GPU vs TPU don AI
GPUs da TPUs sune manyan nau'ikan guntu guda biyu don horarwa da gudanar da AI.
Dubawa
GPUs are flexible all-rounders dominated by NVIDIA; TPUs are Google's custom chips built specifically to crunch the math behind neural networks.
Zurfafa nutsewa
A GPU (Graphics Processing Unit) was originally built to render video-game graphics, but its thousands of parallel cores turned out to be perfect for the matrix math in deep learning. NVIDIA GPUs (kamar A100 da H100), an haɗa su tare da yanayin yanayin software na CUDA, sun zama tsohuwar masana'antar. TPU (Tensor Processing Unit) ASIC Google ce - takamaiman guntu da aka tsara daga karce don ayyukan tensor. TPUs suna amfani da 'systolic array' wanda ke watsa bayanai ta hanyar grid na raka'a masu tarin yawa tare da ƙarancin zirga-zirgar ƙwaƙwalwar ajiya, yana mai da su inganci sosai don haɓakar manyan matrix. Kasuwancin da ya dace: GPUs suna da yawa, ana samunsu sosai, kuma suna goyan bayan ɗimbin yanayin yanayin software; TPUs na iya ba da mafi kyawun aiki-per-watt da farashi don takamaiman horo mai girma amma galibi an ɗaure su da Google Cloud da tarin TensorFlow/JAX.
Fahimtar Fasaha
Bambancin kanun labarai shine gine-gine. GPU yana da nau'ikan maƙasudin gaba ɗaya da yawa tare da 'Tensor Cores' na musamman don lissafin matrix. An gina TPU a kusa da tsararru na systolic: grid hardware inda bayanai ke gudana ta hanyar haɗin haɗin kai mai tarawa, don haka matsakaicin sakamako yana wucewa kai tsaye tsakanin sel maimakon karantawa da rubuta ƙwaƙwalwar ajiya akai-akai. Wannan yana yanke matsa lamba na ƙwaƙwalwar ajiyar ƙwaƙwalwar ajiya - galibi ainihin ƙwanƙwasa - yin TPUs sosai a cikin matrix mai yawa wanda ke mamaye horon hanyar sadarwa.
Dabarun Tasiri
Kudin da kasafin kuɗi
Hukunce-hukuncen gine-gine suna haifar da aiki da tsadar aiki na shekaru.
Shawarwari masu haske
Ilimin fasaha yana taimaka wa ƙungiyoyi su zaɓi tari mai kyau, ba kawai sabon abu ba.
Kula da inganci
Zaɓuɓɓukan injiniya mafi kyau suna rage abin dogaro a cikin samarwa.
Makomar GPU vs TPU don AI
Halin al'ada-silicon yana haɓakawa. Bayan Google's TPUs, Amazon (Trainium/Inferentia), Microsoft (Maia), da yawancin masu farawa suna zayyana takamaiman guntu na AI don yanke dogaro ga NVIDIA da ƙarancin farashi. Yi tsammanin ƙarin ƙwarewa - keɓaɓɓen kwakwalwan kwamfuta waɗanda aka inganta don horarwa tare da ƙarancin ƙarancin latency - da haɓaka fifiko kan aiki-per-watt yayin da makamashi ya zama ƙaƙƙarfan ɗaure. NVDIA's CUDA moat yana ci gaba da mamaye GPUs a yanzu, amma jagorar dogon lokaci shine mafi yanayin shimfidar kayan masarufi.
Aiwatar da Gaskiyar Duniya
Horar da babban samfurin harshe akan Google Cloud TPU 'pod' na dubban kwakwalwan kwamfuta masu haɗin gwiwa
Masu bincike suna amfani da NVIDIA H100 GPUs tare da CUDA don gwaji tare da sababbin gine-ginen ƙira
Farawa na hayar GPUs ta sa'a daga mai samar da gajimare saboda sassaucin su da faffadan tallafin tsarin
Google yana gudanar da bincike don Bincike da Fassara da kyau akan TPUs a ma'auni mai girma
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.
Alamar ma'auni a ƙarƙashin ainihin kaya da yanayin bayanai.
Kula da kayan aiki don kurakurai, ɗigo, da tasirin mai amfani.
Shirya bijirowa da hanyoyin mayar da martani kafin sikeli.
Ci gaba da Bincike
Free newsletter
Get the daily AI briefing
Three verified AI stories every weekday morning, written in plain English. Free forever, no ads.
One email each weekday. Unsubscribe in one click. We never sell or share your address.
Test yourself
Take the GPU vs TPU for AI quiz
Instant feedback on every answer, and a shareable certificate with a verifiable ID once you pass a course.
Support free AI education. AI Understanding is a 501(c)(3) nonprofit — no ads, no paywall, ever. Make a donation
Jagora na gaba
Gudanar da Ƙwaƙwalwar Ƙwaƙwalwar GPU da Rarraba
Tambayoyin da ake yawan yi
What is GPU vs TPU for AI?
GPUs da TPUs sune manyan nau'ikan guntu guda biyu don horarwa da gudanar da AI. GPUs masu sassaucin ra'ayi ne wanda NVIDIA ta mamaye; TPUs Google's guntu na al'ada da aka gina musamman don murƙushe lissafi a bayan cibiyoyin sadarwa.
Menene GPU da aka tsara don yi kafin ya zama tsakiyar AI?
GPUs an gina su don yin zane-zane, amma ƙaƙƙarfan ƙirar su ta daidaici ta tabbatar da dacewa ga matrix ɗin a cikin zurfin koyo.
Wanene ya tsara TPU?
Sashin sarrafawa na Tensor guntu ne na al'ada (ASIC) wanda Google ya tsara musamman don ayyukan aikin cibiyar sadarwa.
Menene ainihin tsarin kayan masarufi ya sa TPUs masu inganci a haɓaka matrix?
TPUs suna amfani da tsarin systolic inda bayanai ke gudana ta hanyar grid na sel masu tarin yawa, suna ba da sakamako kai tsaye a tsakanin su da rage zirga-zirgar ƙwaƙwalwar ajiya.
Wanne dalili ne sau da yawa ƙugiya ta GASKIYA da TPUs ke son ragewa?
Matsar da bayanai a ciki da waje daga ƙwaƙwalwar ajiya akai-akai shine ƙayyadaddun abu; systolic array yana rage wannan ta hanyar wucewa tsaka-tsakin sakamako kai tsaye tsakanin sel.
Menene babban amfani mai amfani na GPUs akan TPUs?
GPUs suna da yawa, akwai ko'ina, kuma ana goyan bayan manyan yanayin yanayin CUDA da babban tsarin tallafi, yana mai da su tsoffin masana'antu.