Hanyar KV Cache: Rage Aikin Cika LLM Mai Maimaitawa

Hanyar tura KV cache tana da mahimmanci lokacin da aka maimaita farkon tambayoyi a cikin zirga-zirgar LLM ɗinku. Idan buƙatar da ta dace ta sauka a kan kwafin da ya dace, injin sabis zai iya sake amfani da yanayin hankali da aka adana maimakon sake lissafin waɗannan alamomin prefill sau da sau.

Wannan yana kama da cikakken bayani na kayan aiki, amma yana zama matsalar samfur da sauri. Dogayen tambayoyin tsarin, mahallin RAG, misalan few-shot, da tarihin tattaunawa mai juyawa na iya sa aikin prefill ya yi tsada. Lokacin da kowace kwafi ta sake lissafin farkon tambaya ɗaya, ƙungiyoyi suna biyan lokaci, lokacin GPU, da tsare-tsaren ƙarfin aiki.

ShareAI yana ba masu haɓaka API ɗaya don samfura 150+, bayyanuwar kasuwa, tura tambayoyi, da sauya matsala. Hanyar tura KV cache tana zaune a mataki ɗaya ƙasa, a cikin kayan aikin sabis na samfur. Abin da ya dace ga masu karatun ShareAI yana da sauƙi: yanke shawarar tura tambayoyi yana da mahimmanci a kowane mataki na tsarin AI, daga zaɓin samfur har zuwa wane kwafin GPU ke sarrafa tambaya mai maimaitawa.

Me yasa Hanyar Tura KV Cache Tana da Mahimmanci

Lokacin fassarar LLM, samfurin yana fara sarrafa tambayar shigarwa a matakin prefill. Yana gina ajiyar maɓalli-da-daraja, wanda yawanci ake kira KV cache, don haka alamomin da aka samar daga baya za su iya komawa ga mahallin da aka riga aka sarrafa.

Ajiyar farkon tambaya yana ba injinan sabis damar sake amfani da wannan ajiyar lokacin da tambaya ta gaba ta raba farkon tambayar iri ɗaya. Takaddun ajiyar farkon tambaya ta atomatik na vLLM yana bayyana wannan a matsayin sake amfani da KV cache don farkon tambayoyi da aka raba don tambayar sabuwa ta iya tsallake lissafi don ɓangaren da aka raba. Ajiyar farkon tambaya ta SGLang yana amfani da ra'ayi mai alaƙa don raba KV cache don jerin alamomin gama gari.

Wannan yana da mahimmanci musamman ga nau'ikan aiki inda tambayoyi da yawa ke farawa iri ɗaya: wakilan tallafi tare da dogon tambayar tsarin, aikace-aikacen RAG da ke amfani da maimaita takardun, wakilan lamba tare da umarnin ma'ajiyar bayanai, ko samfuran tattaunawa da ke ɗaukar tarihin tattaunawa a cikin juyawa.

Inda Round-Robin Ya Kasa

Ajiyar farkon tambaya ya fi sauƙi a kan kwafi ɗaya. Tsarin iri ɗaya yana ganin farkon tambaya mai maimaitawa kuma zai iya sake amfani da ajiyarsa idan akwai ƙwaƙwalwar ajiya. Matsalar tana bayyana lokacin da sabis ɗin ya faɗaɗa a kwance.

Tare da mai daidaita nauyi na round-robin na yau da kullum, tambaya ta farko na iya kunna ajiyar a kan kwafi A, yayin da tambaya ta biyu tare da farkon tambaya iri ɗaya ta sauka a kan kwafi B. Kwafi B ba shi da wannan yanayin da aka adana, don haka yana sake lissafin aikin prefill iri ɗaya. Tambaya ta uku na iya zuwa kwafi C kuma ta rasa kuma.

Yayin da adadin kwafi ya ƙaru, daidaita nauyi mai sauƙi na iya rarraba tambayoyi masu alaƙa a kan ƙarin injuna. Rundunar sabis na samfur na iya zama daidaitacce, amma adadin samun ajiyar farkon tambaya yana raguwa. Wannan shi ne gibin da hanyar tura KV cache ke ƙoƙarin cikewa.

Matakai Uku na Hanyar Gudanarwa Mai Aiki

1. Dacewar Zama

Dacewar zama yana jagorantar zirga-zirgar daga mai amfani ɗaya, wurin aiki, mai haya, ko tattaunawa zuwa kwafi ɗaya. Ita ce mafi sauƙi wajen farawa don tattaunawa mai juyawa saboda tambayoyin da ke bi sau da yawa suna raba mahallin da ya gabata.

Matsalar ita ce cewa ainihin mai amfani ba koyaushe yake daidai da kamanceceniya tambaya ba. Mutane biyu na iya raba dogon tsarin tambaya ɗaya kuma har yanzu a jagoranci su zuwa kwafi daban-daban. Dacewar zama kuma na iya rikicewa lokacin da aka ƙara ko cire kwafi.

2. Hanyar Prefix-Hash

Hanyar prefix-hash tana amfani da tambayar kanta a matsayin maɓallin hanyar. Mai jagoranci yana yin hash na farkon tambayar mai tsayayye kuma yana aika daidai prefixes zuwa kwafi ɗaya.

Wannan yana aiki mafi kyau lokacin da tambayoyin tsarin da ake maimaitawa, misalan few-shot, ko mahallin da aka samo wanda aka raba ya fi mahimmanci fiye da ainihin mai amfani. Mafi wahala shi ne zaɓar iyakar prefix. Idan hash ya haɗa da alamar lokaci, ID na buƙata, ko filin na musamman na mai amfani, maɓallin hanyar yana rarrabuwa kuma sake amfani da cache yana rushewa.

3. Hanyar Cache-Event-Aware

Mafi ci gaba yana bin waɗanne tubalan cache suke kan wane kwafi, sannan yana jagorantar kowace buƙata zuwa kwafi tare da mafi kyawun daidaiton cache yayin da har yanzu yana la'akari da nauyi. aikin na'ura mai ba da hanya tsakanin hanyoyin sadarwa llm-d yana bayyana mai zaɓar ƙarshen da ke la'akari da KV-cache locality, nauyin yanzu, da fifiko lokacin zaɓar inda buƙata ya kamata ta je.

Wannan ya fi rikitarwa, amma yana daidai ga manyan rukunin aiki inda rashin cache ake aunawa, mai tsada, kuma mai yawan faruwa.

Lokacin Da Za A Tsallake Shi

Hanyar KV cache ba ta da daraja ta atomatik saboda rikitarwa. Ba ta dace sosai ba lokacin da tambayoyin suka kasance gajeru, mafi yawan na musamman, ko aka sarrafa su a cikin batches tare da ƙaramin tsari mai maimaitawa.

Takaitaccen takardu, ƙirƙirar kirkira, cirewa na lokaci ɗaya, da yawancin ayyukan batch na asinkron ba za su iya samun isasshen daidaiton prefix da aka raba don tabbatar da hanyar cache-aware ba. A irin waɗannan lokuta, daidaiton nauyi na yau da kullum na iya zama mafi tsabta.

Gwajin aikace-aikace yana auna: adadin samun cache, lokaci zuwa farkon alamar, yawan aiki, zurfin jerin aiki, matsin ƙwaƙwalwar GPU, da farashin kowace aikin da aka kammala. Idan hanyar cache-aware ba ta motsa waɗannan lambobin ba, gyara tsarin tambaya da farko.

Yadda Wannan Ya Dace Da ShareAI

ShareAI kasuwa ce ta AI da API, ba mai daidaita nauyin samfurin AI a cikin rukunin GPU ɗinku ba. Masu haɓakawa suna amfani da ShareAI don samun dama ga samfura da yawa ta hanyar API ɗaya, kwatanta siginar kasuwa, tsara buƙatu, sarrafa amfani, da kuma sauyawa lokacin da wata hanya ta lalace.

Wannan har yanzu yana sa hanyar KV cache ta zama mai mahimmanci. Idan kuna sarrafa tsarin fassarar ku na kanku, yana taimaka muku yin tambayoyi mafi kyau game da kayan aiki. Idan kuna amfani da samfuran da aka shirya, yana taimaka muku tantance dalilin da yasa hanyoyi biyu masu suna iri ɗaya na samfurin na iya yin aiki daban-daban a ƙarƙashin nauyin aiki na gaske.

Ga Masu Gina, wannan kuma yana da alaƙa da farashi. Wani app mai dogon tambayoyi, maimaita mahallin RAG, ko madaukai na wakili na iya haifar da amfani da AI mara daidaito sosai. ShareAI Builder yana ba masu mallakar aikace-aikace damar tsara zirga-zirgar fassarar AI ta hanyar ShareAI, saita riba ko ƙarin farashi, bari abokan ciniki su biya ShareAI don amfani da aka tsara, kuma su karɓi biyan kuɗi na wata-wata bisa ga amfani da aka samar. Aikace-aikacen kansa yana ci gaba da kasancewa a waje da ShareAI.

Don zaɓin samfur da kimanta hanya, fara da kasuwar samfuran ShareAI. Don abubuwan aiwatarwa na asali, yi amfani da Manuniya API na ShareAI.

Jerin Duba Hanyar KV Cache

• Sanya abun cikin tambaya mai tsayayye da farko: tambayar tsarin, dokokin kayan aiki, misalai, da mahallin da ake maimaitawa.
• Matsar da filayen da ke canzawa zuwa baya: lokutan lokaci, lambar buƙata, bayanan musamman na mai amfani, da umarnin lokaci ɗaya.
• Auna adadin samun cache kafin da bayan canje-canje na hanya.
• Kula da lokaci zuwa farkon alamar, yawan aiki, zurfin jerin aiki, da matsin VRAM tare.
• Fara da hanyar prefix-hash kafin gina hanyar da ke da masaniyar cache-event.
• Raba dokokin hanya ta nauyin aiki maimakon tilasta manufofin duniya ɗaya.
• Ka kiyaye farashi da jinkiri a bayyane a matakin aikace-aikace, ba kawai a cikin rukunin fassarar ba.

Tambayoyi akai-akai (FAQ).

Menene hanyar sadarwar KV cache?

Hanyar sadarwar KV cache wata dabara ce ta sadarwa da ke aika buƙatu tare da maimaita farkon tambayoyi zuwa kwafi waɗanda ake tsammanin suna riƙe da daidaitaccen KV cache. Manufar ita ce rage maimaita lissafin prefill.

Ta yaya hanyar sadarwar KV cache ta bambanta da adana farkon tambayoyi?

Adana farkon tambayoyi ita ce ikon injin samfurin amfani da yanayin da aka adana don farkon tambayoyi da aka raba. Hanyar sadarwar KV cache ita ce dabarar sanya zirga-zirga da ke taimakawa buƙatun da suka dace su isa inda wannan yanayin da aka adana yake.

Me yasa hanyar sadarwar round-robin ke cutar da adana farkon tambayoyi?

Hanyar sadarwar round-robin tana rarraba buƙatu a tsakanin kwafi ba tare da sanin wane kwafi ke da wane farkon tambaya da aka adana ba. Wata tambaya da aka maimaita na iya rasa cache saboda kawai ta sauka a wani kwafi daban.

Waɗanne nau'ikan aiki ne suka fi amfana daga hanyar sadarwar KV cache?

Tattaunawa mai juyawa da yawa, RAG, wakilan lamba, wakilan tallafi, tambayoyi masu ɗan kaɗan, da aikace-aikace tare da dogayen tsarin tambayoyi da aka raba su ne mafi dacewa saboda suna sake amfani da manyan farkon tambayoyi.

Yaushe ya kamata wata ƙungiya ta kauce wa hanyar sadarwar KV cache?

Kauce mata idan tambayoyin suna da gajarta, mafi yawansu na musamman ne, ko kuma suna da tsarin tsari tare da ƙaramin maimaituwa. A irin waɗannan lokuta, rikitarwa na hanyar sadarwa na iya ƙara ƙaramin amfani.

Shin vLLM da SGLang suna tallafawa adana farkon tambayoyi?

Eh. vLLM yana daftarin adana farkon tambayoyi ta atomatik, kuma SGLang yana daftarin adana farkon tambayoyi don raba KV cache a cikin jerin alamu na gama gari. Har yanzu injin samfurin yana buƙatar taimakon hanyar sadarwa idan kwafi da yawa suna cikin aiki.

Shin hanyar sadarwar KV cache iri ɗaya ce da adana ma'ana?

A'a. Hanyar sadarwar KV cache tana aiki tare da daidaitaccen ko kusan daidaitaccen amfani da farkon tambayoyi a cikin hidimar fahimta. Adana ma'ana tana adana da sake amfani da amsoshi ko sakamakon tsaka-tsaki bisa ma'ana, yawanci tare da haɗe-haɗe ko iyakokin kamance.

Shin ShareAI yana maye gurbin mai daidaita nauyin da ke da masaniyar KV cache?

A'a. ShareAI kasuwa ce ta AI da kuma API layer don samun damar samfurori, hanya, failover, amfani, da kuma biyan kuɗi. KV-cache-aware routing shine ƙananan matakin kayan aikin samfurin samfurin don ƙungiyoyin da ke aiki da kwafin inference.

Ta yaya ya kamata Masu Gina su yi tunani game da hanyar KV cache?

Masu Gina ya kamata su ɗauki halayen cache a matsayin ɗaya daga cikin abubuwan da ke haifar da farashi a cikin aikace-aikacen da ke da nauyin AI. Idan aikace-aikacen su yana da amfani mara daidaito, ShareAI na iya taimakawa wajen tsara da samun kuɗi daga wannan zirga-zirgar AI yayin da aikace-aikacen ya kasance an gina shi kuma an mallake shi a wajen ShareAI.

Me ya kamata ƙungiyoyi su auna kafin su canza hanyar?

Auna ƙimar cache hit, lokaci zuwa farkon token, throughput, zurfin layi, matsin lamba na VRAM, farashi a kowace aiki, da ingancin fitarwa. Canje-canje na hanya ya kamata su inganta nauyin aiki, ba kawai dashboard ba.

Shin hanyar KV cache na iya rage farashin API na AI?

Zai iya rage farashin kayan aiki ga ƙungiyoyin da ke hidimar samfurori da kansu saboda ƙarancin aikin prefill mai maimaitawa na iya inganta ingancin GPU. Ga APIs da aka karɓa, tasirin ya dogara da ko mai bayarwa ya bayyana waɗannan tanadin a cikin farashi ko aiki.