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
Horovod CANDLE P1B2 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=160.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3054118606590065 0.0145175696084793 0.0072495875225558 0.0 0.0168351221481132 0.0052775229223777 0.0 0.0 0.050171685905693 0.0 0.0 0.0 0.0 0.0335546915521329 0.0033391294642726 0.0 0.4102870708237419 0.0083199748091844 0.0 0.0 0.0 0.0 0.0 0.0062318006615403 0.0670909781964424 0.0 0.1313144966321437 0.0083199748091844 0.0 0.2118143531734755 0.0 0.0 0.0072243861120394 0.0 0.0 0.0 0.0127157599869979 0.0199653475095537 0.0883100323763649 0.0416479232060306 0.0 0.0 0.0 1.91920145325e-09 135.546003 84.253394 9.731523 48 64 172671882588.884237027919205491
Horovod CANDLE P1B2 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=150.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3049524718473291 0.0145513339725187 0.0071869705529867 0.0 0.0166626192927306 0.0052873187998424 0.0 0.0 0.0501258372061477 0.0 0.0 0.0 0.0 0.0335317691417478 0.0033445552716551 0.0 0.410811351240639 0.0083394759974277 0.0 0.0 0.0 0.0 0.0 0.0062627790749883 0.0663785807679789 0.0 0.1312409304821482 0.0083394759974277 0.0 0.2104993415354 0.0 0.0 0.0072371461480614 0.0 0.0 0.0 0.0125853002497441 0.0197722708027308 0.0882378548966154 0.0415668679673133 0.0 0.0 0.0 2.00021871528e-09 128.35879 81.28098 12.987032 48 64 173324691620.770624749496069519
Horovod CANDLE P1B2 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=140.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3065770588259986 0.0146347503421334 0.0069690562498654 0.0 0.0164371626055302 0.0052651760601071 0.0 0.0 0.0503750351318493 0.0 0.0 0.0 0.0 0.0338946326030966 0.0033493533295154 0.0 0.4089022022800495 0.0083477263614333 0.0 0.0 0.0 0.0 0.0 0.0062211311624522 0.0664399368798377 0.0 0.128781351149892 0.0083477263614333 0.0 0.2105235194146454 0.0 0.0 0.0072759960938965 0.0 0.0 0.0 0.0124539544279584 0.0194230106778237 0.0874609552087451 0.0415604864392113 0.0 0.0 0.0 2.12215047667e-09 129.708564 83.227901 11.175414 48 64 170586515414.332491789049378656
Horovod CANDLE P1B2 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=120.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3056761822696445 0.0146728321975184 0.0069826149148928 0.0 0.0164292848166617 0.0052395494964612 0.0 0.0 0.0502439413937407 0.0 0.0 0.0 0.0 0.0338259414891006 0.0033387284524743 0.0 0.4117096851745656 0.0084349038173201 0.0 0.0 0.0 0.0 0.0 0.0062557400671794 0.0664788516057086 0.0 0.1298911562491885 0.0084349038173201 0.0 0.2111411257696675 0.0 0.0 0.0072966083233416 0.0 0.0 0.0 0.0125360150946239 0.0195186300095167 0.0879075430422089 0.0417851982345791 0.0 0.0 0.0 2.2848802739e-09 126.572519 78.103053 12.992366 48 64 171861440393.872534276772899055
Horovod CANDLE P1B2 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=130.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3082797598129191 0.014581102907735 0.0071986582126686 0.0 0.0167089481256868 0.0052799711051249 0.0 0.0 0.0505879138056188 0.0 0.0 0.0 0.0 0.0338252881442632 0.0033031512817837 0.0 0.4094545109547771 0.0083492311123262 0.0 0.0 0.0 0.0 0.0 0.0062721773110629 0.066550472889212 0.0 0.1295502226233996 0.0083492311123262 0.0 0.2094653901827941 0.0 0.0 0.0072739038895172 0.0 0.0 0.0 0.0127243796941819 0.0199230379068505 0.0894731363652624 0.0421980071783521 0.0 0.0 0.0 2.40501017152e-09 127.23601 77.726277 14.969586 48 64 171648815413.98795855018704682
Horovod CANDLE P1B2 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=110.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3111075167678652 0.0146366560334858 0.0072313263446297 0.0 0.0166411284422788 0.0052732019751689 0.0 0.0 0.0510190636965585 0.0 0.0 0.0 0.0 0.0341219631126575 0.0033425285137586 0.0 0.4050189484447274 0.0084040966539883 0.0 0.0 0.0 0.0 0.0 0.0063173838974315 0.066354053681191 0.0 0.1304224636345194 0.0084040966539883 0.0 0.2141486418174164 0.0 0.0 0.0071824840118999 0.0 0.0 0.0 0.0125953025738727 0.0198266289185024 0.088557382030618 0.0417542592940334 0.0 0.0 0.0 2.45914715267e-09 124.862768 80.371122 12.109785 48 64 170301573675.774057801170322676
Horovod CANDLE P1B2 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=90.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3057189839487132 0.0145458836265891 0.0071558663354763 0.0 0.0165243898117563 0.0052375842275023 0.0 0.0 0.0501524135144005 0.0 0.0 0.0 0.0 0.0335241701046903 0.0033305933945193 0.0 0.4104566988995668 0.008277989190639 0.0 0.0 0.0 0.0 0.0 0.0062515213697161 0.0659005224489801 0.0 0.1298187901458583 0.008277989190639 0.0 0.2096330851559405 0.0 0.0 0.0071629735460291 0.0 0.0 0.0 0.0125359283471411 0.0196917946826174 0.0879082556563212 0.0414134991922271 0.0 0.0 0.0 2.98044540859e-09 129.666667 75.823188 13.069565 48 64 173488019444.925215864747059524
Horovod CANDLE P1B2 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=90.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3057189839487132 0.0145458836265891 0.0071558663354763 0.0 0.0165243898117563 0.0052375842275023 0.0 0.0 0.0501524135144005 0.0 0.0 0.0 0.0 0.0335241701046903 0.0033305933945193 0.0 0.4104566988995668 0.008277989190639 0.0 0.0 0.0 0.0 0.0 0.0062515213697161 0.0659005224489801 0.0 0.1298187901458583 0.008277989190639 0.0 0.2096330851559405 0.0 0.0 0.0071629735460291 0.0 0.0 0.0 0.0125359283471411 0.0196917946826174 0.0879082556563212 0.0414134991922271 0.0 0.0 0.0 2.98044540859e-09 129.666667 75.823188 13.069565 48 64 173488019444.925215864747059524
Horovod CANDLE P1B2 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=70.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3085585017180468 0.0145726229382756 0.0071958759808113 0.0 0.0167055093160545 0.0052553173187298 0.0 0.0 0.0506179641801618 0.0 0.0 0.0 0.0 0.0338744161867639 0.0034040007842752 0.0 0.4104389644942734 0.0082871367660021 0.0 0.0 0.0 0.0 0.0 0.0062951425864102 0.0666920885672377 0.0 0.13057082367998 0.0082871367660021 0.0 0.210446150169023 0.0 0.0 0.0072903744099362 0.0 0.0 0.0 0.0128288301949124 0.0200247061757237 0.0880417633294096 0.0414986862297924 0.0 0.0 0.0 3.36439245172e-09 125.004314 76.479724 14.999137 48 64 172155397538.088256093455506214
Horovod CANDLE P1B2 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=100.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3369687588727657 0.0118791274272998 0.0056110700803169 0.0 0.0214886433591072 0.0048512888280774 0.0 0.0 0.0488169925252817 0.0 0.0 0.0 0.0 0.0268452254515525 0.0069756790607264 0.0 0.3691155162339044 0.0066151845668931 0.0 0.0 0.0 0.0 0.0 0.0052721519142106 0.071524678824573 0.0 0.1543371141484362 0.0066151845668931 0.0 0.2451396974159758 0.0 0.0 0.0060193380283895 0.0 0.0 0.0 0.0084514792164142 0.0140625492967311 0.1040657421826827 0.0496277611430539 0.0 0.0 0.0 3.13372051935e-09 127.717336 78.355252 11.838599 48 64 186772139501.898494341873863506
Horovod CANDLE P1B2 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=80.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3363151966576862 0.0119675328893486 0.006318018994422 0.0 0.0219140202053792 0.0048713847565047 0.0 0.0 0.0485631840902442 0.0 0.0 0.0 0.0 0.0271617208011064 0.0050366753630007 0.0 0.3669658061217815 0.0066235480888484 0.0 0.0 0.0 0.0 0.0 0.0050486913987626 0.0724215752459678 0.0 0.155553525770865 0.0066235480888484 0.0 0.2510032170629772 0.0 0.0 0.0066896094806554 0.0 0.0 0.0 0.0092796462796253 0.0155976652740473 0.1053566502520464 0.0505614028401767 0.0 0.0 0.0 3.5684006524e-09 126.037245 79.767393 12.720309 48 64 199215261750.914480916767360695
Horovod CANDLE P1B2 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=60.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.336344877903112 0.012075057948051 0.0062993847904081 0.0 0.021480775626711 0.0048263912527211 0.0 0.0 0.0484534839207042 0.0 0.0 0.0 0.0 0.0269522069698168 0.0070757831046148 0.0 0.3685488753207329 0.0066554922456972 0.0 0.0 0.0 0.0 0.0 0.0051209767608504 0.0739319931617227 0.0 0.1563853096847352 0.0066554922456972 0.0 0.2556804257438808 0.0 0.0 0.0060322890961313 0.0 0.0 0.0 0.0093011827899057 0.0156005675803138 0.1039313339658294 0.0478091136771568 0.0 0.0 0.0 3.8359915626e-09 126.053398 74.208738 15.869626 48 64 187819071872.950213980744379857
Horovod CANDLE P1B2 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=50.0, epochs=384.0 1.301 p1b2-hybrid.py empirical 1.301 1 0.3052075095946454 0.0146958835184862 0.0071666654288275 0.0 0.0167088469198685 0.0052441245379145 0.0 0.0 0.0500624981848328 0.0 0.0 0.0 0.0 0.0335194276228382 0.0033799739570605 0.0 0.4051247968494543 0.0083068024746309 0.0 0.0 0.0 0.0 0.0 0.0063510651346302 0.0668485696979414 0.0 0.1299314369692822 0.0083068024746309 0.0 0.2097524542615433 0.0 0.0 0.0072725837493035 0.0 0.0 0.0 0.0126562638704207 0.0198229292992482 0.0889311425912258 0.0419238582510361 0.0 0.0 0.0 4.22600160459e-09 136.721733 84.648612 14.98849 48 64 174790403580.943283969289156583
Horovod CANDLE NT3 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=70.0, epochs=48.0 1.301 nt3-hybrid-opt.py empirical 1.301 1 0.5988338265437401 0.0178809862848635 0.0020485194743175 0.0 0.0303881214553196 0.0010233867736137 0.0 0.0 0.1118295234367062 0.0 0.0 0.0 0.0 0.0811568433075185 0.0070325649666903 0.0 0.1729514662163626 0.005856923363513 0.0 0.0 0.0 0.0 0.0 0.0120828904326972 0.1435023638573317 0.0 0.2269212565297892 0.005856923363513 0.0 0.4243131524948982 0.0 0.0 0.0047045530830789 0.0 0.0 0.0 0.0173665570690781 0.0194150765433955 0.1573315821371322 0.063067546131056 0.0 0.0 0.0 4.93508573584e-09 145.377736 92.479675 11.290807 48 64 161959008573.121462255321481605
Horovod CANDLE NT3 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=60.0, epochs=48.0 1.301 nt3-hybrid-opt.py empirical 1.301 1 0.5934407982532376 0.018157988890312 0.0020715366893799 0.0 0.0304324237249753 0.0010302375906238 0.0 0.0 0.110879723240975 0.0 0.0 0.0 0.0 0.0804610512262361 0.007043435922605 0.0 0.1747196840224087 0.0059276751416822 0.0 0.0 0.0 0.0 0.0 0.0121116188341126 0.1435627450905299 0.0 0.2240737154365659 0.0059276751416822 0.0 0.4256897224543398 0.0 0.0 0.0047635811576625 0.0 0.0 0.0 0.01721031276324 0.0192818494526199 0.1574878993621391 0.0631739991460381 0.0 0.0 0.0 4.91342961188e-09 140.332296 89.924704 13.433727 48 64 163397021921.071867922492714474
Horovod CANDLE NT3 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=40.0, epochs=48.0 1.301 nt3-hybrid-opt.py empirical 1.301 1 0.5931891220701542 0.0180245649543554 0.0020924633075722 0.0 0.0304716845743293 0.0010333199635191 0.0 0.0 0.1107459390896013 0.0 0.0 0.0 0.0 0.0803481944951751 0.0070598286928164 0.0 0.1764002478547367 0.0058642816069364 0.0 0.0 0.0 0.0 0.0 0.0121234294526632 0.1438994013491842 0.0 0.2215591888659695 0.0058642816069364 0.0 0.4242126273868149 0.0 0.0 0.0046743453553785 0.0 0.0 0.0 0.0170899775986623 0.0191824409062345 0.159688950709373 0.0640840237606982 0.0 0.0 0.0 5.0135001584e-09 141.230299 88.61515 15.007941 48 64 163238928322.121023990431794139
Horovod CANDLE NT3 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=50.0, epochs=48.0 1.301 nt3-hybrid-opt.py empirical 1.301 1 0.5919288868234271 0.0182115756655911 0.0020681614396801 0.0 0.0305567714213076 0.0010212145223891 0.0 0.0 0.1105245823907014 0.0 0.0 0.0 0.0 0.0801419398986639 0.0070927442992823 0.0 0.1772509273578399 0.0059628712997555 0.0 0.0 0.0 0.0 0.0 0.0120807325585382 0.1443525523920886 0.0 0.2242880544609162 0.0059628712997555 0.0 0.4252091262676138 0.0 0.0 0.0047820820974952 0.0 0.0 0.0 0.0171981941602576 0.0192663555999377 0.1591312589234601 0.0638080413503468 0.0 0.0 0.0 5.0052284676e-09 138.989018 86.894448 13.059182 48 64 163688777705.856265636972019686
Horovod CANDLE NT3 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=30.0, epochs=48.0 1.301 nt3-hybrid-opt.py empirical 1.301 1 0.5915065342262094 0.0181708809557959 0.0020328758350372 0.0 0.0305141038610341 0.0010205760760763 0.0 0.0 0.1105221635169846 0.0 0.0 0.0 0.0 0.0801792839613328 0.0070673478390416 0.0 0.1693471304688576 0.0060046155249861 0.0 0.0 0.0 0.0 0.0 0.0122572899897166 0.14411486631912 0.0 0.2241860314397411 0.0060046155249861 0.0 0.4342326034066101 0.0 0.0 0.0048151150611101 0.0 0.0 0.0 0.0174054871051697 0.0194383629402069 0.1581061265965918 0.0634487400981296 0.0 0.0 0.0 5.17949586698e-09 134.661376 86.720752 11.981775 48 64 164077270611.958873373542394115
Horovod CANDLE NT3 Benchmark ANL Theta 48 48 64 learning rate=0.001, batch size=10.0, epochs=48.0 1.301 nt3-hybrid-opt.py empirical 1.301 1 0.5886788448047798 0.0181660179808881 0.0020764826601162 0.0 0.0301219927477103 0.0010178547188455 0.0 0.0 0.1099932476979878 0.0 0.0 0.0 0.0 0.0798167668542246 0.0071088022687494 0.0 0.1705832973224553 0.0059094116824947 0.0 0.0 0.0 0.0 0.0 0.0122078087291326 0.1422600533677073 0.0 0.224289929152717 0.0059094116824947 0.0 0.4282266340362988 0.0 0.0 0.0048633737515441 0.0 0.0 0.0 0.0172750934259042 0.0193515760860203 0.1582057534874548 0.0632805429444456 0.0 0.0 0.0 7.23196964868e-09 139.04097 90.394649 12.067726 48 64 165247929963.053324975061308362