Uhlolojikelele
Inqolobane ye-KV igcina okhiye namagugu isiguquli esesivele senziwe ikhompuyutha ngakho-ke ayisebenzi kabusha kuwo wonke amathokheni amasha - kodwa ingafaka ibhaluni kumagigabhayithi. Ukulungiselelwa kwenqolobane ye-KV kuyashwabana futhi kulawule leyo nkumbulo ukuze amamodeli anikeze okuqukethwe okude kubasebenzisi abaningi ngesikhathi esisodwa.
I-KV Cache Optimization iyibhulokhi yokwakha yobuchwepheshe ethinta ikhwalithi yemodeli, izindleko zengqalasizinda, ukubambezeleka, nokuthembeka esikalini.
I-Deep Dive
Ku-transformer, ithokheni ngayinye entsha inakekela wonke amathokheni adlule ngokhiye bokunaka (K) kanye namanani (V). Ukubala kabusha u-K no-V kukho konke ukulandelana kuzo zonke izinyathelo kungaba yi-quadratic futhi kumoshe, ngakho amamodeli awagcine kunqolobane: inqolobane ye-KV. Okubi usayizi. Inqolobane ikhula ngokulandelana ngobude bokulandelana, usayizi wenqwaba, izendlalelo, namakhanda, ngakho-ke isicelo somongo omude singadla inkumbulo ye-GPU eningi kunezilinganiso zemodeli ngokwazo. Ukuthuthukisa kubhekana nalokhu ngama-engeli amaningana: inkumbulo ephejiwe (I-PagedAttention ye-vLLM) igcina inqolobane kumabhulokhi angahlangene ukuze kuqedwe ukuhlukana futhi inike amandla ukwabelana; izitolo ze-quantization K no-V ku-8-bit noma 4-bit; kanye nezinguquko zezakhiwo ezifana ne-Grouped-Query Attention (GQA) kanye ne-Multi-Query Attention (MQA) zivumela izinhloko zemibuzo eziningi zabelane ngamakhanda ambalwa okhiye/inani, ukusika usayizi wenqolobane emthonjeni.
I-Technical Insight
I-PagedAttention iboleka i-virtual-memory pageing ezinhlelweni zokusebenza: inqolobane ihlala kumabhulokhi anosayizi ongashintshi adwetshwe ngetafula lokubheka, ngakho-ke izicelo zisebenzisa amabhulokhi eziwadingayo kanye neziqalo ezifanayo (njengokwaziswa kwesistimu okwabelwanayo) zingakhomba amabhulokhi afanayo. I-Multi-head Latent Attention (MLA), esetshenziswa kumamodeli we-DeepSeek, icindezela i-K ne-V ibe ivekhtha ecashile okwabelwana ngayo, isika inkumbulo ngendlela emangalisayo kuyilapho igcina ukunemba.
Ukwenza I-KV Cache Optimization
Inqolobane ye-KV igcina okhiye namagugu isiguquli esesivele senziwe ikhompuyutha ngakho-ke ayisebenzi kabusha kuwo wonke amathokheni amasha - kodwa ingafaka ibhaluni kumagigabhayithi. Ukulungiselelwa kwenqolobane ye-KV kuyashwabana futhi kulawule leyo nkumbulo ukuze amamodeli anikeze okuqukethwe okude kubasebenzisi abaningi ngesikhathi esisodwa. I-KV Cache Optimization iyibhulokhi yokwakha yobuchwepheshe ethinta ikhwalithi yemodeli, izindleko zengqalasizinda, ukubambezeleka, nokuthembeka esikalini. Ukuze wakhe ukuqonda okujulile, phatha i-KV Cache Optimization njengemodeli yokusebenza, hhayi isici esisodwa: chaza imiphumela oyifunayo, ucacise ukucabanga, futhi uhlukanise lokho isistimu engakwenza ngokwethembeka kulokho okusadinga ukwahlulela kochwepheshe.
Empeleni, amaqembu aqinile asebenzisa i-KV Cache Optimization athuthukisa izakhiwo, idatha, nokukhetha kwengqalasizinda ngokumelene nokuthembeka nezindleko. Babhala imibandela yempumelelo ecacile, ukuhlola okuqhathaniswa nedatha engokoqobo nokugeleza komsebenzi, futhi baphindaphinde ngokusekelwe kumaphethini okuhluleka aqashiwe esikhundleni sokuwina kwebhentshimakhi yesikhathi esisodwa. Yilapho ukuqonda kwethiyori kuguquka kube amandla ahlala njalo kuwo wonke umkhiqizo, inqubomgomo, kanye nokusebenza.
Izinqumo zezakhiwo ziqhuba ukusebenza kanye nezindleko zokusebenza iminyaka. Ngesikhathi esifanayo, Ukuthuthukisa ibhentshimakhi eyodwa kungafihla ubuthakathaka obubanzi besistimu. Indlela eqine kakhulu iwukuhlanganisa isivinini sokuhlola nesiyalo sokuphatha: qhuba abashayeli bezindiza, bamba ubufakazi, ushicilele amalogi ezinqumo, futhi ubuyekeze izivikelo ngokuqhubekayo njengoba imodeli yokuziphatha, okulindelwe ngabasebenzisi, kanye nezimfuneko zokulawula zishintsha.
I-Strategic Impact
Izinqumo zezakhiwo ziqhuba ukusebenza kanye nezindleko zokusebenza iminyaka.
Izinqumo zezakhiwo ziqhuba ukusebenza kanye nezindleko zokusebenza iminyaka. Ekusetshenzisweni kwekhwalithi ephezulu, lokhu kuhunyushwa emithethweni yokusebenza elinganisekayo, imingcele yobunikazi, nemikhuba yokubuyekeza ephindelelayo ukuze amaqembu akwazi ukukala ukuzethemba esikhundleni sokukala ukungaqondakali.
Imfundo yobuchwepheshe isiza amaqembu ukuthi akhethe isitaki esifanele, hhayi nje esisha.
Imfundo yobuchwepheshe isiza amaqembu ukuthi akhethe isitaki esifanele, hhayi nje esisha. Ekusetshenzisweni kwekhwalithi ephezulu, lokhu kuhunyushwa emithethweni yokusebenza elinganisekayo, imingcele yobunikazi, nemikhuba yokubuyekeza ephindelelayo ukuze amaqembu akwazi ukukala ukuzethemba esikhundleni sokukala ukungaqondakali.
Izinketho ezingcono zobunjiniyela zinciphisa izehlakalo ezinokwethenjelwa ekukhiqizeni.
Izinketho ezingcono zobunjiniyela zinciphisa izehlakalo ezinokwethenjelwa ekukhiqizeni. Ekusetshenzisweni kwekhwalithi ephezulu, lokhu kuhunyushwa emithethweni yokusebenza elinganisekayo, imingcele yobunikazi, nemikhuba yokubuyekeza ephindelelayo ukuze amaqembu akwazi ukukala ukuzethemba esikhundleni sokukala ukungaqondakali.
Ukuqaliswa Komhlaba Wangempela
I-PagedAttention ye-vLLM isebenzisa izikhathi eziningi zokuxoxa ngesikhathi esisodwa ngokupakisha amabhlogo e-KV ngaphandle kokuhlukana kwenkumbulo.
Ukunakwa Kwemibuzo Ehlanganisiwe kumamodeli we-Llama ehlisa usayizi wenqolobane ye-KV ukuze izimo ezinde zilingane kumemori ye-GPU
Ukulinganisa inqolobane ye-KV ibe yi-8-bit (KV8) ukuze kuncishiswe inkumbulo yenqolobane ngohhafu ngesikhathi sokufingqa kwedokhumenti ende
Isiqalo sokugcina inqolobane esisebenzisa kabusha amabhulokhi e-KV wokwaziswa kwesistimu okwabelwana ngayo ezinkulungwaneni zezicelo ze-API
Amaphethini Okusebenzisa
KV Cache Optimization in practice
I-PagedAttention ye-vLLM isebenzisa izikhathi eziningi zengxoxo ngesikhathi esisodwa ngokupakisha amabhlogo e-KV ngaphandle kokuhlukana kwenkumbulo.
I-PagedAttention ye-vLLM isebenzisa izikhathi eziningi zengxoxo ngesikhathi esisodwa ngokupakisha amabhulokhi e-KV ngaphandle kokuhlukana kwenkumbulo Amathimba ngokuvamile athola imiphumela engcono lapho echaza izinga eliphezulu ngaphambili, egcina indlela yokukhuphuka yomuntu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
KV Cache Optimization in practice
Ukunakwa Kwemibuzo Ehlanganisiwe kumamodeli we-Llama ehlisa usayizi wenqolobane ye-KV ukuze izimo ezinde zilingane kumemori ye-GPU.
Ukunakwa Kwemibuzo Ehlanganisiwe kumamodeli we-Llama okunciphisa usayizi wenqolobane ye-KV ukuze izimo ezinde zilingane kumemori ye-GPU Amaqembu ngokuvamile athola imiphumela engcono uma echaza izinga eliphezulu ngaphambili, egcina indlela yokukhuphuka yomuntu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
KV Cache Optimization in practice
Ukulinganisa inqolobane ye-KV ibe yi-8-bit (KV8) ukuze kuncishiswe inkumbulo yenqolobane ngohhafu ngesikhathi sokufingqa kwedokhumenti ende.
Ukulinganisa inqolobane ye-KV iye ku-8-bit (KV8) ukuze kuncishiswe inkumbulo yenqolobane cishe ngohhafu phakathi nesikhathi sokufinyezwa kwemibhalo emide Amathimba ngokuvamile athola imiphumela engcono lapho echaza imingcele yekhwalithi ngaphambili, agcine indlela yokukhuphuka kwabantu yamacala asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
KV Cache Optimization in practice
Isiqalo sokugcina inqolobane esisebenzisa kabusha amabhulokhi e-KV wokwaziswa kwesistimu okwabelwana ngayo kuzo zonke izinkulungwane zezicelo ze-API.
Ukufakwa kunqolobane kwesiqalo okusebenzisa kabusha amabhulokhi e-KV okwaziswa kwesistimu okwabelwana ngayo ezinkulungwaneni zezicelo ze-API Amathimba ngokuvamile athola imiphumela engcono uma echaza imingcele yekhwalithi ngaphambili, egcina indlela yokukhuphuka yomuntu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
Izingozi & Guardrails
Ukuthuthukisa ibhentshimakhi eyodwa kungafihla ubuthakathaka obubanzi besistimu.
Izindleko zengqalasizinda nezokulungisa zivame ukubukelwa phansi.
Izikhala zokuphepha nokubonakala zingakhula njengoba izinhlelo ziba nzima kakhulu.
Ukuqalisa Umhlahlandlela
Chaza ukubambezeleka, ikhwalithi, nezindleko ezihlosiwe ngaphambi kokuqaliswa.
Chaza ukubambezeleka, ikhwalithi, nezindleko ezihlosiwe ngaphambi kokuqaliswa. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.
Ibhentshimakhi ngaphansi komthwalo wangempela nezimo zedatha.
Ibhentshimakhi ngaphansi komthwalo wangempela nezimo zedatha. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.
Ukuqapha amathuluzi amaphutha, ukukhukhuleka, nomthelela wabasebenzisi.
Ukuqapha amathuluzi amaphutha, ukukhukhuleka, nomthelela wabasebenzisi. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.
Lungiselela izindlela zokuhlehlisa nezigameko ngaphambi kokukala.
Lungiselela izindlela zokuhlehlisa nezigameko ngaphambi kokukala. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.