MuMMI

Create Training Set

Train application_name system_name processors num_mpi num_omppn input frequency executable_name scenario frequency papi_tot_cyc papi_tot_ins papi_l1_tcm papi_l2_tcm papi_fml_ins papi_br_tkn papi_l2_ldm papi_l2_stm papi_fdv_ins papi_br_cn papi_tot_iis papi_ca_shr papi_ca_cln papi_ca_itv papi_br_ntk papi_br_msp papi_fp_ins papi_res_stl papi_l1_ldm papi_l1_stm papi_l2_tcw papi_l2_dca papi_l2_dcr papi_l2_dcw papi_l1_icm papi_br_ins papi_l1_dch papi_l1_dca papi_l1_dcm papi_l1_tca papi_l1_ica papi_fp_ops papi_l2_ica papi_tlb_dm papi_vec_ins papi_l2_dcm papi_l2_icm papi_l2_tch papi_l2_tca papi_ld_ins papi_sr_ins papi_tlb_im papi_hw_int papi_l3_tcm nruntime power_sys power_cpu power_mem num_mpi num_omppn scaling_factor
STREAM_PC ANL Theta 128 128 1 STREAM array size=256000000.0, NTIMES=5000.0 1.301 stream_mpic empirical 1.301 1 0.1017051527380434 0.0340496086369086 0.0 0.0 0.0 0.0372409503717281 0.0238567984331316 0.0 0.0030699511989156 0.0 0.0 0.0 0.0 0.0112299410051187 0.0100880671778137 0.0 0.0014495003873248 0.0298540432341629 0.5308578249946067 0.0573197659389503 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.000204482581282 0.0 0.0 0.0 0.0125999442897648 0.0298701898508192 0.0 0.001090082115513 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.3168119431e-10 280.427245 199.767802 14.987616 128 1 221661256652.832613923
Horovod CANDLE P1B2 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=150.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3252382968908034 0.0131219141362303 0.0047459743246804 0.0 0.0179823057654572 0.0031155533268163 0.0 0.0 0.0545706635474669 0.0 0.0 0.0 0.0 0.0367393026237473 0.0036424795406712 0.0 0.4508917772961848 0.0063555991438856 0.0 0.0 0.0 0.0 0.0 0.0067757354366294 0.07267964003631 0.0 0.13806781986361 0.0063555991438856 0.0 0.2298529579673502 0.0 0.0 0.0052667015954571 0.0 0.0 0.0 0.0122179615068439 0.0169639358315243 0.0940560436148056 0.042781755158859 0.0 0.0 0.0 1.22968289832e-09 120.5625 71.026442 13.387019 128 64 158045477631.279090260219827109
Horovod CANDLE P1B2 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=160.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3271508657985925 0.0132097401877493 0.0048308929859674 0.0 0.0179728993002102 0.0031336403595112 0.0 0.0 0.0549761232478651 0.0 0.0 0.0 0.0 0.036992445789117 0.003658018096684 0.0 0.4493929133473596 0.0063953526688548 0.0 0.0 0.0 0.0 0.0 0.0067892726200071 0.0726241396623296 0.0 0.1379301839018817 0.0063953526688548 0.0 0.2279531359670535 0.0 0.0 0.0053176600335992 0.0 0.0 0.0 0.0123423737729066 0.017173266758874 0.0943807265657525 0.042955268485635 0.0 0.0 0.0 1.27589208919e-09 131.255 77.5925 14.98 128 64 156497888568.901849482279099387
Horovod CANDLE P1B2 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=130.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3264087673760617 0.0132565749957026 0.0047865336431633 0.0 0.0179416150748184 0.0031062467614675 0.0 0.0 0.0548188003054535 0.0 0.0 0.0 0.0 0.0368485995170257 0.0036526821579981 0.0 0.4467235542521911 0.0064683907709213 0.0 0.0 0.0 0.0 0.0 0.0068062671629902 0.0726180719155417 0.0 0.137926402466394 0.0064683907709213 0.0 0.2302424555649897 0.0 0.0 0.0053158067652488 0.0 0.0 0.0 0.0123262894630338 0.0171128231061971 0.0944042488714837 0.0430048590898221 0.0 0.0 0.0 1.36224292845e-09 133.355972 82.653396 14.0 128 64 156534211003.486747444822090976
Horovod CANDLE P1B2 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=140.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3242218304497985 0.0130204281156801 0.0047282310863035 0.0 0.0179336483939485 0.0031062639682035 0.0 0.0 0.0544542982882046 0.0 0.0 0.0 0.0 0.0366334314104145 0.0036308621918978 0.0 0.4439554033107188 0.0063315606375854 0.0 0.0 0.0 0.0 0.0 0.0067873706397494 0.0723919805601651 0.0 0.1370836666051734 0.0063315606375854 0.0 0.2280913353388118 0.0 0.0 0.0053702999386 0.0 0.0 0.0 0.012262973181734 0.0169912042680375 0.0952059960003501 0.0432321329609515 0.0 0.0 0.0 1.37091041735e-09 124.210162 75.032333 11.420323 128 64 157741312826.270938249647257303
Horovod CANDLE P1B2 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=110.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3295540785360592 0.0141724161580233 0.0046537699601044 0.0 0.0180535615314078 0.003101860045176 0.0 0.0 0.0553895710337694 0.0 0.0 0.0 0.0 0.0372712722399527 0.0036487959803772 0.0 0.4455408958623408 0.0072445216728519 0.0 0.0 0.0 0.0 0.0 0.0068519552061489 0.0729563993775971 0.0 0.137519206210265 0.0072445216728519 0.0 0.2309904982437261 0.0 0.0 0.0053146132804923 0.0 0.0 0.0 0.0124051368220508 0.0170589067821553 0.0956679404470111 0.0436099061573007 0.0 0.0 0.0 1.50989801903e-09 125.095949 79.03838 11.053305 128 64 155097705969.867272751818864277
Horovod CANDLE P1B2 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=120.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3236979652087738 0.0131512098546944 0.0047190417914497 0.0 0.0178543103436087 0.0031275335115326 0.0 0.0 0.0543401893744202 0.0 0.0 0.0 0.0 0.0365264168404698 0.0036352328779352 0.0 0.4492143582590077 0.0063604545485186 0.0 0.0 0.0 0.0 0.0 0.0067661289834074 0.0722392863249865 0.0 0.1366324748859639 0.0063604545485186 0.0 0.2286208660629281 0.0 0.0 0.0053826778757128 0.0 0.0 0.0 0.0122794672599474 0.0169985090513971 0.0947688982259065 0.043122105203621 0.0 0.0 0.0 1.48728778021e-09 128.770878 77.561028 15.012848 128 64 157777769119.347345464599364525
XSBench ANL Theta 128 2 64 gridpoints=100000.0, threads per node=64.0 1.301 XSBench empirical 1.301 1 0.4757729186928262 0.0057462438294075 0.0 0.0 0.0 0.1139954497389149 0.05924890803067 0.0 0.0011248926897195 0.0 0.0 0.0 0.0 0.0472357349282028 0.0193965359206253 0.0 0.028493958000273 0.0032304172964316 0.2519633348812865 0.0100986216579094 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0023900728577072 0.0 0.0 0.0 0.0701681785742442 0.0031771933514231 0.0 0.0039732068003202 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.15710406679e-09 0.0 0.0 0.0 2 64 208774077400.112151065513065666
FTLA-rSC13 ANL Theta 128 128 1 max matrix size=20000.0, min matrix size=6000.0, stride size=2000.0, block size=100.0, number of failure injetions=1.0 1.301 testing_ftdqr.x empirical 1.301 1 1.124213933743154 0.0034351580211545 0.0 0.0 0.0 0.5155924717785946 0.0989240820574683 0.0 0.0003103793179931 0.0 0.0 0.0 0.0 0.0977428956679554 0.0322084539418683 0.0 0.0663277496225295 0.0024272629519054 0.12938853774245 0.0653360655322372 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0010010552861943 0.0 0.0 0.0 0.1353974436297948 0.0024545468942365 0.0 0.0026984504371839 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.3948799758e-10 246.527344 174.339844 11.205078 128 1 346472375262.969984822
Horovod CANDLE P1B2 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=70.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3256787185251208 0.0131625034183939 0.0047556574334039 0.0 0.0180191738840755 0.0031260003204027 0.0 0.0 0.0547279487546131 0.0 0.0 0.0 0.0 0.0368149445699989 0.003661186105721 0.0 0.4436501519805199 0.0063639109456352 0.0 0.0 0.0 0.0 0.0 0.0068542311206787 0.0730342862248883 0.0 0.1378047000271116 0.0063639109456352 0.0 0.2299684755458726 0.0 0.0 0.0052138611237617 0.0 0.0 0.0 0.0122270112559019 0.0169826686893058 0.0951758940283858 0.0433253060485689 0.0 0.0 0.0 1.73620979838e-09 128.738574 82.744059 12.985375 128 64 157239177693.114891911591631897
Horovod CANDLE P1B2 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=90.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3263710862308098 0.0132682545430009 0.0048297133414434 0.0 0.0179204461397311 0.0030959116908776 0.0 0.0 0.0548148465372684 0.0 0.0 0.0 0.0 0.0368965920871234 0.0036986104734028 0.0 0.4472858664187635 0.0063908683201855 0.0 0.0 0.0 0.0 0.0 0.0068219849633412 0.072432868081752 0.0 0.1361496589766882 0.0063908683201855 0.0 0.2319674643145147 0.0 0.0 0.0053380396967777 0.0 0.0 0.0 0.0123549640869159 0.0171846774283593 0.094051862944273 0.0428123406953861 0.0 0.0 0.0 1.7870870462e-09 125.448214 74.5125 13.008929 128 64 156737397652.566566961443178974
Horovod CANDLE P1B2 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=90.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3263710862308098 0.0132682545430009 0.0048297133414434 0.0 0.0179204461397311 0.0030959116908776 0.0 0.0 0.0548148465372684 0.0 0.0 0.0 0.0 0.0368965920871234 0.0036986104734028 0.0 0.4472858664187635 0.0063908683201855 0.0 0.0 0.0 0.0 0.0 0.0068219849633412 0.072432868081752 0.0 0.1361496589766882 0.0063908683201855 0.0 0.2319674643145147 0.0 0.0 0.0053380396967777 0.0 0.0 0.0 0.0123549640869159 0.0171846774283593 0.094051862944273 0.0428123406953861 0.0 0.0 0.0 1.7870870462e-09 125.448214 74.5125 13.008929 128 64 156737397652.566566961443178974
Horovod CANDLE P1B2 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=100.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3643569306503415 0.0106141323685604 0.0042784459320556 0.0 0.0236074499967139 0.0028382162937991 0.0 0.0 0.0534826656085989 0.0 0.0 0.0 0.0 0.030196399333315 0.0074405673782666 0.0 0.4011144925675496 0.004848950466348 0.0 0.0 0.0 0.0 0.0 0.0057621088037817 0.0783560493883321 0.0 0.1655137305975324 0.004848950466348 0.0 0.2709860830635727 0.0 0.0 0.0042817147608889 0.0 0.0 0.0 0.0087515975762614 0.013030043508317 0.1116719020893594 0.0500921917727075 0.0 0.0 0.0 1.53850886542e-09 120.537543 70.716724 12.614334 128 64 190345568740.063685709846886064
Horovod CANDLE P1B2 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=80.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3563238532961072 0.0105393185099521 0.0038057821929723 0.0 0.0227674144999137 0.0028356982414609 0.0 0.0 0.0523023161486271 0.0 0.0 0.0 0.0 0.0290472894184552 0.0053526751617059 0.0 0.3764422694328899 0.0048006481988295 0.0 0.0 0.0 0.0 0.0 0.0056434458275587 0.0784619864024336 0.0 0.1615696981953444 0.0048006481988295 0.0 0.2581274684563032 0.0 0.0 0.0048018722180091 0.0 0.0 0.0 0.0078379245501774 0.0116437067431497 0.1119142526989414 0.0543180011955216 0.0 0.0 0.0 1.72180390758e-09 125.787879 80.377104 13.074074 128 64 172273122214.538910972262901037
STREAM_PC ANL Theta 128 128 1 STREAM array size=512000000.0, NTIMES=5000.0 1.301 stream_mpic empirical 1.301 1 0.1009250905461435 0.0294146867075393 0.0 0.0 0.0 0.0374693980748886 0.0240591894978908 0.0 0.0031295729133981 0.0 0.0 0.0 0.0 0.0117094642947667 0.0103888956312627 0.0 0.0034652018899543 0.0300497694151147 0.5529272478110494 0.0576719091823662 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0001113806843866 0.0 0.0 0.0 0.0117048701629697 0.0286729469179797 0.0 0.0011764842834069 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.2833500862e-10 275.77193 203.642743 13.07177 128 1 430584458097.389211284
FTLA-rSC13 ANL Theta 128 128 1 max matrix size=20000.0, min matrix size=6000.0, stride size=2000.0, block size=100.0, number of failure injetions=2.0 1.301 testing_ftdqr.x empirical 1.301 1 1.116348303176214 0.0035231463405653 0.0 0.0 0.0 0.511729965634646 0.0998236003611127 0.0 0.0003173009712829 0.0 0.0 0.0 0.0 0.098536315196138 0.0324214612657938 0.0 0.0658939006348268 0.002484341827101 0.1307145456534369 0.0647759596397266 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0010300365502917 0.0 0.0 0.0 0.1357432117580438 0.0024887707723832 0.0 0.0025917574228578 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.3750751704e-10 247.263689 177.564841 12.108069 128 1 470720853657.646401798
Horovod CANDLE P1B2 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=50.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3219513293564553 0.0130881969316108 0.0048002716603894 0.0 0.017924760095704 0.0031137124357843 0.0 0.0 0.0540853998007578 0.0 0.0 0.0 0.0 0.0363986710984225 0.0036490096980751 0.0 0.4452324500131826 0.0062790369956747 0.0 0.0 0.0 0.0 0.0 0.0068640918834467 0.0725759167911072 0.0 0.1385196189354937 0.0062790369956747 0.0 0.2295601618613685 0.0 0.0 0.0052394796633953 0.0 0.0 0.0 0.0122594006319852 0.0170596722923746 0.0944656762662969 0.0428389080651211 0.0 0.0 0.0 2.30131391146e-09 128.51087 79.807065 12.452446 128 64 159694213018.877745797155717508
Horovod CANDLE P1B2 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=60.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3591371591780479 0.0105091103503541 0.0043226170335418 0.0 0.0232761901016075 0.0028151970456335 0.0 0.0 0.0527217023515247 0.0 0.0 0.0 0.0 0.0293157851033618 0.0054865672904712 0.0 0.4013207863676684 0.0047783869074931 0.0 0.0 0.0 0.0 0.0 0.0056695691020122 0.0780226023361764 0.0 0.1602267751626559 0.0047783869074931 0.0 0.2607463397905581 0.0 0.0 0.0047643562500145 0.0 0.0 0.0 0.0086886229616568 0.0130112399951986 0.1114437193372071 0.0499512898717667 0.0 0.0 0.0 2.16146864255e-09 128.278378 78.725676 12.109459 128 64 171148447272.208149851236896909
FTLA-rSC13 ANL Theta 128 128 1 max matrix size=20000.0, min matrix size=6000.0, stride size=2000.0, block size=100.0, number of failure injetions=3.0 1.301 testing_ftdqr.x empirical 1.301 1 1.109641488161476 0.0035803351103805 0.0 0.0 0.0 0.506724840205058 0.0993661613707114 0.0 0.0003265432285186 0.0 0.0 0.0 0.0 0.0971761704384084 0.0320210801215931 0.0 0.065979256717506 0.0028780960803083 0.1268700229540454 0.0638862397499102 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0010634567676526 0.0 0.0 0.0 0.1357480169109469 0.0025281345435541 0.0 0.0027012837686283 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.3687500609e-10 246.104612 174.344207 11.069741 128 1 603108431317.482141851
FTLA-rSC13 ANL Theta 128 128 1 max matrix size=20000.0, min matrix size=6000.0, stride size=2000.0, block size=100.0, number of failure injetions=4.0 1.301 testing_ftdqr.x empirical 1.301 1 1.106202004646121 0.0036579888702638 0.0 0.0 0.0 0.5017314416907989 0.0986755279115959 0.0 0.0003290908984133 0.0 0.0 0.0 0.0 0.0981503377474366 0.0323566931558585 0.0 0.0649395949077002 0.0025498445730591 0.1269615309229561 0.063427216692206 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0010846889745108 0.0 0.0 0.0 0.1357001021801694 0.002548610262225 0.0 0.0023541843402166 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.3591567015e-10 246.828837 173.669767 12.368372 128 1 730843430593.580763691
FTLA-rSC13 ANL Theta 128 128 1 max matrix size=20000.0, min matrix size=6000.0, stride size=2000.0, block size=100.0, number of failure injetions=5.0 1.301 testing_ftdqr.x empirical 1.301 1 1.101483530228381 0.0040987301021905 0.0 0.0 0.0 0.4965111048236181 0.1004068170427689 0.0 0.0003219056816211 0.0 0.0 0.0 0.0 0.0988246274553314 0.032763440732495 0.0 0.0659940766888215 0.0025405098136526 0.1295909171769115 0.0610047855988251 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0011005905419291 0.0 0.0 0.0 0.1363286594204992 0.0025375991713907 0.0 0.0019708038290144 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.3576436293e-10 250.213509 178.771739 11.641304 128 1 876370219172.120891838
Horovod CANDLE NT3 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=70.0, epochs=128.0 1.301 nt3-hybrid-opt.py empirical 1.301 1 0.5889426989638944 0.0181733538908182 0.0020926102561664 0.0 0.0300779928337772 0.001022500276392 0.0 0.0 0.1099929178601383 0.0 0.0 0.0 0.0 0.0797773686090857 0.0070845582834634 0.0 0.1744511169949059 0.0059253921785077 0.0 0.0 0.0 0.0 0.0 0.0120762501906897 0.1419462056574483 0.0 0.2237019770821643 0.0059253921785077 0.0 0.4283899777992187 0.0 0.0 0.0046434175872291 0.0 0.0 0.0 0.0172627475685928 0.0193553578247592 0.1576647858393212 0.0630073247932225 0.0 0.0 0.0 4.81802912012e-09 136.466877 91.239748 15.24164 128 64 164401871855.077491805900646151
Horovod CANDLE NT3 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=60.0, epochs=128.0 1.301 nt3-hybrid-opt.py empirical 1.301 1 0.5945187558133437 0.0180564788501563 0.0020238860586597 0.0 0.0303325072079261 0.0010255044365796 0.0 0.0 0.1110415604734947 0.0 0.0 0.0 0.0 0.080522945857066 0.0070307253301712 0.0 0.1767318528186164 0.0059058502551593 0.0 0.0 0.0 0.0 0.0 0.0122538599691907 0.1431365238888439 0.0 0.2221711629820414 0.0059058502551593 0.0 0.4300160678436187 0.0 0.0 0.0046506435384235 0.0 0.0 0.0 0.0173544891246638 0.0193783751833236 0.1587190159691468 0.0636161172762152 0.0 0.0 0.0 5.00681689958e-09 139.2457 93.60688 13.159091 128 64 162852311629.050778925868315086
Horovod CANDLE NT3 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=50.0, epochs=128.0 1.301 nt3-hybrid-opt.py empirical 1.301 1 0.5873739831335535 0.0183041287297946 0.0020192552683697 0.0 0.0300441921739162 0.0010160554113278 0.0 0.0 0.1097728031627022 0.0 0.0 0.0 0.0 0.0796029753460057 0.0070844889934541 0.0 0.174980464455112 0.0060524048869086 0.0 0.0 0.0 0.0 0.0 0.012228386527379 0.1418702747718783 0.0 0.22231626964989 0.0060524048869086 0.0 0.4246028913373757 0.0 0.0 0.0046636291058412 0.0 0.0 0.0 0.0174871527272712 0.0195064079956409 0.1594509907634867 0.0639090766172227 0.0 0.0 0.0 4.95286580628e-09 137.763303 86.559021 11.718654 128 64 164791666668.034561591542204355
Horovod CANDLE NT3 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=40.0, epochs=128.0 1.301 nt3-hybrid-opt.py empirical 1.301 1 0.5959042974661707 0.0181343265353894 0.002037564182922 0.0 0.0305278815772389 0.0010129596021141 0.0 0.0 0.1113281261166685 0.0 0.0 0.0 0.0 0.0807352164833725 0.0071047782296918 0.0 0.1746494734921178 0.0059385189894486 0.0 0.0 0.0 0.0 0.0 0.0121546176715895 0.1441306014692769 0.0 0.2274405142113707 0.0059385189894486 0.0 0.4322454666003031 0.0 0.0 0.0045785459455475 0.0 0.0 0.0 0.0173208953177355 0.0193584595006575 0.1595613130897308 0.0639001242232404 0.0 0.0 0.0 5.02350102674e-09 136.518315 83.42674 12.379731 128 64 162998791607.966697409430297968
Horovod CANDLE NT3 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=30.0, epochs=128.0 1.301 nt3-hybrid-opt.py empirical 1.301 1 0.5901682222773964 0.0180188042738794 0.0020701255495336 0.0 0.0301899920353206 0.001008744583543 0.0 0.0 0.110302429799285 0.0 0.0 0.0 0.0 0.0800000783040664 0.0071232091300076 0.0 0.1699851722272501 0.0058975318678979 0.0 0.0 0.0 0.0 0.0 0.0123810146285546 0.1424912669516961 0.0 0.224306872678967 0.0058975318678979 0.0 0.4246484207468067 0.0 0.0 0.0047043608676593 0.0 0.0 0.0 0.0172610093900184 0.019331134939552 0.158980210620787 0.0637712838429975 0.0 0.0 0.0 5.13871793651e-09 138.854772 89.218139 14.016598 128 64 164023665516.158412199481970123
Horovod CANDLE NT3 Benchmark ANL Theta 128 128 64 learning rate=0.001, batch size=10.0, epochs=128.0 1.301 nt3-hybrid-opt.py empirical 1.301 1 0.5863512055420886 0.0180561772655115 0.0020509441296691 0.0 0.0303091416318284 0.001022471321405 0.0 0.0 0.109564478809267 0.0 0.0 0.0 0.0 0.0794716531494765 0.0070974027978311 0.0 0.1743879725830543 0.0059080674795096 0.0 0.0 0.0 0.0 0.0 0.0121637373893777 0.1432628902256641 0.0 0.2227352767267587 0.0059080674795096 0.0 0.4279690581840662 0.0 0.0 0.0046254531146262 0.0 0.0 0.0 0.0175453064080063 0.0195962505376754 0.1579105101413002 0.0632955021342772 0.0 0.0 0.0 6.81305003542e-09 143.647241 96.02649 12.130243 128 64 165865849968.08060914430171863
HACC ANL Theta 128 128 1 nstep=3.0, nsub=5.0, ng/np=640.0 1.301 hacc_tpm empirical 1.301 1 0.64188415393594 0.0078330072083232 0.0 0.0 0.0 0.1867995328293444 0.0428050450911433 0.0 0.0003675774484724 0.0 0.0 0.0 0.0 0.0447922566582117 0.0222661807044786 0.0 0.0222907137690949 0.0077234824324863 0.0733789697334531 0.012372247912558 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0001901289833498 0.0 0.0 0.0 0.0631473833002213 0.0077041092122262 0.0 0.0082022154309355 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 8.0415951507e-10 197.105892 136.927895 12.097651 128 1 1525547945413.804677572
la-fti ANL Theta 128 128 1 max matrix size=50000.0, min matrix size=8000.0, stride size=2000.0, block size=100.0, Ckp L1=1.0, Ckp L2=2.0, Ckp L3=3.0, Ckp L4=4.0 1.301 testing_ftdqr.x empirical 1.301 1 1.151919076643876 0.0032923662788012 0.0 0.0 0.0 0.6504077190617236 0.0716777190419176 0.0 0.0002683138997076 0.0 0.0 0.0 0.0 0.0651230578375523 0.0226147785953807 0.0 0.0423363795078891 0.0025800266214359 0.1297303744237573 0.1013903240534058 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0007784722233272 0.0 0.0 0.0 0.087869261010905 0.0025544771138452 0.0 0.001975400878522 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.6645148133e-10 268.42853 182.649726 18.140918 128 1 2236327782974.186505119
la ANL Theta 128 128 1 max matrix size=50000.0, min matrix size=8000.0, stride size=2000.0, block size=100.0 1.301 testing_ftdqr.x empirical 1.301 1 1.152524865009888 0.0032724733142638 0.0 0.0 0.0 0.652540462710583 0.0721812518185639 0.0 0.0002765923384886 0.0 0.0 0.0 0.0 0.0655666501156871 0.0227953017104075 0.0 0.042843020778044 0.0025770902265444 0.129146663734662 0.1071788347352799 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0007642854446472 0.0 0.0 0.0 0.0898431086556223 0.0025603994740603 0.0 0.0012971125222128 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.6216513091e-10 268.044889 183.104547 18.074428 128 1 2281429330050.692964206
Nek5000-flat ANL Theta 128 128 1 domain dimension=2.0, Iters=100000.0 1.301 nek5000 empirical 1.301 1 0.4250434682100561 0.0309313968015339 0.0 0.0 0.0 0.1536597998721138 0.0518342372462836 0.0 0.0013383720872717 0.0 0.0 0.0 0.0 0.0464201667168396 0.0218462489792299 0.0 0.0219568418125471 0.0208504502591668 0.08789841547413 0.0321533196139961 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0107030484157608 0.0 0.0 0.0 0.0570292713698976 0.0205534206093032 0.0 0.001925737587021 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.853617013e-10 199.552548 139.764597 12.994692 128 1 2398731001119.165473113
Nek5000-cache ANL Theta 128 128 1 domain dimension=2.0, Iters=100000.0 1.301 nek5000 empirical 1.301 1 0.4207600759840912 0.0308645211623507 0.0 0.0 0.0 0.1477263648919038 0.0495222648838758 0.0 0.0013264105265997 0.0 0.0 0.0 0.0 0.0432137511481487 0.0212300529939244 0.0 0.0222300549786663 0.0200633892552985 0.0896628380219373 0.0317024502064306 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0105729533544923 0.0 0.0 0.0 0.0567257291818264 0.0201783123804056 0.0 0.0019469506254319 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.9749367208e-10 189.080742 131.909328 11.892083 128 1 2407434306020.932609379
Nekbone-ori-cache ANL Theta 128 128 1 Element size=256.0, Iters=1000.0 1.301 nekbone empirical 1.301 1 0.7486750277202926 0.0006084869490753 0.0 0.0 0.0 0.2495548530481638 0.0167703008101362 0.0 2.53195641257e-05 0.0 0.0 0.0 0.0 0.0059002816310905 0.0054176064824524 0.0 0.0004825524800208 0.0005580250347513 0.5225856642541049 0.0018360580279997 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.33143219253e-05 0.0 0.0 0.0 0.0061303426516076 0.0005576043251519 0.0 3.01453302668e-05 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.1906100278e-10 178.729295 129.537151 12.746805 128 1 2938952078933.099167617
Nekbone-ori-flat ANL Theta 128 128 1 Element size=256.0, Iters=1000.0 1.301 nekbone empirical 1.301 1 0.7491811970471178 0.0006079384539845 0.0 0.0 0.0 0.2500380271241561 0.0168559843794206 0.0 2.60070290083e-05 0.0 0.0 0.0 0.0 0.0059204582317926 0.0054263444971038 0.0 0.0004688812811926 0.0005545352442648 0.5226007438975728 0.0018406464163381 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.32401104753e-05 0.0 0.0 0.0 0.0061521792233772 0.0005614113356183 0.0 3.11132071517e-05 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.1945335812e-10 171.016327 119.983199 14.065073 128 1 2937363194081.465968653
Nekbone-fti ANL Theta 128 128 1 Element size=256.0, Iters=1000.0, ckp L1=5.0, ckp L2=8.0, ckp L3=9.0, ckp L4=10.0 1.301 nekbone empirical 1.301 1 0.7501314524815855 0.0006785044637304 0.0 0.0 0.0 0.2497258536648154 0.0170047510491476 0.0 2.60537439628e-05 0.0 0.0 0.0 0.0 0.0061168685056848 0.0055001368457375 0.0 0.0006339644138042 0.0006176484602449 0.5255008439611727 0.0018424816491294 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.73221802467e-05 0.0 0.0 0.0 0.0063899852560703 0.0006164858805693 0.0 6.11534841624e-05 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.2785760468e-10 172.233155 120.165773 11.008627 128 1 2953058208335.926677125
Nekbone-fti ANL Theta 128 128 1 Element size=256.0, Iters=1000.0, ckp L1=4.0, ckp L2=6.0, ckp L3=8.0, ckp L4=10.0 1.301 nekbone empirical 1.301 1 0.7501793074329132 0.0006777145804903 0.0 0.0 0.0 0.2499460390236154 0.0170355304790859 0.0 2.9328658982e-05 0.0 0.0 0.0 0.0 0.0060760115022811 0.0054801840863429 0.0 0.0006140007278292 0.0006199911606948 0.5239801295223466 0.0018506331673506 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.6445610531e-05 0.0 0.0 0.0 0.0063543419959017 0.0006143716263528 0.0 9.06872816832e-05 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.270871162e-10 172.355644 120.064366 10.940065 128 1 2956420728831.503396126
Nekbone-fti ANL Theta 128 128 1 Element size=256.0, Iters=1000.0, ckp L1=3.0, ckp L2=5.0, ckp L3=7.0, ckp L4=11.0 1.301 nekbone empirical 1.301 1 0.750255201725396 0.0006784727491675 0.0 0.0 0.0 0.2495503588578142 0.0171172924656001 0.0 2.88470808233e-05 0.0 0.0 0.0 0.0 0.0061912041755026 0.0055267006064172 0.0 0.0006586456406164 0.0006180987619632 0.5235688680649109 0.0018588732815445 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.78614181897e-05 0.0 0.0 0.0 0.0065266161194981 0.0006190390723533 0.0 6.17651392944e-05 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.2855407933e-10 180.594287 127.57385 10.706224 128 1 2960448584658.946047933
Nekbone-fti ANL Theta 128 128 1 Element size=256.0, Iters=1000.0, ckp L1=2.0, ckp L2=4.0, ckp L3=6.0, ckp L4=8.0 1.301 nekbone empirical 1.301 1 0.7502720704998845 0.0006741081120442 0.0 0.0 0.0 0.249709901289269 0.0170082710351406 0.0 2.67918657324e-05 0.0 0.0 0.0 0.0 0.0061317535077677 0.0055031978344324 0.0 0.000705891130947 0.0006195083850467 0.5233278575824302 0.001852699549348 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.72093745609e-05 0.0 0.0 0.0 0.006457553718309 0.000618873792366 0.0 7.08825750932e-05 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.3026882557e-10 181.298559 122.304833 13.01789 128 1 2957103045326.42655828
Nekbone-fti ANL Theta 128 128 1 Element size=256.0, Iters=1000.0, ckp L1=1.0, ckp L2=2.0, ckp L3=3.0, ckp L4=4.0 1.301 nekbone empirical 1.301 1 0.7525607184712739 0.0006799582284757 0.0 0.0 0.0 0.2495862535071235 0.0173814415843765 0.0 2.77360629758e-05 0.0 0.0 0.0 0.0 0.0065823334830505 0.0056454699316376 0.0 0.0008841487277893 0.0006215544410269 0.5236971092271867 0.001866790930771 0.0 0.0 0.0 0.0 0.0 0.0 0.0 6.08756946038e-05 0.0 0.0 0.0 0.007033305102993 0.0006234317479296 0.0 8.95819623418e-05 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.4209235858e-10 178.323905 127.703923 13.418339 128 1 2977043095050.057104713
OpenMC ANL Theta 128 2 64 Particles size=4000000.0, batch size=100.0, inactive size=20.0 1.301 openmc empirical 1.301 1 0.0787143935098503 0.0036726532382459 0.0 0.0 0.0 0.0182023868040132 0.0170056245808573 0.0 9.03437911223e-05 0.0 0.0 0.0 0.0 0.0062442572162669 0.0029329368185625 0.0 0.003875422329119 0.0010219367935032 0.015932949115584 0.0096987025827494 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0025834079479233 0.0 0.0 0.0 0.0090341491866275 0.0010462129026034 0.0 0.0012472019927431 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.1835537233e-10 163.494652 107.581538 12.026667 2 64 4759811619295.946694239