I-Tensor Parallelism yamamodeli amakhulu
Indlela yokuhlukanisa izibalo ngaphakathi kwesendlalelo esisodwa se-neural-network kuma-GPU amaningi ukuze imodeli enkulu kakhulu kudivayisi eyodwa isakwazi ukusebenza.
Uhlolojikelele
It matters because frontier models have hundreds of billions of parameters that no single GPU can hold or compute fast enough alone.
I-Deep Dive
I-Tensor parallelism (ebuye ibizwe ngokuthi i-intra-layer model parallelism) ihlukanisa u-matric wesisindo somuntu ngamunye kuwo wonke ama-GPU esikhundleni sokubeka izendlalelo eziphelele kumadivayisi ahlukene. Ku-transformer, ukuphindaphinda kwe-matrix enkulu—ukuqagela kokunakwa kanye ne-feed-forward MLP—kuyahlukaniswa: isibonelo, i-matrix yesisindo sokuqala ye-MLP ihlukaniswa ngamakholomu futhi eyesibili ngemigqa, ngakho-ke i-GPU ngayinye ibala ucezu futhi ukunciphisa konke okukodwa kuhlanganisa imiphumela. Ukunaka kuhlukaniswa ngamakhanda, i-GPU ngayinye iphethe isethi engaphansi. Ngoba yonke i-GPU yenza ingxenye yazo zonke izendlalelo ngasikhathi sinye, i-tensor parallelism kunciphisa inkumbulo ye-GPU ngayinye futhi isheshisa ikhompuyutha, kodwa idinga ukuxhumana okuvamile, okunomkhawulokudonsa ophezulu phakathi kwe-GPU isendlalelo ngasinye. Kungakho ivamise ukuvalelwa ngaphakathi kwendawo exhunywe yi-NVLink, futhi ihlanganiswe nepayipi kanye nokufana kwedatha yokuqeqeshwa okukhulu kakhulu nemisebenzi yokuhlinzeka.
I-Technical Insight
Iqhinga, elidume yi-Megatron-LM, likhetha ubukhulu bokuhlukanisa ukuze ukuxhumana kube kuncane. Ukuhlukanisa ikholomu ye-matrix yokuqala ye-MLP kuvumela i-GPU ngayinye ukuthi isebenzise ukungaqondile endaweni ngaphandle kokuvumelanisa; ukuhlukanisa umugqa wesibili ngokuhlakanipha kusho ukuthi okuphumayo kudinga nje ukunciphisa okukodwa ukuze kube nesamba semiphumela engaphelele. Ngakho-ke ungqimba ngalunye lufaka cishe ukuncishiswa okubili konke (kuya phambili) nokubili (emuva). Ngoba lezi ziqoqwana zenzeka kuzo zonke izendlalelo, ukubambezeleka kuyabusa-ngakho ukufana kwe-tensor kuhlala ngemuva kwezixhumanisi ezisheshayo ze-intra-node njenge-NVLink kunokuba amanethiwekhi ahamba kancane phakathi kwama-node.
I-Strategic Impact
Izindleko kanye nesabelomali
Izinqumo zezakhiwo ziqhuba ukusebenza kanye nezindleko zokusebenza iminyaka.
Izinqumo ezicacile
Imfundo yobuchwepheshe isiza amaqembu ukuthi akhethe isitaki esifanele, hhayi nje esisha.
Ukulawulwa kwekhwalithi
Izinketho ezingcono zobunjiniyela zinciphisa izehlakalo ezinokwethenjelwa ekukhiqizeni.
Ikusasa Le-Tensor Parallelism Yamamodeli Amakhulu
Ukufana kwe-tensor kuhlala kuyisisekelo kodwa kuya ngokuya kuxutshwa ku-'3D parallelism' (i-tensor + pipeline + idatha) futhi kuhlanganiswe nokufana kochwepheshe kumamodeli we-Mixture-of-Experts. Amafreyimu afana ne-Megatron-LM, i-DeepSpeed, ne-vLLM azenza kube lula ukuhlukanisa. Njengoba i-GPU ixhumeka (i-NVLink, i-NVSwitch) kanye nezindwangu zokukhanya ziya ngokushesha, umkhawulo we-node-boundary uyaxega, okuvumela amaqembu abanzi ahambisanayo. Lindela ukufanisa okuzenzakalelayo okuhlakaniphile okukhetha ubukhulu be-shard nosayizi beqembu ukuze unciphise ukuxhumana kwe-topology yeqoqo elithile.
Ukuqaliswa Komhlaba Wangempela
Ukuqeqesha imodeli yepharamitha engu-175B ngokuhlukanisa u-matric wesisindo sesendlalelo ngasinye kuma-GPU angu-8 endaweni eyodwa exhunywe ku-NVLink usebenzisa i-Megatron-LM.
Inikeza imodeli yengxoxo yepharamitha engu-70B ku-vLLM ene-tensor_parallel_size=4 ukuze izisindo zilingane kuma-GPU amane futhi ziphendule ngesikhathi sangempela.
Ukunaka kwe-transformer kugxila kuwo wonke ama-GPU ukuze idivayisi ngayinye ihlanganise isethi engaphansi, bese ihlanganisa okuphumayo kwesendlalelo esilandelayo.
Ukuhlanganisa i-tensor parallelism ngaphakathi kwama-node nokufana kwamapayipi kuwo wonke ama-node ukuqeqesha amamodeli wamapharamitha ayizigidigidi kumaqoqo amakhulu e-GPU.
Izingozi & Guardrails
Ukuthuthukisa ibhentshimakhi eyodwa kungafihla ubuthakathaka obubanzi besistimu.
Izindleko zengqalasizinda nezokulungisa zivame ukubukelwa phansi.
Izikhala zokuphepha nokubonakala zingakhula njengoba izinhlelo ziba nzima kakhulu.
Ukuqalisa Umhlahlandlela
Chaza ukubambezeleka, ikhwalithi, nezindleko ezihlosiwe ngaphambi kokuqaliswa.
Ibhentshimakhi ngaphansi komthwalo wangempela nezimo zedatha.
Ukuqapha amathuluzi amaphutha, ukukhukhuleka, nomthelela wabasebenzisi.
Lungiselela izindlela zokuhlehlisa nezigameko ngaphambi kokukala.
Qhubeka Uhlole
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Umhlahlandlela olandelayo
Ukufana kweModel kanye nePipeline
Imibuzo evame ukubuzwa
What is Tensor Parallelism for Large Models?
Indlela yokuhlukanisa izibalo ngaphakathi kwesendlalelo esisodwa se-neural-network kuma-GPU amaningi ukuze imodeli enkulu kakhulu kudivayisi eyodwa isakwazi ukusebenza. Kubalulekile ngoba amamodeli asemngceleni anamakhulu ezigidigidi zamapharamitha okungekho i-GPU eyodwa engakwazi ukuyibamba noma ukubala ngokushesha ngokwanele iyodwa.
I-tensor parallelism ihlukaniselani kuwo wonke ama-GPU?
I-Tensor (intra-layer) parallelism ihlukanisa u-matric wesisindo ngaphakathi kwesendlalelo, ngakho-ke yonke i-GPU ibala ingxenye yesendlalelo esifanayo—ehlukile kokufana kwamapayipi, okubeka izendlalelo eziphelele kuma-GPU ahlukene.
Ekuhlukaniseni i-MLP yesitayela se-Megatron, bahlukaniswa kanjani omatikuletsheni ababili besisindo ukuze kuncishiswe ukuxhumana?
Ukuhlukanisa i-matrix yokuqala ngamakholomu kuvumela i-GPU ngayinye ukuthi isebenzise ukungaqondile kwendawo; ukuhlukanisa okwesibili ngemigqa kusho ukunciphisa konke okukodwa kubala okuphumayo okungaphelele—ukunciphisa ukuvumelanisa.
Kungani i-tensor parallelism ivame ukugcinwa endaweni eyodwa?
Isendlalelo ngasinye sidala ukuxhumana okuhlangene (kunciphisa konke), ngakho ithrafikhi esindayo, ezwela ukubambezeleka idinga izixhumanisi ezisheshayo ze-intra-node njenge-NVLink esikhundleni sokunensa kwamanethiwekhi aphakathi kwamanodi.
Ingabe indlela yokunaka ivame ukufana kanjani ngaphansi kwe-tensor parallelism?
Izinhloko zokunaka zizimele, ngakho-ke zisakazwa kuwo wonke ama-GPU—idivayisi ngayinye ihlanganisa amakhanda athile futhi okuphumayo kuyahlanganiswa.
Yikuphi ukusebenza kweqoqo elivame ukuhlanganisa imiphumela engaphelele ku-tensor parallelism?
Ukunciphisa konke kubala ingxenye yemiphumela ebalwa ku-GPU ngayinye ukuze ivumelane ngomphumela wesendlalelo; lokhu kwenzeka izikhathi eziningi kusendlalelo ngasinye kumaphasi aya phambili nangemuva.