{"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\/sq\/blog\/news\/opublikovan-instrumentarij-zluda-pozvolyayushhij-zapuskat-cuda-prilozheniya-na-gpu-amd","title":{"rendered":"ZLUDA ka b\u00ebr\u00eb publike nj\u00eb mjet q\u00eb mund\u00ebson ekzekutimin e aplikacioneve CUDA n\u00eb GPU-t\u00eb AMD","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Projekti ZLUDA p\u00ebrgatiti nj\u00eb realizim t\u00eb hapur t\u00eb teknologjis\u00eb CUDA p\u00ebr GPU-t\u00eb AMD, q\u00eb lejon ekzekutimin e aplikacioneve CUDA t\u00eb pa modifikuara me nj\u00eb performanc\u00eb t\u00eb ngjashme me at\u00eb t\u00eb aplikacioneve q\u00eb ekzekutohen pa nd\u00ebrmjet\u00ebs. Mjeti i botuar ofron p\u00ebrputhshm\u00ebri binare me aplikacionet ekzistuese CUDA t\u00eb nd\u00ebrtuara me ndihm\u00ebn e kompajlerit CUDA p\u00ebr GPU-t\u00eb NVIDIA. Realizimi punon mbi grumbullin e zhvilluar nga kompania AMD, ROCm dhe runtime HIP (Heterogeneous-computing Interface for Portability). Kodi i projektit \u00ebsht\u00eb shkruar n\u00eb gjuh\u00ebn Rust dhe shp\u00ebrndahet n\u00ebn licencat MIT dhe Apache 2.0. P\u00ebrkrahja p\u00ebr punimin n\u00eb Linux dhe Windows \u00ebsht\u00eb e siguruar. <\/p>\n

Shtresa p\u00ebr organizimin e pun\u00ebs CUDA n\u00eb sistemet me GPU AMD \u00ebsht\u00eb zhvilluar p\u00ebr dy vitet e fundit, por projekti ka nj\u00eb histori m\u00eb t\u00eb gjat\u00eb dhe fillimisht \u00ebsht\u00eb krijuar p\u00ebr t\u00eb siguruar funksionimin e CUDA n\u00eb GPU-t\u00eb Intel. Ndryshimi i politik\u00ebs s\u00eb mb\u00ebshtetjes p\u00ebr GPU tregohet nga fakti q\u00eb n\u00eb fillim zhvilluesi ZLUDA ka qen\u00eb nj\u00eb punonj\u00ebs i Intel, por n\u00eb vitin 2021 kjo kompani vler\u00ebsoi mund\u00ebsin\u00eb e ekzekutimit t\u00eb aplikacioneve CUDA n\u00eb GPU-t\u00eb Intel si t\u00eb pa interesuar p\u00ebr biznesin dhe nuk e vazhdoi zhvillimin e iniciativ\u00ebs. <\/p>\n

N\u00eb fillim t\u00eb vitit 2022, zhvilluesi dha dor\u00ebheqjen nga Intel dhe n\u00ebnshkroi nj\u00eb kontrat\u00eb me kompanin\u00eb AMD p\u00ebr zhvillimin e shtres\u00ebs p\u00ebr p\u00ebrputhshm\u00ebri me CUDA. Kompania AMD k\u00ebrkoi gjat\u00eb zhvillimit q\u00eb t\u00eb mos publikohet interesimi i AMD p\u00ebr projektin ZLUDA dhe t\u00eb mos b\u00ebhen komitete n\u00eb depozita publike t\u00eb ZLUDA. Pas dy vjet\u00ebsh, kompania AMD vendosi se ekzekutimi i aplikacioneve CUDA n\u00eb GPU-t\u00eb AMD nuk p\u00ebrb\u00ebn nj\u00eb interes p\u00ebr biznesin, gj\u00eb q\u00eb sipas kushteve t\u00eb kontrat\u00ebs i lejoj zhvilluesit t\u00eb publikoj\u00eb punimet e tij. Duke qen\u00eb se prodhuesit e GPU-ve kan\u00eb ndaluar financimin e projektit, e ardhmja e tij tani varet nga interesat e komunitetit dhe rinjohja e p\u00ebrvojave nga kompani t\u00eb tjera. Pa mb\u00ebshtetje t\u00eb jashtme, projekti do t\u00eb zhvillohet vet\u00ebm n\u00eb drejtimet q\u00eb jan\u00eb interesante p\u00ebr autorin, si DLSS (Deep Learning Super Sampling). <\/p>\n

N\u00eb form\u00ebn aktuale, niveli i cil\u00ebsis\u00eb s\u00eb realizimit vler\u00ebsohet si nj\u00eb version alfa. Megjithat\u00eb, ZLUDA tashm\u00eb mund t\u00eb p\u00ebrdoret p\u00ebr ekzekutimin e shum\u00eb aplikacioneve CUDA, duke p\u00ebrfshir\u00eb Geekbench, 3DF Zephyr, Blender, Reality Capture, LAMMPS, NAMD, waifu2x, OpenFOAM dhe Arnold. \u00cbsht\u00eb siguruar mb\u00ebshtetje minimale p\u00ebr primitive dhe biblioteka si cuDNN, cuBLAS, cuSPARSE, cuFFT, NCCL dhe NVML. <\/p>\n

Kursi i par\u00eb i aplikacioneve CUDA n\u00ebn menaxhimin e ZLUDA ka vonesa t\u00eb dukshme, pasi ZLUDA b\u00ebn kompilimin e kodit GPU. N\u00eb startet e m\u00ebpasshme, nj\u00eb vones\u00eb e till\u00eb nuk ekziston, pasi kodi i kompiluar ruhet n\u00eb cache. Gjat\u00eb ekzekutimit t\u00eb kodit t\u00eb kompiluar, performanca \u00ebsht\u00eb e ngjashme me at\u00eb t\u00eb natyrshme. Kur paket\u00ebn Geekbench e ekzekuton GPU AMD Radeon 6800 XT, varianti i testit p\u00ebr CUDA, i realizuar me ZLUDA, tregoi performanc\u00eb duksh\u00ebm m\u00eb t\u00eb lart\u00eb se varianti bazuar n\u00eb OpenCL.

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

\u041f\u043e\u0434\u0434\u0435\u0440\u0436\u043a\u0430 \u043e\u0444\u0438\u0446\u0438\u0430\u043b\u044c\u043d\u043e\u0433\u043e CUDA Driver API \u0438 \u0438\u0437\u0443\u0447\u0435\u043d\u043d\u043e\u0439 \u043f\u0440\u0438 \u043f\u043e\u043c\u043e\u0449\u0438 \u043e\u0431\u0440\u0430\u0442\u043d\u043e\u0433\u043e \u0438\u043d\u0436\u0438\u043d\u0438\u0440\u0438\u043d\u0433\u0430 \u0447\u0430\u0441\u0442\u0438 \u043d\u0435\u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0433\u043e API CUDA \u0440\u0435\u0430\u043b\u0438\u0437\u043e\u0432\u0430\u043d\u0430 \u0432 ZLUDA \u0447\u0435\u0440\u0435\u0437 \u0437\u0430\u043c\u0435\u043d\u0443 \u0432\u044b\u0437\u043e\u0432\u043e\u0432 \u0444\u0443\u043d\u043a\u0446\u0438\u0439 \u043d\u0430 \u0430\u043d\u0430\u043b\u043e\u0433\u0438\u0447\u043d\u044b\u0435 \u0444\u0443\u043d\u043a\u0446\u0438\u0438, \u043f\u0440\u0435\u0434\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u043c\u044b\u0435 \u0432 HIP runtime, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u0432\u043e \u043c\u043d\u043e\u0433\u043e\u043c \u043f\u043e\u0445\u043e\u0434\u0438\u0442 \u043d\u0430 CUDA. \u041d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u0444\u0443\u043d\u043a\u0446\u0438\u044f cuDeviceGetAttribute() \u0437\u0430\u043c\u0435\u043d\u044f\u0435\u0442\u0441\u044f \u043d\u0430 hipDeviceGetAttribute(). \u041f\u043e\u0445\u043e\u0436\u0438\u043c \u043e\u0431\u0440\u0430\u0437\u043e\u043c \u043e\u0431\u0435\u0441\u043f\u0435\u0447\u0438\u0432\u0430\u0435\u0442\u0441\u044f \u0438 \u0441\u043e\u0432\u043c\u0435\u0441\u0442\u0438\u043c\u043e\u0441\u0442\u044c \u0441 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0430\u043c\u0438 NVIDIA, \u0442\u0430\u043a\u0438\u043c\u0438 \u043a\u0430\u043a NVML, cuBLAS \u0438 cuSPARSE, — \u0434\u043b\u044f \u043f\u043e\u0434\u043e\u0431\u043d\u044b\u0445 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a \u0432 ZLUDA \u043f\u0440\u0435\u0434\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u044e\u0442\u0441\u044f \u0442\u0440\u0430\u043d\u0441\u043b\u0438\u0440\u0443\u044e\u0449\u0438\u0435 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 \u0441 \u0442\u0435\u043c \u0436\u0435 \u0438\u043c\u0435\u043d\u0435\u043c \u0438 \u0442\u0435\u043c \u0436\u0435 \u043d\u0430\u0431\u043e\u0440\u043e\u043c \u0444\u0443\u043d\u043a\u0446\u0438\u0439, \u043f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u043d\u044b\u0435 \u0432 \u0432\u0438\u0434\u0435 \u043d\u0430\u0434\u0441\u0442\u0440\u043e\u0435\u043a \u043d\u0430\u0434 \u043f\u043e\u0445\u043e\u0436\u0438\u043c\u0438 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0430\u043c\u0438 AMD. <\/p>\n

Kodi GPU i aplikacioneve, i kompiluar n\u00eb p\u00ebrfaq\u00ebsimin PTX (Ekzekutimi i Thread-eve Paralel), translirohet nga nj\u00eb kompilues special fillimisht n\u00eb nj\u00eb p\u00ebrfaq\u00ebsim t\u00eb p\u00ebrkohsh\u00ebm LLVM IR, mbi t\u00eb cilin gjenerohet kodi binar p\u00ebr GPU AMD.

\"ZLUDA<\/center>
\n
Burimi: 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-news"],"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\udd47U publikua mjeti ZLUDA, i cili lejon ekzekutimin e aplikacioneve CUDA n\u00eb GPU AMD | ProHoster","description":"Projekti ZLUDA ka p\u00ebrgatitur nj\u00eb realizim t\u00eb hapur t\u00eb teknologjis\u00eb CUDA p\u00ebr GPU AMD, i cili lejon ekzekutimin e aplikacioneve CUDA t\u00eb pa modifikuara me performanc\u00eb, e cila \u00ebsht\u00eb af\u00ebrsisht e ngjashme me performanc\u00ebn e aplikacioneve t\u00eb ekzekutuara pa t\u00eb.","canonical_url":"https:\/\/prohoster.info\/sq\/blog\/news\/opublikovan-instrumentarij-zluda-pozvolyayushhij-zapuskat-cuda-prilozheniya-na-gpu-amd","robots":"max-image-preview:large","keywords":"","webmasterTools":{"miscellaneous":""},"schema":null,"og:locale":"sq_AL","og:site_name":"ProHoster | \u041a\u0443\u043f\u0438\u0442\u044c \u043d\u0430\u0434\u0435\u0436\u043d\u044b\u0439 \u0445\u043e\u0441\u0442\u0438\u043d\u0433 \u0434\u043b\u044f \u0441\u0430\u0439\u0442\u043e\u0432 \u0441 \u0437\u0430\u0449\u0438\u0442\u043e\u0439 \u043e\u0442 DDoS, VPS VDS \u0441\u0435\u0440\u0432\u0435\u0440\u044b","og:type":"article","og:title":"\ud83e\udd47\u041e\u043f\u0443\u0431\u043b\u0438\u043a\u043e\u0432\u0430\u043d \u0438\u043d\u0441\u0442\u0440\u0443\u043c\u0435\u043d\u0442\u0430\u0440\u0438\u0439 ZLUDA, \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u044e\u0449\u0438\u0439 \u0437\u0430\u043f\u0443\u0441\u043a\u0430\u0442\u044c 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 \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.","og:url":"https:\/\/prohoster.info\/sq\/blog\/news\/opublikovan-instrumentarij-zluda-pozvolyayushhij-zapuskat-cuda-prilozheniya-na-gpu-amd","og:image":"https:\/\/prohoster.info\/wp-content\/uploads\/2021\/11\/logo-350.jpg","og:image:secure_url":"https:\/\/prohoster.info\/wp-content\/uploads\/2021\/11\/logo-350.jpg","og:image:width":350,"og:image:height":350,"article:published_time":"2024-02-12T20:02:45+00:00","article:modified_time":"2024-02-12T20:02:45+00:00","article:publisher":"https:\/\/www.facebook.com\/prohoster","article:author":"https:\/\/www.facebook.com\/prohoster"},"aioseo_meta_data":[],"gt_translate_keys":[{"key":"link","format":"url"}],"_links":{"self":[{"href":"https:\/\/prohoster.info\/sq\/wp-json\/wp\/v2\/posts\/113552","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/prohoster.info\/sq\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/prohoster.info\/sq\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/prohoster.info\/sq\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/prohoster.info\/sq\/wp-json\/wp\/v2\/comments?post=113552"}],"version-history":[{"count":0,"href":"https:\/\/prohoster.info\/sq\/wp-json\/wp\/v2\/posts\/113552\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/prohoster.info\/sq\/wp-json\/wp\/v2\/media\/113553"}],"wp:attachment":[{"href":"https:\/\/prohoster.info\/sq\/wp-json\/wp\/v2\/media?parent=113552"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/prohoster.info\/sq\/wp-json\/wp\/v2\/categories?post=113552"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/prohoster.info\/sq\/wp-json\/wp\/v2\/tags?post=113552"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}