Uhlolojikelele
Uma imodeli inkulu kakhulu ukuthi ingangena ku-GPU eyodwa, imodeli nokufana kwepayipi kuhlukanisa imodeli ngokwayo kuwo wonke amadivayisi. Yilokhu okwenza ukuqeqesha amamodeli olimi amakhulu anamakhulu ezigidigidi zamapharamitha angenzeka ngokomzimba.
I-Model and Pipeline Parallelism iyibhulokhi yokwakha yobuchwepheshe ethinta ikhwalithi yamamodeli, izindleko zengqalasizinda, ukubambezeleka, nokuthembeka esikalini.
I-Deep Dive
Ukufana kwemodeli kuhlukanisa imodeli eyodwa kuwo wonke ama-GPU amaningi ukuze kungabikho idivayisi eyodwa edinga ukubamba zonke izisindo. Kunezinhlobo ezimbili zokunambitheka eziyinhloko. I-Tensor (intra-layer) parallelism ihlukanisa izibalo ngaphakathi kwesendlalelo, njengokusika ukuphindaphinda okukhulu kwe-matrix kuwo wonke ama-GPU okuthi ingxenye ngayinye ibale ingxenye yalokho okukhiphayo. Ukufana kwepayipi (inter-layer) kwabela izendlalelo ezihlukene ezilandelanayo kuma-GPU ahlukene, ngakho-ke ibhulokhi engu-1 iphila ku-GPU 0, i-block 2 ku-GPU 1, njalo njalo, ngokuvula okudlulele phambili njengomugqa wokuhlanganisa. Inselele ngamapayipi okungenangqondo 'ibhamuza': kuyilapho i-GPU 0 isebenza kuqeqebana lokuqala, ama-GPU angezansi ahlala engenzi lutho. Ukufakwa kwamapayipi kuhlukanisa iqoqo ngalinye libe ngamaqoqo amancane ukuze zonke izigaba zihlale zimatasa, kuthuthukisa kakhulu ukusetshenziswa.
I-Technical Insight
I-Tensor parallelism (njengaku-NVIDIA Megatron-LM) ihlukanisa ikholomu ka-matrices wesisindo- noma ngokuhlakanipha komugqa futhi isebenzisa ukunciphisa konke ukuze kuhlanganiswe imiphumela engaphelele, igcine ukuxhumana ngaphakathi kwenodi ye-NVLink esheshayo. Ukufana kwepayipi (i-GPipe, i-PipeDream) ihlukanisa inqwaba ibe amaqoqo amancane ageleza ngezigaba ngeshejuli ehlukanisiwe, incipha isikhathi 'sebhamuza' sokungenzi lutho. Okubili kuvame ukugqitshwa ndawonye, nokufana kwe-tensor phakathi kwe-node nokufana kwepayipi kuwo wonke ama-node.
I-Mastering Model kanye Nokufana Kwepayipi
Uma imodeli inkulu kakhulu ukuthi ingangena ku-GPU eyodwa, imodeli nokufana kwepayipi kuhlukanisa imodeli ngokwayo kuwo wonke amadivayisi. Yilokhu okwenza ukuqeqesha amamodeli olimi amakhulu anamakhulu ezigidigidi zamapharamitha angenzeka ngokomzimba. I-Model and Pipeline Parallelism iyibhulokhi yokwakha yobuchwepheshe ethinta ikhwalithi yamamodeli, izindleko zengqalasizinda, ukubambezeleka, nokuthembeka esikalini. Ukuze wakhe ukuqonda okujulile, phatha i-Model and Pipeline Parallelism njengemodeli yokusebenza, hhayi isici esisodwa: chaza imiphumela efiselekayo, ucacise ukucabanga, futhi uhlukanise lokho uhlelo olungakwenza ngokwethembeka kulokho okusadinga ukwahlulela kochwepheshe.
Empeleni, amaqembu aqinile asebenzisa i-Model kanye nePipeline Parallelism athuthukisa ukukhetha kwezakhiwo, idatha, kanye nengqalasizinda ngokumelene nokuthembeka nezindleko. Babhala imibandela yempumelelo ecacile, ukuhlola okuqhathaniswa nedatha engokoqobo nokugeleza komsebenzi, futhi baphindaphinde ngokusekelwe kumaphethini okuhluleka aqashiwe esikhundleni sokuwina kwebhentshimakhi yesikhathi esisodwa. Yilapho ukuqonda kwethiyori kuguquka kube amandla ahlala njalo kuwo wonke umkhiqizo, inqubomgomo, kanye nokusebenza.
Izinqumo zezakhiwo ziqhuba ukusebenza kanye nezindleko zokusebenza iminyaka. Ngesikhathi esifanayo, Ukuthuthukisa ibhentshimakhi eyodwa kungafihla ubuthakathaka obubanzi besistimu. Indlela eqine kakhulu iwukuhlanganisa isivinini sokuhlola nesiyalo sokuphatha: qhuba abashayeli bezindiza, bamba ubufakazi, ushicilele amalogi ezinqumo, futhi ubuyekeze izivikelo ngokuqhubekayo njengoba imodeli yokuziphatha, okulindelwe ngabasebenzisi, kanye nezimfuneko zokulawula zishintsha.
I-Strategic Impact
Izinqumo zezakhiwo ziqhuba ukusebenza kanye nezindleko zokusebenza iminyaka.
Izinqumo zezakhiwo ziqhuba ukusebenza kanye nezindleko zokusebenza iminyaka. Ekusetshenzisweni kwekhwalithi ephezulu, lokhu kuhunyushwa emithethweni yokusebenza elinganisekayo, imingcele yobunikazi, nemikhuba yokubuyekeza ephindelelayo ukuze amaqembu akwazi ukukala ukuzethemba esikhundleni sokukala ukungaqondakali.
Imfundo yobuchwepheshe isiza amaqembu ukuthi akhethe isitaki esifanele, hhayi nje esisha.
Imfundo yobuchwepheshe isiza amaqembu ukuthi akhethe isitaki esifanele, hhayi nje esisha. Ekusetshenzisweni kwekhwalithi ephezulu, lokhu kuhunyushwa emithethweni yokusebenza elinganisekayo, imingcele yobunikazi, nemikhuba yokubuyekeza ephindelelayo ukuze amaqembu akwazi ukukala ukuzethemba esikhundleni sokukala ukungaqondakali.
Izinketho ezingcono zobunjiniyela zinciphisa izehlakalo ezinokwethenjelwa ekukhiqizeni.
Izinketho ezingcono zobunjiniyela zinciphisa izehlakalo ezinokwethenjelwa ekukhiqizeni. Ekusetshenzisweni kwekhwalithi ephezulu, lokhu kuhunyushwa emithethweni yokusebenza elinganisekayo, imingcele yobunikazi, nemikhuba yokubuyekeza ephindelelayo ukuze amaqembu akwazi ukukala ukuzethemba esikhundleni sokukala ukungaqondakali.
Ukuqaliswa Komhlaba Wangempela
Ukuqeqesha amamodeli esitayela se-GPT nge-NVIDIA Megatron-LM, ehlukanisa ukunaka kwesendlalelo ngasinye se-transformer namatrices okudlulisela phambili kuwo wonke ama-GPU ngokusebenzisa i-tensor parallelism.
Ukusebenzisa i-GPipe ukubeka izendlalelo ezihlukene zombono omkhulu noma imodeli yolimi kuma-accelerator ahlukene kuyilapho i-micro-batching ibagcina bematasa.
Injini yepayipi ye-DeepSpeed ehlukanisa imodeli yepharamitha eyizigidigidi ezingamakhulu ngezigaba ezindaweni eziningi.
Ukuhlanganisa i-tensor parallelism ngaphakathi kweseva eyodwa ye-8-GPU nokufana kwepayipi okuhlanganisa amaseva amaningi ukuqeqesha imodeli enkulu kakhulu emshinini owodwa.
Amaphethini Okusebenzisa
Ukufana kweModel kanye nePipeline ekusebenzeni
Ukuqeqesha amamodeli esitayela se-GPT nge-NVIDIA Megatron-LM, ehlukanisa ukunaka kwesendlalelo ngasinye se-transformer namatrices okudlulisela phambili kuwo wonke ama-GPU ngokusebenzisa i-tensor parallelism.
Ukuqeqesha amamodeli esitayela se-GPT nge-NVIDIA Megatron-LM, ehlukanisa ukunaka kwe-transformer ngayinye kanye no-matrices odlulisela phambili kuwo wonke ama-GPU ngokusebenzisa i-tensor parallelism Amaqembu ngokuvamile athola imiphumela engcono uma echaza imingcele yekhwalithi ngaphambili, agcine indlela yokukhuphuka komuntu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
Ukufana kweModel kanye nePipeline ekusebenzeni
Ukusebenzisa i-GPipe ukubeka izendlalelo ezihlukene zombono omkhulu noma imodeli yolimi kuma-accelerator ahlukene kuyilapho i-micro-batching ibagcina bematasa.
Ukusebenzisa i-GPipe ukubeka izendlalelo ezihlukene zombono omkhulu noma imodeli yolimi kuma-accelerator ahlukene kuyilapho i-micro-batching iwagcina ematasa Amaqembu ngokuvamile athola imiphumela engcono lapho echaza izinga eliphezulu ngaphambili, agcine indlela yokukhuphuka yomuntu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
Ukufana kweModel kanye nePipeline ekusebenzeni
Injini yepayipi ye-DeepSpeed ehlukanisa imodeli yepharamitha eyizigidigidi ezingamakhulu ngezigaba ezindaweni eziningi.
Injini yepayipi ye-DeepSpeeds ehlukanisa imodeli yepharamitha yezigidigidi ezingamakhulu amaningi ibe izigaba kuwo wonke ama-node amaningi Amaqembu ngokuvamile athola imiphumela engcono lapho echaza izinga eliphezulu ngaphambili, egcina indlela yokukhuphuka komuntu yamakesi asemaphethelweni, futhi elandelela kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
Ukufana kweModel kanye nePipeline ekusebenzeni
Ukuhlanganisa i-tensor parallelism ngaphakathi kweseva eyodwa ye-8-GPU nokufana kwepayipi okuhlanganisa amaseva amaningi ukuqeqesha imodeli enkulu kakhulu emshinini owodwa.
Ukuhlanganisa i-tensor parallelism ngaphakathi kweseva eyodwa ye-8-GPU nokufana kwepayipi okuhlanganisa amaseva amaningi ukuze kuqeqeshwe imodeli enkulu kakhulu emshinini owodwa Amathimba ngokuvamile athola imiphumela engcono uma echaza imingcele yekhwalithi ngaphambili, agcine indlela yokukhuphuka komuntu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
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.
Chaza ukubambezeleka, ikhwalithi, nezindleko ezihlosiwe ngaphambi kokuqaliswa. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.
Ibhentshimakhi ngaphansi komthwalo wangempela nezimo zedatha.
Ibhentshimakhi ngaphansi komthwalo wangempela nezimo zedatha. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.
Ukuqapha amathuluzi amaphutha, ukukhukhuleka, nomthelela wabasebenzisi.
Ukuqapha amathuluzi amaphutha, ukukhukhuleka, nomthelela wabasebenzisi. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.
Lungiselela izindlela zokuhlehlisa nezigameko ngaphambi kokukala.
Lungiselela izindlela zokuhlehlisa nezigameko ngaphambi kokukala. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.