@ -291,8 +298,7 @@ Return the factor of a vertex in a QED feynman diagram.
end
@inline function QED_inner_edge(p::QEDParticle)
pos_mom = p.momentum
return propagator(particle(p), pos_mom)
return propagator(particle(p), p.momentum)
end
"""
@ -300,24 +306,49 @@ end
Calculate and return a new particle from two given interacting ones at a vertex.
"""
function QED_conserve_momentum(p1::QEDParticle, p2::QEDParticle)
#println("Conserving momentum of \n$(direction(p1)) $(p1)\n and \n$(direction(p2)) $(p2)")
T3 = interaction_result(typeof(p1), typeof(p2))
# TODO: probably also need to do something about the spin/pol
function QED_conserve_momentum(
p1::P1,
p2::P2,
) where {
Dir1 <: ParticleDirection,
Dir2 <: ParticleDirection,
SpinPol1 <: AbstractSpinOrPolarization,
SpinPol2 <: AbstractSpinOrPolarization,
P1 <: Union{FermionStateful{Dir1, SpinPol1}, AntiFermionStateful{Dir1, SpinPol1}, PhotonStateful{Dir1, SpinPol1}},
P2 <: Union{FermionStateful{Dir2, SpinPol2}, AntiFermionStateful{Dir2, SpinPol2}, PhotonStateful{Dir2, SpinPol2}},
}
P3 = interaction_result(P1, P2)
p1_mom = p1.momentum
if (typeof(direction(p1)) <: Outgoing)
if (Dir1 <: Outgoing)
p1_mom *= -1
end
p2_mom = p2.momentum
if (typeof(direction(p2)) <: Outgoing)
if (Dir2 <: Outgoing)
p2_mom *= -1
end
p3_mom = p1_mom + p2_mom
if (typeof(direction(T3)) <: Incoming)
return T3(-p3_mom)
if (typeof(direction(P3)) <: Incoming)
return P3(-p3_mom)
end
return T3(p3_mom)
return P3(p3_mom)
end
"""
QEDProcessInput <: AbstractProcessInput
Input for a QED Process. Contains the [`QEDProcessDescription`](@ref) of the process it is an input for, and the values of the in and out particles.
See also: [`gen_process_input`](@ref)
"""
struct QEDProcessInput{N1, N2, N3, N4, N5, N6} <: AbstractProcessInput
process::QEDProcessDescription
inFerms::SVector{N1, FermionStateful{Incoming, SpinUp}}
outFerms::SVector{N2, FermionStateful{Outgoing, SpinUp}}
inAntiferms::SVector{N3, AntiFermionStateful{Incoming, SpinUp}}
outAntiferms::SVector{N4, AntiFermionStateful{Outgoing, SpinUp}}
inPhotons::SVector{N5, PhotonStateful{Incoming, PolX}}
outPhotons::SVector{N6, PhotonStateful{Outgoing, PolX}}
end
"""
@ -328,6 +359,10 @@ Return the model of this process description.
model(::QEDProcessDescription) = QEDModel()
model(::QEDProcessInput) = QEDModel()
function copy(process::QEDProcessDescription)
return QEDProcessDescription(copy(process.inParticles), copy(process.outParticles))
end
==(p1::QEDProcessDescription, p2::QEDProcessDescription) =
p1.inParticles == p2.inParticles && p1.outParticles == p2.outParticles
@ -335,14 +370,23 @@ function in_particles(process::QEDProcessDescription)
return process.inParticles
end
function in_particles(input::QEDProcessInput)
return input.inParticles
end
function out_particles(process::QEDProcessDescription)
return process.outParticles
end
function out_particles(input::QEDProcessInput)
return input.outParticles
function get_particle(input::QEDProcessInput, t::Type{Particle}, n::Int)::Particle where {Particle}
if (t <: FermionStateful{Incoming})
return input.inFerms[n]
elseif (t <: FermionStateful{Outgoing})
return input.outFerms[n]
elseif (t <: AntiFermionStateful{Incoming})
return input.inAntiferms[n]
elseif (t <: AntiFermionStateful{Outgoing})
return input.outAntiferms[n]
elseif (t <: PhotonStateful{Incoming})
return input.inPhotons[n]
elseif (t <: PhotonStateful{Outgoing})
return input.outPhotons[n]
end
@assert false "Invalid type given"
end

View File

@ -32,20 +32,63 @@ function show(io::IO, process::QEDProcessDescription)
return nothing
end
"""
String(process::QEDProcessDescription)
Create a short string suitable as a filename or similar, describing the given process.
```jldoctest
julia> using MetagraphOptimization
julia> String(parse_process("ke->ke", QEDModel()))
qed_ke-ke
julia> print(parse_process("kk->ep", QEDModel()))
qed_kk-ep
```
"""
function String(process::QEDProcessDescription)
# types() gives the types in order (QED) instead of random like keys() would
str = "qed_"
for type in types(QEDModel())
for _ in 1:get(process.inParticles, type, 0)
str = str * String(type)
end
end
str = str * "-"
for type in types(QEDModel())
for _ in 1:get(process.outParticles, type, 0)
str = str * String(type)
end
end
return str
end
"""
show(io::IO, processInput::QEDProcessInput)
Pretty print an [`QEDProcessInput`](@ref) (with newlines).
Pretty print a [`QEDProcessInput`](@ref) (with newlines).
"""
function show(io::IO, processInput::QEDProcessInput)
println(io, "Input for $(processInput.process):")
println(io, " $(length(processInput.inParticles)) Incoming particles:")
for particle in processInput.inParticles
println(io, " $particle")
if !isempty(processInput.inFerms)
println(io, " $(processInput.inFerms)")
end
println(io, " $(length(processInput.outParticles)) Outgoing Particles:")
for particle in processInput.outParticles
println(io, " $particle")
if !isempty(processInput.outFerms)
println(io, " $(processInput.outFerms)")
end
if !isempty(processInput.inAntiferms)
println(io, " $(processInput.inAntiferms)")
end
if !isempty(processInput.outAntiferms)
println(io, " $(processInput.outAntiferms)")
end
if !isempty(processInput.inPhotons)
println(io, " $(processInput.inPhotons)")
end
if !isempty(processInput.outPhotons)
println(io, " $(processInput.outPhotons)")
end
return nothing
end
@ -53,7 +96,7 @@ end
"""
show(io::IO, particle::T) where {T <: QEDParticle}
Pretty print an [`QEDParticle`](@ref) (no newlines).
Pretty print a [`QEDParticle`](@ref) (no newlines).
"""
function show(io::IO, particle::T) where {T <: QEDParticle}
print(io, "$(String(typeof(particle))): $(particle.momentum)")

View File

@ -3,7 +3,7 @@ using UUIDs
using Base.Threads
# TODO: reliably find out how many threads we're running with (nthreads() returns 1 when precompiling :/)
rng = [Random.MersenneTwister(0) for _ in 1:32]
rng = [Random.MersenneTwister(0) for _ in 1:64]
"""
Node

View File

@ -71,3 +71,7 @@ function optimize_to_fixpoint!(optimizer::GreedyOptimizer, graph::DAG)
end
return nothing
end
function String(optimizer::GreedyOptimizer)
return "greedy_optimizer_$(optimizer.estimator)"
end

View File

@ -47,3 +47,7 @@ function optimize_step!(optimizer::RandomWalkOptimizer, graph::DAG)
end
end
end
function String(::RandomWalkOptimizer)
return "random_walker"
end

View File

@ -28,3 +28,7 @@ function optimize_to_fixpoint!(optimizer::ReductionOptimizer, graph::DAG)
end
return nothing
end
function String(::ReductionOptimizer)
return "reduction_optimizer"
end

View File

@ -4,5 +4,7 @@ QEDbase = "10e22c08-3ccb-4172-bfcf-7d7aa3d04d93"
QEDprocesses = "46de9c38-1bb3-4547-a1ec-da24d767fdad"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"

View File

@ -18,12 +18,12 @@ end
@safetestset "ABC-Model Unit Tests " begin
include("unit_tests_abcmodel.jl")
end
@safetestset "QED Feynman Diagram Generation Tests" begin
include("unit_tests_qed_diagrams.jl")
end
@safetestset "QED-Model Unit Tests " begin
include("unit_tests_qedmodel.jl")
end
@safetestset "QED Feynman Diagram Generation Tests" begin
include("unit_tests_qed_diagrams.jl")
end
@safetestset "Node Reduction Unit Tests " begin
include("node_reduction.jl")
end

View File

@ -2,6 +2,8 @@ using MetagraphOptimization
using QEDbase
using AccurateArithmetic
using Random
using UUIDs
using StaticArrays
import MetagraphOptimization.ABCParticle
import MetagraphOptimization.interaction_result
@ -27,11 +29,11 @@ function ground_truth_graph_result(input::ABCProcessInput)
constant = (1 / 137.0)^2
# calculate particle C in diagram 1
diagram1_C = ParticleC(input.inParticles[1].momentum + input.inParticles[2].momentum)
diagram2_C = ParticleC(input.inParticles[1].momentum + input.outParticles[2].momentum)
diagram1_C = ParticleC(input.inA[1].momentum + input.inB[1].momentum)
diagram2_C = ParticleC(input.inA[1].momentum + input.outB[1].momentum)
diagram1_Cp = ParticleC(input.outParticles[1].momentum + input.outParticles[2].momentum)
diagram2_Cp = ParticleC(input.outParticles[1].momentum + input.inParticles[2].momentum)
diagram1_Cp = ParticleC(input.outA[1].momentum + input.outB[1].momentum)
diagram2_Cp = ParticleC(input.outA[1].momentum + input.inB[1].momentum)
check_particle_reverse_moment(diagram1_Cp.momentum, diagram1_C.momentum)
check_particle_reverse_moment(diagram2_Cp.momentum, diagram2_C.momentum)
@ -47,7 +49,18 @@ function ground_truth_graph_result(input::ABCProcessInput)
return sum_kbn([diagram1_result, diagram2_result])
end
machine = get_machine_info()
machine = Machine(
[
MetagraphOptimization.NumaNode(
0,
1,
MetagraphOptimization.default_strategy(MetagraphOptimization.NumaNode),
-1.0,
UUIDs.uuid1(),
),
],
[-1.0;;],
)
process_2_2 = ABCProcessDescription(
Dict{Type, Int64}(ParticleA => 1, ParticleB => 1),
@ -56,14 +69,12 @@ process_2_2 = ABCProcessDescription(
particles_2_2 = ABCProcessInput(
process_2_2,
ABCParticle[
ParticleA(SFourMomentum(0.823648, 0.0, 0.0, 0.823648)),
ParticleB(SFourMomentum(0.823648, 0.0, 0.0, -0.823648)),
],
ABCParticle[
ParticleA(SFourMomentum(0.823648, -0.835061, -0.474802, 0.277915)),
ParticleB(SFourMomentum(0.823648, 0.835061, 0.474802, -0.277915)),
],
SVector{1}(ParticleA(SFourMomentum(0.823648, 0.0, 0.0, 0.823648))),
SVector{1}(ParticleB(SFourMomentum(0.823648, 0.0, 0.0, -0.823648))),
SVector{0, ParticleC}(),
SVector{1}(ParticleA(SFourMomentum(0.823648, -0.835061, -0.474802, 0.277915))),
SVector{1}(ParticleB(SFourMomentum(0.823648, 0.835061, 0.474802, -0.277915))),
SVector{0, ParticleC}(),
)
expected_result = ground_truth_graph_result(particles_2_2)

View File

@ -3,6 +3,7 @@ using QEDbase
using QEDprocesses
using StatsBase # for countmap
using Random
using UUIDs
import MetagraphOptimization.caninteract
import MetagraphOptimization.issame
@ -17,32 +18,32 @@ def_momentum = SFourMomentum(1.0, 0.0, 0.0, 0.0)
RNG = Random.default_rng()
testparticleTypes = [
PhotonStateful{Incoming},
PhotonStateful{Outgoing},
FermionStateful{Incoming},
FermionStateful{Outgoing},
AntiFermionStateful{Incoming},
AntiFermionStateful{Outgoing},
PhotonStateful{Incoming, PolX},
PhotonStateful{Outgoing, PolX},
FermionStateful{Incoming, SpinUp},
FermionStateful{Outgoing, SpinUp},
AntiFermionStateful{Incoming, SpinUp},
AntiFermionStateful{Outgoing, SpinUp},
]
testparticleTypesPropagated = [
PhotonStateful{Outgoing},
PhotonStateful{Incoming},
FermionStateful{Outgoing},
FermionStateful{Incoming},
AntiFermionStateful{Outgoing},
AntiFermionStateful{Incoming},
PhotonStateful{Outgoing, PolX},
PhotonStateful{Incoming, PolX},
FermionStateful{Outgoing, SpinUp},
FermionStateful{Incoming, SpinUp},
AntiFermionStateful{Outgoing, SpinUp},
AntiFermionStateful{Incoming, SpinUp},
]
function compton_groundtruth(input::QEDProcessInput)
# p1k1 -> p2k2
# formula: (ie)^2 (u(p2) slashed(ε1) S(p2 k1) slashed(ε2) u(p1) + u(p2) slashed(ε2) S(p1 + k1) slashed(ε1) u(p1))
p1 = input.inParticles[findfirst(x -> typeof(x) <: FermionStateful, input.inParticles)]
p2 = input.outParticles[findfirst(x -> typeof(x) <: FermionStateful, input.outParticles)]
p1 = input.inFerms[1]
p2 = input.outFerms[1]
k1 = input.inParticles[findfirst(x -> typeof(x) <: PhotonStateful, input.inParticles)]
k2 = input.outParticles[findfirst(x -> typeof(x) <: PhotonStateful, input.outParticles)]
k1 = input.inPhotons[1]
k2 = input.outPhotons[1]
u_p1 = base_state(Electron(), Incoming(), p1.momentum, spin_or_pol(p1))
u_p2 = base_state(Electron(), Outgoing(), p2.momentum, spin_or_pol(p2))
@ -117,36 +118,36 @@ end
@testset "Known processes" begin
compton_process = QEDProcessDescription(
Dict{Type, Int}(PhotonStateful{Incoming} => 1, FermionStateful{Incoming} => 1),
Dict{Type, Int}(PhotonStateful{Outgoing} => 1, FermionStateful{Outgoing} => 1),
Dict{Type, Int}(PhotonStateful{Incoming, PolX} => 1, FermionStateful{Incoming, SpinUp} => 1),
Dict{Type, Int}(PhotonStateful{Outgoing, PolX} => 1, FermionStateful{Outgoing, SpinUp} => 1),
)
@test parse_process("ke->ke", QEDModel()) == compton_process
positron_compton_process = QEDProcessDescription(
Dict{Type, Int}(PhotonStateful{Incoming} => 1, AntiFermionStateful{Incoming} => 1),
Dict{Type, Int}(PhotonStateful{Outgoing} => 1, AntiFermionStateful{Outgoing} => 1),
Dict{Type, Int}(PhotonStateful{Incoming, PolX} => 1, AntiFermionStateful{Incoming, SpinUp} => 1),
Dict{Type, Int}(PhotonStateful{Outgoing, PolX} => 1, AntiFermionStateful{Outgoing, SpinUp} => 1),
)
@test parse_process("kp->kp", QEDModel()) == positron_compton_process
trident_process = QEDProcessDescription(
Dict{Type, Int}(PhotonStateful{Incoming} => 1, FermionStateful{Incoming} => 1),
Dict{Type, Int}(FermionStateful{Outgoing} => 2, AntiFermionStateful{Outgoing} => 1),
Dict{Type, Int}(PhotonStateful{Incoming, PolX} => 1, FermionStateful{Incoming, SpinUp} => 1),
Dict{Type, Int}(FermionStateful{Outgoing, SpinUp} => 2, AntiFermionStateful{Outgoing, SpinUp} => 1),
)
@test parse_process("ke->eep", QEDModel()) == trident_process
pair_production_process = QEDProcessDescription(
Dict{Type, Int}(PhotonStateful{Incoming} => 2),
Dict{Type, Int}(FermionStateful{Outgoing} => 1, AntiFermionStateful{Outgoing} => 1),
Dict{Type, Int}(PhotonStateful{Incoming, PolX} => 2),
Dict{Type, Int}(FermionStateful{Outgoing, SpinUp} => 1, AntiFermionStateful{Outgoing, SpinUp} => 1),
)
@test parse_process("kk->pe", QEDModel()) == pair_production_process
pair_annihilation_process = QEDProcessDescription(
Dict{Type, Int}(FermionStateful{Incoming} => 1, AntiFermionStateful{Incoming} => 1),
Dict{Type, Int}(PhotonStateful{Outgoing} => 2),
Dict{Type, Int}(FermionStateful{Incoming, SpinUp} => 1, AntiFermionStateful{Incoming, SpinUp} => 1),
Dict{Type, Int}(PhotonStateful{Outgoing, PolX} => 2),
)
@test parse_process("pe->kk", QEDModel()) == pair_annihilation_process
@ -160,12 +161,24 @@ end
for i in 1:100
input = gen_process_input(process)
@test countmap(typeof.(input.inParticles)) == process.inParticles
@test countmap(typeof.(input.outParticles)) == process.outParticles
@test length(input.inFerms) == get(process.inParticles, FermionStateful{Incoming, SpinUp}, 0)
@test length(input.inAntiferms) == get(process.inParticles, AntiFermionStateful{Incoming, SpinUp}, 0)
@test length(input.inPhotons) == get(process.inParticles, PhotonStateful{Incoming, PolX}, 0)
@test length(input.outFerms) == get(process.outParticles, FermionStateful{Outgoing, SpinUp}, 0)
@test length(input.outAntiferms) == get(process.outParticles, AntiFermionStateful{Outgoing, SpinUp}, 0)
@test length(input.outPhotons) == get(process.outParticles, PhotonStateful{Outgoing, PolX}, 0)
@test isapprox(
sum(getfield.(input.inParticles, :momentum)),
sum(getfield.(input.outParticles, :momentum));
sum([
getfield.(input.inFerms, :momentum)...,
getfield.(input.inAntiferms, :momentum)...,
getfield.(input.inPhotons, :momentum)...,
]),
sum([
getfield.(input.outFerms, :momentum)...,
getfield.(input.outAntiferms, :momentum)...,
getfield.(input.outPhotons, :momentum)...,
]);
atol = sqrt(eps()),
)
end
@ -179,7 +192,18 @@ end
model = QEDModel()
process = parse_process("ke->ke", model)
machine = get_machine_info()
machine = Machine(
[
MetagraphOptimization.NumaNode(
0,
1,
MetagraphOptimization.default_strategy(MetagraphOptimization.NumaNode),
-1.0,
UUIDs.uuid1(),
),
],
[-1.0;;],
)
graph = MetagraphOptimization.DAG()
@ -289,3 +313,37 @@ end
compton_function = get_compute_function(graph_generated, process, machine)
@test isapprox(compton_function.(input), compton_groundtruth.(input))
end
@testset "Equal results after optimization" for optimizer in
[ReductionOptimizer(), RandomWalkOptimizer(MersenneTwister(0))]
@testset "Process $proc_str" for proc_str in ["ke->ke", "kp->kp", "kk->ep", "ep->kk", "ke->kke", "ke->kkke"]
model = QEDModel()
process = parse_process(proc_str, model)
machine = Machine(
[
MetagraphOptimization.NumaNode(
0,
1,
MetagraphOptimization.default_strategy(MetagraphOptimization.NumaNode),
-1.0,
UUIDs.uuid1(),
),
],
[-1.0;;],
)
graph = gen_graph(process)
compute_function = get_compute_function(graph, process, machine)
if (typeof(optimizer) <: RandomWalkOptimizer)
optimize!(optimizer, graph, 100)
elseif (typeof(optimizer) <: ReductionOptimizer)
optimize_to_fixpoint!(optimizer, graph)
end
reduced_compute_function = get_compute_function(graph, process, machine)
input = [gen_process_input(process) for _ in 1:100]
@test isapprox(compute_function.(input), reduced_compute_function.(input))
end
end