Isbarbar-dhigga Xogta
Isbarbardhigga xogtu waxay si dhakhso leh u tababartaa hal moodal iyadoo ku soo celinaysa GPU-yo badan, iyadoo GPU kastaa uu farsameeyo jeex ka duwan dufcada xogta.
Dulmar
It is the workhorse technique that lets teams scale to dozens or thousands of accelerators.
quusid qoto dheer
Marka la eego xogta isku midka ah, GPU kastaa wuxuu hayaa koobi isku mid ah oo miisaannada moodeelka laakiin wuxuu farsameeyaa qayb yar oo tusaalooyin tababar ah. Qalab kastaa wuxuu si madaxbanaan u xisaabiyaa baaska hore iyo kan dambe, isagoo soo saaraya jaanis u gaar ah. Kahor cusboonaysiinta miisaannada, gradients-yada ayaa celcelis ahaan lagu qiyaasaa dhammaan GPU-yada iyadoo la adeegsanayo hawlgal isgaarsiineed oo dhan-yar, marka nuqul kastaa wuu sii socdaa oo wuxuu u dhaqmaa sidii isagoo loo tababaray hal dufcadood oo weyn oo la isku daray. Tani waxay si wax ku ool ah u dhufataa wax-soo-saarka: 8 GPU-yadu waxay calalin karaan qiyaastii 8x xogta tallaabo kasta. Qabashada ayaa ah in GPU kastaa uu ku habboon yahay moodelka oo dhan, gradients-yadiisa, iyo xaaladda hagaajinta ee xusuusta, markaa isbarbardhigga xogta cad ma caawinayso marka moodalku aad ugu weyn yahay hal qalab.
Aragtida Farsamada
Hawlgalka muhiimka ah waa-dhammaan-dhimista, kaas oo soo koobaya jaangooyooyinka qalabka oo dib u qaybiya natiijada. Garaac-dhammaan-yar-yar, oo ay adeegsadaan maktabadaha sida NCCL iyo Horovod, waxay ku dhaafaan jajabyo jajaban oo ku wareegsan giraanta macquulka ah si wadarta isgaarsiintu ay uga madax bannaan tahay tirinta GPU-ga. PyTorch's DistributedDataParallel waxa uu ku dul wareegayaa isgaadhsiintan iyo kaarka danbe, isaga oo ka saaraya isku xidhka isku xidhka lakabyada hore halka lakabyada danbe ay wali ku jiraan xisaabinta, iyaga oo qarinaya daahitaanka shabakada.
Saamaynta Istiraatijiyadeed
Qiimaha iyo miisaaniyada
Go'aamada qaab-dhismeedku waxay horseedaan waxqabadka iyo kharashka hawlgalka sannadaha.
Go'aamo cad
Waxbarashada farsamada waxay ka caawisaa kooxaha inay doortaan xidhmo sax ah, ma aha oo kaliya kan ugu cusub.
Xakamaynta tayada
Doorashooyinka injineernimada ee wanaagsan waxay yareeyaan shilalka la isku halleyn karo ee wax soo saarka.
Mustaqbalka Isbarbar-dhigga Xogta
Isbarbar yaaca xogta saafiga ah ayaa si isa soo taraysa loogu daraa jeexjeexid iyo isbarbardhigga moodeelka isbarbardhigga 'nD barbar-dhigga' ee moodooyinka cabbirka-trillion-ka. Filo is riixis xariif ah oo xariif ah, isgaarsiin aan isku mid ahayn iyo isgaarsiin is dulsaaran, iyo topology-og dhammaan-yaraynta ka faa'iidaysanaysa dhaqsaha badan NVLink gudaha qandhicirka iyo gaabiska InfiniBand ee qanjidhada. Marka ay kooxuhu koraan, dhimista saamiga isgaadhsiinta-ilaa- xisaabinta ayaa ah caqabadda dhexe ee injineernimada ee kumanaanka GPU-yada lagu mashquulinayo.
Dhaqangelinta Adduunka-dhabta ah
Tababarka kala-soocida sawirka ResNet ee guud ahaan 8 GPU-yada hal server ah iyadoo la adeegsanayo PyTorch DistributedDataParallel, GPU kastaa wuxuu gacanta ku hayaa 32 ka mid ah 256-sawir.
Kordhinta tababbarka BERT ee boqollaal GPU-yada Horovod, iyadoo la isticmaalayo giraan-yaraynta si loo waafajiyo jaangooyooyinka tallaabo kasta.
Hagaajinta qaabka talo bixinta ee kutlada qanjirada badan leh halkaas oo nood kasta ay ka shaqeyso jeexjeexyada isdhexgalka isticmaale ee kala duwan.
Isticmaalka TensorFlow's Strategy Mirrored si loo faafiyo tababbarka qaabka aragga ee GPU-yada badan ee hal goob shaqo oo leh isbeddello kood ah.
Khatarta & Dariiqyada Ilaalada
Hagaajinta hal bartilmaameed waxay qarin kartaa daciifnimada nidaamka ballaaran.
Kaabayaasha dhaqaalaha iyo dayactirka inta badan waa la dhayalsadaa.
Nabadgelyada iyo daldaloolada u fiirsashada ayaa kori kara marka nidaamyadu noqdaan kuwo aad u adag.
Qorshe Hawleedka Dhaqangelinta
Qeex daahida, tayada, iyo bartilmaameedyada qiimaha ka hor inta aan la hirgelin.
Benchmark marka la eego culeyska dhabta ah iyo xaaladaha xogta.
La socodka qalabka khaladaadka, leexashada, iyo saamaynta isticmaalaha.
U diyaari dib-u-noqoshada iyo dariiqyada jawaab-celinta dhacdada ka hor inta aanad miisaan.
Sii wad Sahaminta
Free newsletter
Get the daily AI briefing
Three verified AI stories every weekday morning, written in plain English. Free forever, no ads.
One email each weekday. Unsubscribe in one click. We never sell or share your address.
Test yourself
Take the Data Parallelism quiz
Instant feedback on every answer, and a shareable certificate with a verifiable ID once you pass a course.
Support free AI education. AI Understanding is a 501(c)(3) nonprofit — no ads, no paywall, ever. Make a donation
Hagaha xiga
Maamulka Xogta AI
Su'aalaha soo noqnoqda
What is Data Parallelism?
Isbarbardhigga xogtu waxay si dhakhso leh u tababartaa hal moodal iyadoo ku soo celinaysa GPU-yo badan, iyadoo GPU kastaa uu farsameeyo jeex ka duwan dufcada xogta. Waa farsamada faraska shaqada ee u ogolaanaysa kooxuhu inay qiyaasaan daraasiin ama kumanaan xawaareyaal ah.
Isbarbardhigga xogta caadiga ah, muxuu GPU kasta hayaa?
GPU kastaa wuxuu hayaa nuqul buuxa oo moodeel ah oo wuxuu socodsiiyaa qayb gaar ah oo ka mid ah dufcada xogta, taas oo ah waxa ka dhigaya 'xog' isbarbardhigga halkii ay ka ahaan lahayd isbarbardhigga moodeelka.
Hawlgalkee isgaarsiineed ee ka dhigaya mid ka mid ah nuqullada moodeelka in ay la mid tahay tallaabo kasta?
Baas kasta oo gadaal-u-dhac ah ka dib, gradients ayaa la isku daraa dhammaan aaladaha iyada oo loo marayo dhammaan-dhimista (sida caadiga ah la soo koobo ka dibna la isku celceliyo) sidaa darteed nuqul kastaa wuxuu khuseeyaa isla cusbooneysiin.
Waa maxay xaddidaadda ugu weyn ee isbarbardhigga xogta cad?
Sababtoo ah GPU kastaa wuxuu hayaa nuqul buuxa oo wax walba ah, isbarbardhigga xogtu waxba ma caawinayso marka moodalku aad u weyn yahay inuu ku habboon yahay hal qalab.
Waa maxay sababta giraantu-dhammaan u-yaraynta u soo jiidanayso tirooyinka GPU-da weyn?
Ku garaac dhammaan-dhimista baasasyada jaangooyooyinka hareeraha giraanta macquulka ah, markaa wadarta xajmiyeedka xajmiyeedka kasta oo GPU-gu soo diro way joogtaa iyada oo aan loo eegin inta GPUs ka qaybqaadato.
Sidee PyTorch DistributedDataParallel u qariyaa daahitaanka isgaarsiinta?
DDP waxa ay bilawday in ay isku xidho jaangooyooyinka lakabyadii hore halka lakabyada danbe wali la xisaabinayo, isgaadhsiinta shabakada oo is dul saaran iyo xisaabinta.