Dubawa
Daidaituwar bayanai yana horar da ƙira ɗaya cikin sauri ta hanyar yin kwafinsa a cikin GPUs da yawa, tare da kowane GPU yana sarrafa wani yanki na daban na tsarin bayanai. Dabarar dokin aiki ce ke baiwa ƙungiyoyin damar yin ƙima zuwa dubunnan ko dubunnan masu hanzari.
Daidaiton bayanai wani shingen gini ne na fasaha wanda ke shafar ingancin samfuri, farashin kayayyakin more rayuwa, jinkiri, da aminci a sikeli.
Zurfafa nutsewa
A cikin daidaiton bayanai, kowane GPU yana riƙe da kwafi iri ɗaya na ma'aunin ƙirar amma yana aiwatar da takamaiman ƙaramin misalan horo. Kowace na'ura tana ƙididdige wucewar gaba da baya da kanta, tana samar da nata tsarin na gradients. Kafin sabuntawar ma'auni, ana ƙididdige matakan gradients a duk GPUs ta amfani da aikin sadarwa mai rahusa, don haka kowane kwafi yana kasancewa cikin aiki tare kuma yana nuna kamar an horar da shi akan babban haɗin gwiwa. Wannan yana haɓaka kayan aiki yadda ya kamata: 8 GPUs na iya taunawa ta hanyar kusan 8x bayanan kowane mataki. Abin kamawa shine kowane GPU dole ne ya dace da duka ƙirar, gradients, da yanayin ingantawa a cikin ƙwaƙwalwar ajiya, don haka daidaitattun bayanai ba ya taimakawa lokacin da samfurin ya yi girma ga na'ura ɗaya.
Fahimtar Fasaha
Makullin aiki shine duka-raguwa, wanda ke tattara gradients a cikin na'urori kuma yana sake rarraba sakamakon. Rage zobe, da dakunan karatu kamar NCCL da Horovod ke amfani da su, suna wucewa da ƙugiya a kusa da zobe mai ma'ana don haka jimillar sadarwa ta kasance mai zaman kanta daga ƙididdigar GPU. PyTorch's DistributedDataParallel ya mamaye wannan hanyar sadarwa tare da wucewar baya, yana kashe daidaitawar gradient don farkon yadudduka yayin da yadudduka ke ci gaba da yin lissafi, suna ɓoye yawancin lattin hanyar sadarwa.
Daidaita Bayanan Bayanai
Daidaituwar bayanai yana horar da ƙira ɗaya cikin sauri ta hanyar yin kwafinsa a cikin GPUs da yawa, tare da kowane GPU yana sarrafa wani yanki na daban na tsarin bayanai. Dabarar dokin aiki ce ke baiwa ƙungiyoyin damar yin ƙima zuwa dubunnan ko dubunnan masu hanzari. Daidaiton bayanai wani shingen gini ne na fasaha wanda ke shafar ingancin samfuri, farashin kayayyakin more rayuwa, jinkiri, da aminci a sikeli. Don gina zurfin fahimta, bi da Daidaituwar Bayanai azaman ƙirar aiki, ba fasali ɗaya ba: ayyana sakamakon da ake so, fayyace zato, da raba abin da tsarin zai iya yi da dogaro daga abin da har yanzu ke buƙatar yanke hukunci na ƙwararru.
A aikace, ƙungiyoyi masu ƙarfi da ke amfani da Daidaitan Bayanai suna haɓaka gine-gine, bayanai, da zaɓin abubuwan more rayuwa tare da 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
Horar da mai rarraba hoto na ResNet a cikin 8 GPUs a cikin sabar guda ɗaya ta amfani da PyTorch DistributedDataParallel, kowane GPU yana sarrafa 32 na tsari mai hoto 256.
Ƙimar BERT pretraining a cikin ɗaruruwan GPUs tare da Horovod, ta amfani da duk-rage don aiki tare gradients kowane mataki.
Kyakkyawan daidaita samfurin shawarwari akan gungu mai nau'in kumburi inda kowane kumburi yana aiwatar da shards-mu'amala daban-daban.
Amfani da Dabarun Mirrored na TensorFlow don yada horon ƙirar hangen nesa a cikin GPUs da yawa akan wurin aiki guda ɗaya tare da ƙaramin canje-canje na lamba.
Hanyoyin Aiwatarwa
Daidaiton bayanai a aikace
Horar da mai rarraba hoto na ResNet a cikin 8 GPUs a cikin sabar guda ɗaya ta amfani da PyTorch DistributedDataParallel, kowane GPU yana sarrafa 32 na tsari mai hoto 256.
Horar da mai rarraba hoto na ResNet a cikin 8 GPUs a cikin sabar guda ɗaya ta amfani da PyTorch DistributedDataParallel, kowane GPU mai sarrafa 32 na ƙungiyoyin hoto 256 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.
Daidaiton bayanai a aikace
Ƙimar BERT pretraining a cikin ɗaruruwan GPUs tare da Horovod, ta amfani da duk-rage don aiki tare gradients kowane mataki.
Scaling BERT pretraining a fadin ɗaruruwan GPUs tare da Horovod, ta yin amfani da duk-rage don aiki tare gradients kowane mataki 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.
Daidaiton bayanai a aikace
Kyakkyawan daidaita samfurin shawarwari akan gungu mai nau'in kumburi inda kowane kumburi yana aiwatar da shards-mu'amala daban-daban.
Daidaita samfurin shawarwarin akan gungu mai kumburi da yawa inda kowane kumburi yana aiwatar da shards na hulɗar mai amfani daban-daban 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 diddigin nasarorin samarwa da ƙimar kuskure a kan lokaci.
Daidaiton bayanai a aikace
Amfani da Dabarun Mirrored na TensorFlow don yada horon ƙirar hangen nesa a cikin GPUs da yawa akan wurin aiki guda ɗaya tare da ƙaramin canje-canje na lamba.
Amfani da TensorFlow's MirroredStrategy don yada horo na samfurin hangen nesa a cikin GPUs da yawa akan wurin aiki guda ɗaya tare da canje-canje kaɗan na ƙididdiga 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 gefen, da kuma bin diddigin abubuwan 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.