Dubawa
Multi-Instance GPU (MIG) fasaha ce ta NVIDIA wacce ke yanka GPU na zahiri guda ɗaya zuwa ɓangarorin keɓancewar kayan masarufi da yawa. Yana da mahimmanci saboda yana ƙyale mai haɓaka mai tsada ɗaya yayi hidimar ƙananan ayyuka da yawa a lokaci ɗaya ba tare da sun shiga tsakani ba.
Multi-Misali GPU Partitioning wani shingen gini ne na fasaha wanda ke shafar ingancin samfuri, farashin kayayyakin more rayuwa, latency, da aminci a sikeli.
Zurfafa nutsewa
An gabatar da shi tare da NVIDIA A100 (Ampere) kuma ya ci gaba akan H100 da sabbin GPUs na cibiyar bayanai, MIG ya zana GPU zuwa lokuta masu zaman kansu har zuwa bakwai. Ba kamar yankan lokaci na software ba, MIG yana ba da keɓewar kayan aiki na gaskiya: kowane misali yana samun nasa keɓaɓɓun na'urorin sarrafawa masu yawa (SMs), yankan cache na L2, masu sarrafa ƙwaƙwalwar ajiya, da ƙayyadadden yanki na ƙwaƙwalwar bandwidth mai girma. Ana iya raba A100 tare da 40GB zuwa lokuta bakwai na 5GB, ko kaɗan mafi girma. Kowane bangare yana aiki kamar ƙaramin GPU mai zaman kansa, don haka aikin hayaniya ko faɗuwa a wani misali ba zai iya yunwa ko lalata wani ba. Wannan ingantaccen ingancin sabis yana sa MIG ya zama manufa don ƙaddamar da sabis, gungu masu haya da yawa, da mahallin ci gaba inda yawancin masu amfani ke raba kati ɗaya.
Fahimtar Fasaha
MIG yana aiki ta hanyar shigar da mashigin giciye na GPU ta jiki don haka kowane misali yana da madaidaiciyar hanya zuwa yanki na ƙwaƙwalwar ajiya da SMs. NVIDIA tana bayyana bayanan martaba azaman juzu'i kamar 1g.5gb (yanki guda ɗaya, 5GB) har zuwa 7g.40gb. Misalin GPU yana adana ƙwaƙwalwar ajiya da SMS; A cikin sa Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar Ƙididdigar a cikinsa tana ƙara rarraba SMs. Saboda ɓangarorin an tilasta musu kayan aiki, kurakurai, kurakuran ECC, da bandwidth na ƙwaƙwalwar ajiya sun kasance suna iyakance ga misali guda.
Jagorar Rarraba Multi-Misali GPU
Multi-Instance GPU (MIG) fasaha ce ta NVIDIA wacce ke yanka GPU na zahiri guda ɗaya zuwa ɓangarorin keɓancewar kayan masarufi da yawa. Yana da mahimmanci saboda yana ƙyale mai haɓaka mai tsada ɗaya yayi hidimar ƙananan ayyuka da yawa a lokaci ɗaya ba tare da sun shiga tsakani ba. Multi-Misali GPU Partitioning wani shingen gini ne na fasaha wanda ke shafar ingancin samfuri, farashin kayayyakin more rayuwa, latency, da aminci a sikeli. Don gina zurfin fahimta, bi Multi-Misali GPU Partitioning a matsayin samfurin 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 masu amfani da Multi-Instance GPU Partitioning 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
Mai ba da girgije yana raba A100 guda ɗaya zuwa yanayi bakwai don haka abokan ciniki bakwai kowanne ya sami garanti, yanki na GPU keɓe don ra'ayi.
Rukunin bincike na jami'a yana ba kowane ɗalibin PhD misali na 10GB MIG don yin samfuri maimakon sarrafa duka katunan.
Sabis na ƙididdigewa yana tattara ƙananan harsuna da ƙirar hangen nesa a kan H100 guda ɗaya, kowanne a cikin ɓangarensa tare da jinkirin da ake iya faɗi.
Tarin Kubernetes yana tallata misalan MIG azaman albarkatun da za'a iya tsarawa don haka kwas ɗin suna buƙatar 'nvidia.com/mig-1g.5gb' kamar kowane hanya.
Hanyoyin Aiwatarwa
Multi-Misali GPU Partitioning a aikace
Mai ba da girgije yana raba A100 guda ɗaya zuwa yanayi bakwai don haka abokan ciniki bakwai kowanne ya sami garanti, yanki na GPU keɓe don ra'ayi.
Mai ba da girgije yana raba A100 guda ɗaya zuwa yanayi bakwai don haka abokan ciniki bakwai kowannensu ya sami garanti, yanki na GPU keɓe don ƙungiyoyin ƙima yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓaka ɗan adam don shari'o'in gefe, da bin diddigin nasarorin samarwa da farashi na kuskure akan lokaci.
Multi-Misali GPU Partitioning a aikace
Rukunin bincike na jami'a yana ba kowane ɗalibin PhD misali na 10GB MIG don yin samfuri maimakon sarrafa duka katunan.
Rukunin binciken jami'a yana ba kowane ɗalibin PhD misali na 10GB MIG don yin samfuri maimakon sarrafa katunan duka Ƙungiyoyi yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓaka ɗan adam don shari'o'i, da bin diddigin nasarorin samarwa da ƙimar kuskure akan lokaci.
Multi-Misali GPU Partitioning a aikace
Sabis na ƙididdigewa yana tattara ƙananan harsuna da ƙirar hangen nesa a kan H100 guda ɗaya, kowanne a cikin ɓangarensa tare da jinkirin da ake iya faɗi.
Sabis na ƙididdigewa yana tattara ƙananan harshe da ƙirar hangen nesa a kan H100 guda ɗaya, kowanne a cikin nasa ɓangaren tare da Ƙungiyoyin jinkirin da za a iya iya gani yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓakar ɗan adam don ƙararraki, da kuma bibiyar nasarorin yawan aiki da ƙimar kuskure a kan lokaci.
Multi-Misali GPU Partitioning a aikace
Tarin Kubernetes yana tallata misalan MIG azaman albarkatun da za'a iya tsarawa don haka kwas ɗin suna buƙatar 'nvidia.com/mig-1g.5gb' kamar kowane hanya.
Tarin Kubernetes yana tallata misalan MIG azaman albarkatun da za'a iya tsarawa don haka kwas ɗin suna buƙatar 'nvidia.com/mig-1g.5gb' kamar sauran ƙungiyoyin albarkatu yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓaka ɗan adam don ƙararraki, da bin diddigin nasarorin samarwa da tsadar kurakurai 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.