Dubawa
Sadarwa ta gama gari ita ce yadda rukunin GPUs ke musanya da haɗa bayanai, kuma NCCL ita ce ɗakin karatu na NVIDIA wanda ke sanya waɗancan musayar musayar wuta cikin sauri. Ayyuka kamar duk-raguwa sune bugun zuciya na horarwa da aka rarraba, aiki tare da gradients a kowane GPU kowane mataki.
Sadarwar Sadarwa da NCCL ƙaƙƙarfan ginin fasaha ne wanda ke shafar ingancin samfuri, farashin kayayyakin more rayuwa, latency, da aminci a sikeli.
Zurfafa nutsewa
Horar da babban samfuri yana nufin kowane GPU yana lissafta gradients akan nasa yanki na bayanai, sannan duk GPUs dole ne su yarda da sakamakon haɗin gwiwa kafin mataki na gaba. Ana yin wannan haɗin kai tare da ayyukan gama kai: duk-rage ƙimar ƙima a cikin GPUs kuma yana ba kowa sakamako; duk-taron tattara kowane yanki na GPU zuwa cikakken kwafi akan su duka; watsa shirye-shirye yana aika bayanan GPU ɗaya ga sauran; rage-watse ya hade sannan ya rabu. NCCL (NVIDIA Collective Communications Library) yana aiwatar da waɗannan da kyau a cikin GPUs a cikin uwar garken da kuma cikin sabar, ta amfani da algorithms na topology-sani kamar zobe da itace duk-rage. Yana amfani da NVLink a cikin kumburi da InfiniBand ko RoCE tsakanin nodes, kuma shine kashin bayan sadarwa a ƙarƙashin PyTorch DDP, FSDP, DeepSpeed, da Megatron.
Fahimtar Fasaha
Ring duk-rage shine al'adar algorithm: GPUs suna samar da zobe na ma'ana, kuma an raba bayanan zuwa gungu-gungu waɗanda ke yawo don haka kowane mataki ya mamaye sadarwa, yana mai da jimlar canja wurin bandwidth-mafi kyau kuma mai zaman kansa daga ƙididdigar GPU. Ga nodes da yawa, algorithms na tushen itace suna rage jinkiri ta hanyar haɗa sakamako cikin matsayi. NCCL auto-gane topology, zabar mafi kyawun algorithm, kuma zai iya saukar da raguwar lissafi a cikin hanyar sadarwa tare da NVIDIA SHARP, ragi bayanan da dole ne su ketare hanyoyin haɗin gwiwa.
Mastering Collective Communication and NCCL
Sadarwa ta gama gari ita ce yadda rukunin GPUs ke musanya da haɗa bayanai, kuma NCCL ita ce ɗakin karatu na NVIDIA wanda ke sanya waɗancan musayar musayar wuta cikin sauri. Ayyuka kamar duk-raguwa sune bugun zuciya na horarwa da aka rarraba, aiki tare da gradients a kowane GPU kowane mataki. Sadarwar Sadarwa da NCCL ƙaƙƙarfan ginin fasaha ne wanda ke shafar ingancin samfuri, farashin kayayyakin more rayuwa, latency, da aminci a sikeli. Don gina zurfin fahimta, kula da Sadarwar Sadarwa da NCCL a matsayin samfurin aiki, ba sifa ɗaya ba: ayyana sakamakon da ake so, bayyana zato, da raba abin da tsarin zai iya yi da dogaro daga abin da har yanzu yana buƙatar yanke hukunci na ƙwararru.
A aikace, ƙungiyoyi masu ƙarfi masu amfani da Sadarwar Sadarwa da NCCL suna haɓaka gine-gine, bayanai, da zaɓin abubuwan more rayuwa a kan dogaro da farashi. Suna rubuta ƙayyadaddun ƙa'idodin nasara, gwaji akan bayanan gaskiya da gudanawar aiki, da jujjuyawar bisa ga tsarin gazawar da aka lura maimakon cin nasara na lokaci ɗaya. Wannan shine inda fahimtar ka'idar ta juya zuwa iyawa mai dorewa a cikin samfura, manufofi, da ayyuka.
Hukunce-hukuncen gine-gine suna haifar da aiki da tsadar aiki na shekaru. A lokaci guda, Haɓaka ma'auni ɗaya na iya ɓoye manyan raunin tsarin. Hanyar da ta fi dacewa ita ce haɗa saurin gwaji tare da horon gudanarwa: gudanar da matukin jirgi, kama shaida, buga rajistan ayyukan yanke shawara, da ci gaba da sabunta abubuwan tsaro kamar yadda halayen ƙira, tsammanin mai amfani, da buƙatun tsari ke tasowa.
Dabarun Tasiri
Hukunce-hukuncen gine-gine suna haifar da aiki da tsadar aiki na shekaru.
Hukunce-hukuncen gine-gine suna haifar da aiki da tsadar aiki na shekaru. A cikin ƙawance masu inganci, ana fassara wannan zuwa ƙa'idodin aiki waɗanda za a iya aunawa, iyakokin ikon mallaka, da kuma bita-da-kullin bita don ƙungiyoyi su iya haɓaka kwarin gwiwa a maimakon ɓata shakku.
Ilimin fasaha yana taimaka wa ƙungiyoyi su zaɓi tari mai kyau, ba kawai sabon abu ba.
Ilimin fasaha yana taimaka wa ƙungiyoyi su zaɓi tari mai kyau, ba kawai sabon abu ba. A cikin ƙawance masu inganci, ana fassara wannan zuwa ƙa'idodin aiki waɗanda za a iya aunawa, iyakokin ikon mallaka, da kuma bita-da-kullin bita don ƙungiyoyi su iya haɓaka kwarin gwiwa a maimakon ɓata shakku.
Zaɓuɓɓukan injiniya mafi kyau suna rage abin dogaro a cikin samarwa.
Zaɓuɓɓukan injiniya mafi kyau suna rage abin dogaro a cikin samarwa. A cikin ƙawance masu inganci, ana fassara wannan zuwa ƙa'idodin aiki waɗanda za a iya aunawa, iyakokin ikon mallaka, da kuma bita-da-kullin bita don ƙungiyoyi su iya haɓaka kwarin gwiwa a maimakon ɓata shakku.
Aiwatar da Gaskiyar Duniya
Daidaita gradients kowane matakin horo a duk GPUs ta amfani da duk-raguwa a cikin PyTorch DistributedDataParallel
Rarraba jihohin ingantawa da tara sigogi akan buƙatu tare da tattara duka da rage-warwatsawa a cikin FSDP ko DeepSpeed ZeRO
Watsa ma'aunin ƙira na farko daga GPU ɗaya zuwa duk wasu a farkon guduwar horo
Yin amfani da zobe duka-rage akan NVLink da InfiniBand don ci gaba da haɓaka babban bandwidth a cikin gungu na GPU masu yawa.
Hanyoyin Aiwatarwa
Sadarwar Jama'a da NCCL a aikace
Daidaita gradients kowane matakin horo a duk GPUs ta amfani da duk-raguwa a cikin PyTorch DistributedDataParallel.
Daidaita gradients kowane matakin horo a cikin duk GPUs ta amfani da duk-raguwa a cikin PyTorch DistributedDataParallel Ƙungiyoyi yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓakar ɗan adam don ƙararrakin ƙira, da bin diddigin nasarorin samarwa da ƙimar kuskure akan lokaci.
Sadarwar Jama'a da NCCL a aikace
Rarraba jihohin ingantawa da tara sigogi akan buƙatu tare da tattara duka da rage-warwatsawa a cikin FSDP ko DeepSpeed ZeRO.
Rarraba jihohin ingantawa da tara sigogi akan buƙatu tare da tarawa da rage-warwatsawa a cikin FSDP ko DeepSpeed ZeRO Ƙungiyoyi yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓakar ɗan adam don ƙararraki, da bin diddigin nasarorin samarwa da ƙimar kuskure akan lokaci.
Sadarwar Jama'a da NCCL a aikace
Watsa ma'aunin ƙira na farko daga GPU ɗaya zuwa duk wasu a farkon guduwar horo.
Watsa ma'aunin ƙira na farko daga GPU ɗaya zuwa duk wasu a farkon gudanar da horo Ƙungiyoyi yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓakar ɗan adam don shari'o'in gefe, da bin duk nasarorin samarwa da ƙimar kuskure akan lokaci.
Sadarwar Jama'a da NCCL a aikace
Yin amfani da zobe duk-rage akan NVLink da InfiniBand don ci gaba da girman bandwidth a cikin rukunonin GPU masu yawan kumburi.
Yin amfani da zobe duk-rage akan NVLink da InfiniBand don ci gaba da haɓaka babban bandwidth a cikin ƙungiyoyin GPU masu yawa yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓakar ɗan adam don shari'o'in gefen, da bin duk nasarorin samarwa da ƙimar kuskure akan lokaci.
Hatsari & Tsare-tsare
Haɓaka ma'auni ɗaya na iya ɓoye manyan raunin tsarin.
Sau da yawa ana raina kayan more rayuwa da kuma kuɗin kulawa.
Tsaro da gibin lura na iya girma yayin da tsarin ke ƙara haɓaka.
Taswirar Hanya
Ƙayyade latency, inganci, da maƙasudin farashi kafin aiwatarwa.
Ƙayyade latency, inganci, da maƙasudin farashi kafin aiwatarwa. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.
Alamar ma'auni a ƙarƙashin ainihin kaya da yanayin bayanai.
Alamar ma'auni a ƙarƙashin ainihin kaya da yanayin bayanai. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.
Kula da kayan aiki don kurakurai, ɗigo, da tasirin mai amfani.
Kula da kayan aiki don kurakurai, ɗigo, da tasirin mai amfani. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.
Shirya bijirowa da hanyoyin mayar da martani kafin sikeli.
Shirya bijirowa da hanyoyin mayar da martani kafin sikeli. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.