HAGAHA Farsamada
PagedAttention iyo vLLM
PagedAttention manages transformer key/value caches using fixed-size blocks mapped from logical token positions.
Dhageyso hagahanAI-waa laga sheekeeyay · ~2 min
Boggaan2 daqiiqo akhri
Dulmar
This reduces cache-allocation waste and supports sharing, while vLLM’s actual throughput depends on the workload and system.
quusid qoto dheer
Marka qaabka luqaddu soo saaro qoraal, wuxuu hayaa 'KV cache' (muhiimka muhiimka ah iyo qiimaha vectors) calaamad kasta oo uu arkay si calaamadda xigta ay ula socoto macnaha guud. Dhaqan ahaan codsi kastaa wuxuu hayaa hal sariirood oo weyn oo iskuxiran oo xusuusta GPU ah oo lagu cabiray dhererkeeda ugu badnaan ee suurtogalka ah, luminaya xaddi aad u badan marka taxanaha ay gaaban yihiin ama kala duwan yihiin dhererka. PagedAttention, oo lagu soo bandhigay xaashida vLLM 2023 ee UC Berkeley, ayaa ka soo amaahday fikradda xusuusta dalwaddii ee nidaamyada hawlgalka: waxay u kala qaybisaa kaydinta KV qaybo cabbir go'an oo ku noolaan kara meel kasta oo xusuusta ah oo loo qoondeeyo baahida. Shaxda la-fiirintu waxay khariidad ka dhigtaa boosaska calaamada macquulka ah ee blocks jirka. Tani waxay ku dhowdahay inay tirtirto kala qaybsanaanta xusuusta waxayna u oggolaanaysaa baloogyada in la wadaago, tusaale ahaan wax soo saar badan oo isla markiiba ah.
Dhaqangelinta Adduunka-dhabta ah
Martigelinta ilo furan LLM API halkaasoo vLLM ugu adeegto isticmaaleyaal badan oo wada sheekaysi isla socda oo ka socda hal GPU oo leh wax soo saar sare.
Wadaagista nidaam dheer oo isla kumanaan codsi ah iyada oo la adeegsanayo prefix caching si loo habeeyo hal mar, maahan ku celcelin
Raadinta laydhka ordaya ama dhamaystirka muunad badan oo la wadaaga baloogyada KV isla markiiba
Ka-goynta qashinka xusuusta GPU-da ee kala-jajabinta si adeeg-bixiyuhu uu ugu xidhi karo kulamo badan oo isku mar ah isla qalab isku mid ah
Mustaqbalka Paged Feejignaanta iyo vLLM
vLLM waxa ay noqotay laf-dhabarta ka-soo-jeedinta il-furan, iyo fikradaha PagedAttention hadda waxay ka soo muuqdaan inta badan xidhmooyinka adeega. Filo caching qoto dheer oo horgale ah (dib-u-isticmaalka nidaamka kaydsan ee isticmaalayaasha oo dhan), hor-u-buuxinta kala-saaray oo kala-saar mashiinno kala duwan, siyaasado ka saarid oo caqli-gal ah, iyo is-dhexgal adag oo leh tiro-koob iyo malo-awaal. Marka daaqadaha macnaha guud ay u koraan malaayiin calaamado ah, maamulka KV ee hufan ee bogag leh ayaa xitaa udub dhexaad u noqda ilaalinta u adeegida la awoodi karo.
Ku dhaqangelinta
Maxay muhiim u tahay
- Qiimaha iyo miisaaniyada. Go'aamada qaab-dhismeedku waxay horseedaan waxqabadka iyo kharashka hawlgalka sannadaha.
- Go'aamo cad. Waxbarashada farsamada waxay ka caawisaa kooxaha inay doortaan xidhmo sax ah, ma aha oo kaliya kan ugu cusub.
- Xakamaynta tayada. Doorashooyinka injineernimada ee wanaagsan waxay yareeyaan shilalka la isku halleyn karo ee wax soo saarka.
Iska ilaali
- Hagaajinta hal bartilmaameed waxay qarin kartaa daciifnimada nidaamka ballaaran.
- Kaabayaasha dhaqaalaha iyo dayactirka inta badan waa la dhayalsadaa.
- Nabadgelyada iyo daldaloolada u fiirsashada ayaa kori kara marka nidaamyadu noqdaan kuwo aad u adag.
Tallaabooyinka xiga
- Qeex daahida, tayada, iyo bartilmaameedyada qiimaha ka hor inta aan la hirgelin.
- Benchmark marka la eego culeyska dhabta ah iyo xaaladaha xogta.
- La socodka qalabka khaladaadka, leexashada, iyo saamaynta isticmaalaha.
- U diyaari dib-u-noqoshada iyo dariiqyada jawaab-celinta dhacdada ka hor inta aanad miisaan.
Sii wad Sahaminta
Warqad bilaash ah
Hel warbixinta maalinlaha ah ee AI
Saddex sheeko oo la xaqiijiyay oo AI ah maalin kasta oo shaqo ah, oo lagu qoray Ingiriis fudud. Bilaash had iyo jeer, aan xayaysiis lahayn.
Hal iimayl maalin kasta oo shaqo ah. Ka bax hal gujin. Marna ma iibinno ama ma wadaagno ciwaankaaga.
Is tijaabi
Take the PagedAttention and vLLM quiz
Fikrad degdeg ah oo ku saabsan jawaab kasta, iyo shahaado la wadaajin karo oo leh aqoonsi la xaqiijin karo markaad ka gudubto koorso.
Taageer waxbarashada AI bilaashka ah. AI Understanding waa 501(c)(3) aan faa'iido doon ahayn — xayaysiis la'aan, albaab lacag ah ma jiro, had iyo jeer. Samee deeq
Su'aalaha soo noqnoqda
What is PagedAttention and vLLM?
PagedAttention manages transformer key/value caches using fixed-size blocks mapped from logical token positions. This reduces cache-allocation waste and supports sharing, while vLLM’s actual throughput depends on the workload and system.
Muxuu kaydiyaa 'KV cache' inta lagu jiro qoraalka qoraalka?
Kaydka KV waxa uu hayaa furaha iyo qiyamka vectors calaamad kasta oo hore, taas oo u oggolaanaysa moodalku inuu si buuxda u eego macnaha guud iyada oo aan dib loo xisaabin tallaabo kasta.
Waa maxay fikradda nidaamka hawlgalka dhiirigeliyay PagedAttention?
PagedAttention waxay soo amaahataa bogag xusuusta dalwaddii ah: khasnadda KV waxay u qaybsantaa bogag cabbir go'an oo meel kasta ku noolaan kara, oo lagu sawiray miis block ah.
Dhibaato noocee ah ayaa ku jirta qoondaynta kaydka KV ee dhaqameed ee PagedAttention xalliyo?
Kaydinta hal sariirood oo weyn codsi kasta, oo lagu qiyaaso dhererka ugu badan, waxay lumisay xaddi badan oo xusuusta GPU ah. Boggu wuxuu qoondeeyaa baloogyo yar yar marka loo baahdo, qashinka qashinka.
Sidee PagedAttention u ogolaataa soosaarayaal badan inay wadaagaan xusuusta degdeg guud?
Horgalayaasha isku midka ah (dardaarannada la wadaago ama laamaha raadinta isha) waxay tixraacayaan isla boggaga KV ee jireed, koobiyeynta kaliya marka laantu kala baxdo.
Halkee laga sameeyay vLLM iyo PagedAttention markii hore?
vLLM iyo PagedAttention algorithm waxay ka soo baxeen UC Berkeley warqad 2023 waxayna si dhakhso ah u noqdeen matoorka adeega il furan oo si weyn loo isticmaalo.
Sii wad waxbarashada
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