{"id":113552,"date":"2024-02-12T22:02:43","date_gmt":"2024-02-12T20:02:45","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/opublikovan-instrumentarij-zluda-pozvolyayushhij-zapuskat-cuda-prilozheniya-na-gpu-amd"},"modified":"2024-02-12T22:02:43","modified_gmt":"2024-02-12T20:02:45","slug":"opublikovan-instrumentarij-zluda-pozvolyayushhij-zapuskat-cuda-prilozheniya-na-gpu-amd","status":"publish","type":"post","link":"https:\/\/prohoster.info\/et\/blog\/novosti-interneta\/opublikovan-instrumentarij-zluda-pozvolyayushhij-zapuskat-cuda-prilozheniya-na-gpu-amd","title":{"rendered":"ZLUDA t\u00f6\u00f6riistakomplekt on avaldatud, v\u00f5imaldades CUDA rakenduste k\u00e4ivitamist AMD GPU-del.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Projekt ZLUDA on valmistanud avatud rakenduse CUDA tehnoloogia GPU AMD jaoks, v\u00f5imaldades k\u00e4itada muudetud CUDA-rakendusi l\u00e4hedase j\u00f5udlusega, nagu ka rakendusi, mis t\u00f6\u00f6tavad ilma kihita. Avaldatud t\u00f6\u00f6riistakomplekt tagab binaarse \u00fchilduvuse olemasolevate CUDA-rakendustega, mis on kompileeritud NVIDIA GPU ja CUDA kompilaatori abil. Rakendus t\u00f6\u00f6tab AMD arendatava ROCm ja HIP (Heterogeneous-computing Interface for Portability) ajakava kohal. Projekti kood on kirjutatud Rust keeles ning seda levitatakse MIT ja Apache 2.0 litsentside alusel. Toetatakse t\u00f6\u00f6d Linuxis ja Windowsis. <\/p>\n

CUDA rakenduste korraldamise kiht AMD GPU s\u00fcsteemides on arendatud viimased kaks aastat, kuid projekt on vanema ajalooga ja loodi algselt CUDA t\u00f6\u00f6 kindlustamiseks Intel GPU-del. GPU toetamist muudeti seet\u00f5ttu, et ZLUDA arendaja oli algselt Intel'i t\u00f6\u00f6taja, kuid 2021. aastal pidas ettev\u00f5te CUDA-rakenduste k\u00e4ivitamise v\u00f5imalust Intel GPU-del \u00e4rihuvide seisukohalt ebaoluliseks ning ei sooritanud initsiatiivi arendamist. <\/p>\n

2022. aasta alguses lahkus arendaja Intelist ja s\u00f5lmis lepingu AMD-ga, et arendada CUDA \u00fchilduvuse kihti. AMD palus arenduse k\u00e4igus mitte avaldada huvi ZLUDA projekti vastu ning mitte teha commite avalikku ZLUDA repositooriumisse. Kahe aasta p\u00e4rast otsustas AMD, et CUDA-rakenduste k\u00e4ivitamine AMD GPU-del ei ole \u00e4ri jaoks huvitav, mis lepingutingimuste kohaselt v\u00f5imaldas arendajal oma t\u00f6\u00f6d avada. Kuna GPU tootjad l\u00f5petasid projekti rahastamise, s\u00f5ltub selle saatus n\u00fc\u00fcd kogukonna huvist ja pakkumistest teistele ettev\u00f5tetele. Ilma v\u00e4lise toeta saab projekt areneda ainult autorile isiklikult huvipakkuvates suundades, n\u00e4iteks DLSS (Deep Learning Super Sampling). <\/p>\n

Praeguses vormis hinnatakse teostuse kvaliteedi taset alfa-versiooniks. Sellegipoolest saab ZLUDA juba kasutada paljude CUDA-rakenduste, sealhulgas Geekbench, 3DF Zephyr, Blender, Reality Capture, LAMMPS, NAMD, waifu2x, OpenFOAM ja Arnold, k\u00e4ivitamiseks. Tagatud on minimaalne tugi primitiividele ja teekidele cuDNN, cuBLAS, cuSPARSE, cuFFT, NCCL ja NVML. <\/p>\n

CUDA-rakenduste esimene k\u00e4ivitamine ZLUDA all toimimise ajal toimub m\u00e4rgatavate viivitustega, kuna ZLUDA kompileerib GPU koodi. J\u00e4rgmiste k\u00e4ivitustega selline viivitus puudub, kuna kompileeritud kood salvestatakse vahem\u00e4llu. Kompileeritud koodi t\u00e4itmise ajal on j\u00f5udlus l\u00e4hedane natiivsele. Geekbench paketi t\u00e4itmisel AMD Radeon 6800 XT GPU-l saavutas CUDA testikomplekt, mille t\u00f6\u00f6tlemiseks kasutati ZLUDA-d, m\u00e4rgatavalt parema j\u00f5udluse kui OpenCL-p\u00f5hine variant.

\"ZLUDA<\/center> <\/p>\n

ZLUDA toetab ametlikku CUDA Driver API-d ja l\u00e4bi tagasip\u00f6\u00f6ratud inseneriabi uuritud dokumenteerimata CUDA API osa, asendades funktsioonikutsed sarnaste funktsioonidega, mida pakub HIP runtime, mis sarnaneb suuresti CUDA-le. N\u00e4iteks funktsioon cuDeviceGetAttribute() asendatakse hipDeviceGetAttribute()-ga. Sarnaselt tagatakse ka \u00fchilduvus NVIDIA raamatukogudega, nagu NVML, cuBLAS ja cuSPARSE; neile raamatukogudele pakub ZLUDA suhtlevad raamatukogud sama nime ja sama funktsioonide koguga, mis on \u00fcles ehitatud sarnaste AMD raamatukogude peale. <\/p>\n

GPU rakenduste kood, kompileeritud PTX (Paralleelne Niit T\u00e4itmine) formaati, t\u00f5lgitakse spetsiaalse kompilaatori abil alguses LLVM IR vaheformaati, mille alusel genereeritakse binaarne kood AMD GPU-dele.

\"ZLUDA<\/center>
\n
Allikas: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

\u041f\u0440\u043e\u0435\u043a\u0442 ZLUDA \u043f\u043e\u0434\u0433\u043e\u0442\u043e\u0432\u0438\u043b \u043e\u0442\u043a\u0440\u044b\u0442\u0443\u044e \u0440\u0435\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044e \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0438 CUDA \u0434\u043b\u044f GPU AMD, \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u044e\u0449\u0443\u044e \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0442\u044c \u043d\u0435\u043c\u043e\u0434\u0438\u0444\u0438\u0446\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0435 CUDA-\u043f\u0440\u0438\u043b\u043e\u0436\u0435\u043d\u0438\u044f \u0441 \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u044c\u044e, \u0431\u043b\u0438\u0437\u043a\u043e\u0439 \u043a \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u0438 \u043f\u0440\u0438\u043b\u043e\u0436\u0435\u043d\u0438\u0439, \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0435\u043c\u044b\u0445 \u0431\u0435\u0437 \u043f\u0440\u043e\u0441\u043b\u043e\u0435\u043a. \u041e\u043f\u0443\u0431\u043b\u0438\u043a\u043e\u0432\u0430\u043d\u043d\u044b\u0439 \u0438\u043d\u0441\u0442\u0440\u0443\u043c\u0435\u043d\u0442\u0430\u0440\u0438\u0439 \u043e\u0431\u0435\u0441\u043f\u0435\u0447\u0438\u0432\u0430\u0435\u0442 \u0431\u0438\u043d\u0430\u0440\u043d\u0443\u044e \u0441\u043e\u0432\u043c\u0435\u0441\u0442\u0438\u043c\u043e\u0441\u0442\u044c \u0441 \u0441\u0443\u0449\u0435\u0441\u0442\u0432\u0443\u044e\u0449\u0438\u043c\u0438 CUDA-\u043f\u0440\u0438\u043b\u043e\u0436\u0435\u043d\u0438\u044f\u043c\u0438, \u0441\u043e\u0431\u0440\u0430\u043d\u043d\u044b\u043c\u0438 \u043f\u0440\u0438 \u043f\u043e\u043c\u043e\u0449\u0438 \u043a\u043e\u043c\u043f\u0438\u043b\u044f\u0442\u043e\u0440\u0430 CUDA \u0434\u043b\u044f GPU NVIDIA. \u0420\u0435\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f \u0440\u0430\u0431\u043e\u0442\u0430\u0435\u0442 \u043f\u043e\u0432\u0435\u0440\u0445 \u0440\u0430\u0437\u0432\u0438\u0432\u0430\u0435\u043c\u043e\u0433\u043e \u043a\u043e\u043c\u043f\u0430\u043d\u0438\u0435\u0439 AMD \u0441\u0442\u0435\u043a\u0430 ROCm \u0438 runtime HIP (Heterogeneous-computing Interface for Portability). \u041a\u043e\u0434 […]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":113553,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-113552","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-novosti-interneta"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\n","aioseo_head_json":{"title":"\ud83e\udd47Avaldatud ZLUDA t\u00f6\u00f6riistakomplekt, mis v\u00f5imaldab k\u00e4itada CUDA rakendusi AMD GPU-del | ProHoster","description":"ZLUDA projekt on valmistanud ette avatud rakenduse CUDA tehnoloogia AMD GPU-dele, mis v\u00f5imaldab k\u00e4itada modifitseerimata CUDA rakendusi, saavutades j\u00f5udluse, mis on l\u00e4hedane rakenduste j\u00f5udlusele, mida k\u00e4itatakse ilma plastide kasutamiseta. Avaldatud t\u00f6\u00f6riistakomplekt tagab binaarse \u00fchilduvuse olemasolevate CUDA rakendustega, mis on koostatud NVIDIA GPU-dele m\u00f5eldud CUDA kompilaatoriga. Lahendus t\u00f6\u00f6tab AMD arendamisel oleva ROCm stacki ja HIP (Heterogeensete Arvutuste \u00dchisinteface) runtime'i peal. 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CUDA-\u043f\u0440\u0438\u043b\u043e\u0436\u0435\u043d\u0438\u044f \u043d\u0430 GPU AMD | ProHoster","og:description":"\u041f\u0440\u043e\u0435\u043a\u0442 ZLUDA \u043f\u043e\u0434\u0433\u043e\u0442\u043e\u0432\u0438\u043b \u043e\u0442\u043a\u0440\u044b\u0442\u0443\u044e \u0440\u0435\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044e \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0438 CUDA \u0434\u043b\u044f GPU AMD, \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u044e\u0449\u0443\u044e \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0442\u044c \u043d\u0435\u043c\u043e\u0434\u0438\u0444\u0438\u0446\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0435 CUDA-\u043f\u0440\u0438\u043b\u043e\u0436\u0435\u043d\u0438\u044f \u0441 \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u044c\u044e, \u0431\u043b\u0438\u0437\u043a\u043e\u0439 \u043a 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\u043a\u043e\u043c\u043f\u0438\u043b\u044f\u0442\u043e\u0440\u0430 CUDA \u0434\u043b\u044f GPU NVIDIA. \u0420\u0435\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f \u0440\u0430\u0431\u043e\u0442\u0430\u0435\u0442 \u043f\u043e\u0432\u0435\u0440\u0445 \u0440\u0430\u0437\u0432\u0438\u0432\u0430\u0435\u043c\u043e\u0433\u043e \u043a\u043e\u043c\u043f\u0430\u043d\u0438\u0435\u0439 AMD \u0441\u0442\u0435\u043a\u0430 ROCm \u0438 runtime HIP (Heterogeneous-computing Interface for Portability). 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