Uhlolojikelele
Indlela uhlaka lwe-AI oluyaba ngayo, luphinde lusebenzise, futhi lufune kabusha inkumbulo ekhawulelwe ku-GPU, nokuthi kungani izikhala ezisele (ukuhlukaniswa) zingabangela amaphutha angaphandle kwenkumbulo ngisho noma inkumbulo eningi isasele. Ukuyiqonda kuyisihluthulelo sokufaka amamodeli amakhulu nokugwema ukuphahlazeka okungaqondakali.
I-GPU Memory Management and Fragmentation iyibhulokhi yokwakha yobuchwepheshe ethinta ikhwalithi yemodeli, izindleko zengqalasizinda, ukubambezeleka, nokuthembeka esikalini.
I-Deep Dive
Imemori ye-GPU igxilile futhi iyigugu: ikhadi lingase libe nengqikithi engu-24, 80, noma 192 GB, okwabelwana ngayo ngezisindo zemodeli, ukwenziwa kusebenze, ama-gradient, izifunda ze-optimizer, namabhafa esikhashana. Ukushayela umshayeli ukuthi anikeze inkumbulo kukho konke ukusebenza kuzohamba kancane, ngakho izinhlaka ezifana ne-PyTorch zisebenzisa i-caching allocator ebamba amabhulokhi amakhulu ngaphambili futhi ikhiphe izingcezu ezincane, bese igcina izingcezu ezikhululiwe echibini ukuze ziphinde zisetshenziswe. Okubanjwayo kuwukuhlukaniswa: njengoba ama-tensor anosayizi abahlukahlukene abiwa futhi akhululwe, indawo yamahhala ihlukana ibe izingcezu ezihlakazekile. Ungaba no-5 GB wamahhala usuwonke kodwa wehluleke ukunikeza i-tensor engu-2 GB esondelene ngoba alikho igebe elilodwa elikhulu ngokwanele. Yingakho ukuqeqeshwa kungaphahlazeka ngamaphutha angaphandle kwenkumbulo naphezu kwe-headroom ebonakala itholakala.
I-Technical Insight
Isabelo senqolobane se-CUDA se-PyTorch sihlukanisa inkumbulo ibe yimifudlana yamabhulokhi futhi siphinde sisebenzise amabhulokhi akhululiwe afana nosayizi abaceliwe, sigwema izingcingo ezibizayo ze-cudaMalloc/cudaFree. Ukuhlukaniswa kuvela lapho amabhlogo ahlukanisiwe engakwazi ukuphinda ahlanganiswe. Amathuluzi afana ne-torch.cuda.empty_cache, inketho ye-PYTORCH_CUDA_ALLOC_CONF expandable_segments, nosizo lwezifinyezo zememori. Izindlela ezintsha ziboleka imibono yenkumbulo ebonakalayo, yenze imephu yamakhasi abonakalayo angahlangani abe ububanzi obubonakalayo obuhlangene ukuze izicelo ezinkulu ziphumelele naphezu kokuhlukana.
I-Mastering GPU Memory Management and Fragmentation
Indlela uhlaka lwe-AI oluyaba ngayo, luphinde lusebenzise, futhi lufune kabusha inkumbulo ekhawulelwe ku-GPU, nokuthi kungani izikhala ezisele (ukuhlukaniswa) zingabangela amaphutha angaphandle kwenkumbulo ngisho noma inkumbulo eningi isasele. Ukuyiqonda kuyisihluthulelo sokufaka amamodeli amakhulu nokugwema ukuphahlazeka okungaqondakali. I-GPU Memory Management and Fragmentation iyibhulokhi yokwakha yobuchwepheshe ethinta ikhwalithi yemodeli, izindleko zengqalasizinda, ukubambezeleka, nokuthembeka esikalini. Ukuze wakhe ukuqonda okujulile, phatha i-GPU Memory Management and Fragmentation 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-GPU Memory Management and Fragmentation 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
Ukugijima kokuqeqeshwa okushayisana ne-'CUDA ephumile kumemori' naphezu kwenkumbulo egodliwe ebonisa isikhala esikhululekile, elungiswe ngokusetha i-PYTORCH_CUDA_ALLOC_CONF ukuze kunikwe amandla amasegimenti anwebekayo.
Kusetshenziswa i-torch.cuda.memory_summary noma isifinyezo sememori ukuxilonga ukuthi imaphi ama-tensor nokuhlukaniswa okudla i-GPU's 80 GB.
I-PagedAttention ye-vLLM ilawula inqolobane ye-KV yokunaka emakhasini anosayizi ongashintshi ukuze inikeze izicelo eziningi zengxoxo ngesikhathi esisodwa ngaphandle kokumosha inkumbulo.
Ukwehlisa usayizi weqoqo noma ukunika amandla ukuhlola kwegradient ukuze kunqandwe inkumbulo yokwenza kusebenze futhi kugwenywe ukuhluleka okuphuma kwenkumbulo okuqhutshwa ukuhlukana.
Amaphethini Okusebenzisa
I-GPU Memory Management kanye nokuhlukaniswa ngokusebenza
Ukugijima kokuqeqeshwa okushayisana ne-'CUDA ephumile kumemori' naphezu kwenkumbulo egodliwe ebonisa isikhala esikhululekile, elungiswe ngokusetha i-PYTORCH_CUDA_ALLOC_CONF ukuze kunikwe amandla amasegimenti anwebekayo.
Ukuqeqeshwa okushayisana ne-'CUDA ephumile enkumbulweni' naphezu kwenkumbulo egodliwe ebonisa indawo ekhululekile, elungiswa ngokusetha i-PYTORCH_CUDA_ALLOC_CONF ukuze kunikwe amandla amasegimenti anwebekayo Amathimba ngokuvamile athola imiphumela engcono uma echaza imikhawulo yekhwalithi ngaphambili, agcina indlela yokukhuphuka yomuntu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
I-GPU Memory Management kanye nokuhlukaniswa ngokusebenza
Kusetshenziswa i-torch.cuda.memory_summary noma isifinyezo sememori ukuxilonga ukuthi imaphi ama-tensor nokuhlukaniswa okudla i-GPU's 80 GB.
Kusetshenziswa i-torch.cuda.memory_summary noma isifinyezo senkumbulo ukuze kutholwe ukuthi yiziphi izithasiselo neziqephu ezidla amaThimba we-GPU angu-80 GB ngokuvamile athola imiphumela engcono lapho echaza imingcele yekhwalithi ngaphambili, agcine indlela yokukhuphuka yomuntu yamacala asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
I-GPU Memory Management kanye nokuhlukaniswa ngokusebenza
I-PagedAttention ye-vLLM ilawula inqolobane ye-KV yokunaka emakhasini anosayizi ongashintshi ukuze inikeze izicelo eziningi zengxoxo ngesikhathi esisodwa ngaphandle kokumosha inkumbulo.
I-PagedAttention ye-vLLM elawula inqolobane ye-KV yokunaka emakhasini anosayizi ongashintshi ukuze isebenze izicelo eziningi zengxoxo ngesikhathi esisodwa ngaphandle kokumosha inkumbulo Amaqembu ngokuvamile athola imiphumela engcono lapho echaza izinga eliphezulu ngaphambili, egcina indlela yokukhuphuka kwabantu yamacala abucayi, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
I-GPU Memory Management kanye nokuhlukaniswa ngokusebenza
Ukwehlisa usayizi weqoqo noma ukunika amandla ukuhlola kwegradient ukuze kunqandwe inkumbulo yokwenza kusebenze futhi kugwenywe ukuhluleka okuphuma kwenkumbulo okuqhutshwa ukuhlukana.
Ukwehlisa usayizi weqoqo noma ukunika amandla ukuhlola kwe-gradient ukuze kunqandwe inkumbulo yokusebenzisa futhi kugweme ukwehluleka okuphuma kwenkumbulo okuqhutshwa ukuhlukana Amaqembu ngokuvamile athola imiphumela engcono uma echaza imikhawulo yekhwalithi ngaphambili, agcine 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.