{"id":54686,"date":"2020-01-01T00:00:00","date_gmt":"2019-12-31T21:00:00","guid":{"rendered":"https:\/\/prohoster.info\/blog\/blog_prohoster\/5-8-mln-iops-zachem-tak-mnogo"},"modified":"2020-02-18T14:02:44","modified_gmt":"2020-02-18T11:02:44","slug":"5-8-mln-iops-zachem-tak-mnogo","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sq\/blog\/administrirovanie\/5-8-mln-iops-zachem-tak-mnogo","title":{"rendered":"5.8 milion IOPS: p\u00ebrse ka kaq shum\u00eb?","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

P\u00ebrsh\u00ebndetje Habr! Setet e t\u00eb dh\u00ebnave p\u00ebr Big Data dhe m\u00ebsim mahnit\u00ebs po rriten eksponencialisht dhe duhet t\u00eb arrijm\u00eb t'i p\u00ebrpunojm\u00eb ato. Postimi yn\u00eb flet p\u00ebr nj\u00eb tjet\u00ebr teknologji inovative n\u00eb fush\u00ebn e llogaritjeve me performanc\u00eb t\u00eb lart\u00eb (HPC, High Performance Computing), e ekspozuar n\u00eb stend\u00ebn e Kingston n\u00eb Supercomputing-2019<\/a><\/noindex>. Kjo \u00ebsht\u00eb aplikimi i sistemeve t\u00eb avancuara t\u00eb ruajtjes s\u00eb t\u00eb dh\u00ebnave (S\u0425D) n\u00eb serverat me procesor\u00eb grafore (GPU) dhe teknologjin\u00eb e autobusit GPUDirect Storage. Fal\u00eb shk\u00ebmbimit t\u00eb t\u00eb dh\u00ebnave n\u00eb m\u00ebnyr\u00eb t\u00eb drejtp\u00ebrdrejt\u00eb midis S\u0425D dhe GPU, duke kaluar jasht\u00eb CPU, ngarkesa e t\u00eb dh\u00ebnave n\u00eb p\u00ebrshpejtuesit GPU p\u00ebrshpejtohet n\u00eb mas\u00eb, prandaj aplikacionet Big Data realizohen n\u00eb maksimumin e performanc\u00ebs q\u00eb ofrojn\u00eb GPU. Nga ana tjet\u00ebr, zhvilluesit e sistemeve HPC jan\u00eb t\u00eb interesuar p\u00ebr arritjet n\u00eb fush\u00ebn e S\u0425D me shpejt\u00ebsi t\u00eb lart\u00eb hyrjeje\/daljeje \u2014 t\u00eb tilla si ato q\u00eb prodhon Kingston.<\/p>\n

\"5.8
\n<\/a><\/noindex><\/p>\n

Performanca e GPU-s\u00eb tejkalon ngarkes\u00ebn e t\u00eb dh\u00ebnave <\/h2>\n

\nQ\u00eb nga krijimi i CUDA n\u00eb vitin 2007 \u2014 arkitektura programore-hardware p\u00ebr llogaritje paralele mbi baz\u00ebn e GPU p\u00ebr zhvillimin e aplikacioneve me q\u00ebllim t\u00eb p\u00ebrgjithsh\u00ebm, kapacitetet hardware t\u00eb vet\u00eb GPU-ve jan\u00eb rritur jasht\u00ebzakonisht. Sot, GPU-t\u00eb gjejn\u00eb gjithnj\u00eb e m\u00eb shum\u00eb aplikime n\u00eb fush\u00ebn e aplikacioneve HPC, si\u00e7 jan\u00eb t\u00eb dh\u00ebnat e m\u00ebdha (Big Data), m\u00ebsimi i makinerive (ML, machine learning) dhe m\u00ebsimi i thell\u00eb (DL, deep learning). <\/p>\n

T\u00eb theksojm\u00eb se, megjith\u00ebse terminologjia \u00ebsht\u00eb e ngjashme, dy t\u00eb fundit p\u00ebrb\u00ebjn\u00eb detyra algoritmike t\u00eb ndryshme. ML m\u00ebson kompjuterin n\u00eb baz\u00eb t\u00eb t\u00eb dh\u00ebnave t\u00eb strukturuara, nd\u00ebrsa DL n\u00eb baz\u00eb t\u00eb reagimit nga rrjeti nervor. Nj\u00eb shembull q\u00eb ndihmon p\u00ebr t\u00eb kuptuar dallimet \u00ebsht\u00eb mjaft i thjesht\u00eb. Supozoni se kompjuteri duhet t\u00eb dalloj\u00eb foto t\u00eb maceve dhe qenve q\u00eb ngarkohen nga sistemi i ruajtjes. P\u00ebr ML duhet t\u00eb jepet nj\u00eb grup imazhesh me shum\u00eb etiketa, \u00e7do e cila p\u00ebrcakton nj\u00eb ve\u00e7ori t\u00eb ve\u00e7ant\u00eb t\u00eb kafsh\u00ebs. P\u00ebr DL \u00ebsht\u00eb e mjaftueshme t\u00eb ngarkohet nj\u00eb num\u00ebr m\u00eb i madh imazhesh, por vet\u00ebm me nj\u00eb etiket\u00eb \u201ckjo \u00ebsht\u00eb nj\u00eb mace\u201d ose \u201ckjo \u00ebsht\u00eb nj\u00eb qen\u201d. DL \u00ebsht\u00eb shum\u00eb e ngjashme me m\u00ebnyr\u00ebn se si m\u00ebsohen f\u00ebmij\u00ebt e vegj\u00ebl \u2014 atyre thjesht u tregohen imazhe mace dhe qen\u00ebsh n\u00eb libra dhe n\u00eb jet\u00eb (n\u00eb shumic\u00ebn e rasteve, as nuk shpjegohet dallimi i detajuar), dhe truri i f\u00ebmij\u00ebs fillon t\u00eb p\u00ebrcaktoj\u00eb llojin e kafsh\u00ebs pas nj\u00eb numri kritik imazhesh p\u00ebr krahasim (sipas vler\u00ebsimeve, b\u00ebhet fjal\u00eb p\u00ebr rreth nj\u00ebqind deri dyqind paraqitje gjat\u00eb gjith\u00eb f\u00ebmij\u00ebris\u00eb s\u00eb hershme). Algoritmet DL ende nuk jan\u00eb aq t\u00eb p\u00ebrsosura: q\u00eb nj\u00eb rrjet nervor t\u00eb punoj\u00eb me sukses p\u00ebr p\u00ebrcaktimin e imazheve, \u00ebsht\u00eb e nevojshme t\u00eb jepen dhe t\u00eb procesohen n\u00eb GPU miliona imazhesh.<\/p>\n

P\u00ebrfundimi i parath\u00ebnies: mbi baz\u00ebn e GPU-ve mund t\u00eb nd\u00ebrtohen aplikacione HPC n\u00eb fush\u00ebn e Big Data, ML dhe DL, por ekziston nj\u00eb problem \u2014 grupet e t\u00eb dh\u00ebnave jan\u00eb aq t\u00eb m\u00ebdha, saq\u00eb koha e nevojshme p\u00ebr ngarkimin e t\u00eb dh\u00ebnave nga sistemi i ruajtjes n\u00eb GPU fillon t\u00eb zvog\u00ebloj\u00eb performanc\u00ebn totale t\u00eb aplikacionit. N\u00eb fjal\u00eb t\u00eb tjera, grafikat e shpejta mbeten t\u00eb pap\u00ebrdorura p\u00ebr shkak t\u00eb ngadal\u00ebsis\u00eb s\u00eb hyrjes dhe daljes s\u00eb t\u00eb dh\u00ebnave q\u00eb vijn\u00eb nga sisteme t\u00eb tjera. Diferenca mes shpejt\u00ebsis\u00eb s\u00eb hyrjes\/daljes t\u00eb GPU-s\u00eb dhe autobusit ndaj CPU-s\u00eb\/SKH-s\u00eb mund t\u00eb jet\u00eb deri n\u00eb nj\u00eb rend.<\/p>\n

Si funksionon teknologjia GPUDirect Storage?<\/h2>\n

\nProcesi i hyrjes dhe daljes kontrollohet nga CPU, ashtu si edhe procesi i ngarkimit t\u00eb t\u00eb dh\u00ebnave nga ruajtja n\u00eb grafikat p\u00ebr p\u00ebrpunim t\u00eb m\u00ebvonsh\u00ebm. Nga kjo erdhi k\u00ebrkesa p\u00ebr nj\u00eb teknologji q\u00eb do t\u00eb siguronin akses t\u00eb drejtp\u00ebrdrejt\u00eb mes GPU dhe disqeve NVMe p\u00ebr nd\u00ebrveprim t\u00eb shpejt\u00eb mes tyre. Teknologjia e par\u00eb e till\u00eb u propozua nga NVIDIA dhe u quajt GPUDirect Storage. N\u00eb thelb, kjo \u00ebsht\u00eb nj\u00eb lloj i teknologjis\u00eb s\u00eb m\u00ebparshme q\u00eb ata kishin zhvilluar, GPUDirect RDMA (Remote Direct Memory Address).<\/p>\n

\"5.8
\nJensen Huang, CEO i NVIDIA, prezanton GPUDirect Storage si nj\u00eb lloj t\u00eb GPUDirect RDMA n\u00eb ekspozit\u00ebn SC-19. Burimi: NVIDIA<\/i><\/p>\n

Dallimi midis GPUDirect RDMA dhe GPUDirect Storage ndodhet tek pajisjet mbi t\u00eb cilat b\u00ebhet adresimi. Teknologjia GPUDirect RDMA \u00ebsht\u00eb e p\u00ebrshtatur p\u00ebr t\u00eb transferuar t\u00eb dh\u00ebnat direkt midis kart\u00ebs s\u00eb rrjetit (NIC) dhe memories s\u00eb GPU-s\u00eb, nd\u00ebrsa GPUDirect Storage ofron nj\u00eb rrug\u00eb direkte p\u00ebr transferimin e t\u00eb dh\u00ebnave midis ruajtjes lokale ose t\u00eb larg\u00ebt, si NVMe ose NVMe p\u00ebrmes Fabric (NVMe-oF) dhe memories s\u00eb GPU-s\u00eb.<\/p>\n

T\u00eb dy opsionet, GPUDirect RDMA dhe GPUDirect Storage, shmangin l\u00ebvizjet e panevojshme t\u00eb t\u00eb dh\u00ebnave p\u00ebrmes nj\u00eb buferi n\u00eb memorien e CPU-s\u00eb dhe lejojn\u00eb mekanizmin e aksesit direkt n\u00eb memorie (DMA) q\u00eb t\u00eb l\u00ebviz\u00eb t\u00eb dh\u00ebnat nga karta e rrjetit ose ruajtja menj\u00ebher\u00eb n\u00eb memorien e GPU-s\u00eb ose prej saj - dhe gjith\u00e7ka pa ngarkes\u00eb n\u00eb procesorin qendror. P\u00ebr GPUDirect Storage, vendndodhja e ruajtjes nuk ka r\u00ebnd\u00ebsi: mund t\u00eb jet\u00eb nj\u00eb disk NVME brenda nj\u00ebsis\u00eb me GPU, brenda raftit ose i lidhur n\u00eb rrjet si NVMe-oF. <\/p>\n

\"5.8
\nSkema e funksionimit t\u00eb GPUDirect Storage. Burimi: NVIDIA<\/i><\/p>\n

Sistemet e ruajtjes Hi-End mbi NVMe jan\u00eb t\u00eb k\u00ebrkuara n\u00eb tregun e aplikacioneve HPC<\/h2>\n

\nDuke e kuptuar se me shfaqjen e GPUDirect Storage interesi i klient\u00ebve t\u00eb m\u00ebdhenj do t\u00eb drejtohet n\u00eb ofert\u00ebn e sistemeve t\u00eb ruajtjes me shpejt\u00ebsi hyrjeje\/daljeje q\u00eb p\u00ebrputhet me kapacitetin e GPU-s\u00eb, n\u00eb ekspozit\u00ebn SC-19, Kingston tregoi nj\u00eb demo sistemi, i p\u00ebrb\u00ebr\u00eb nga sisteme ruajt\u00ebse t\u00eb bazuara n\u00eb disqe NVMe dhe nj\u00eb nj\u00ebsie me GPU, n\u00eb t\u00eb cil\u00ebn u krye analiza e mij\u00ebra imazheve satelitore p\u00ebr sekond\u00eb. Ne kemi shkruar tashm\u00eb p\u00ebr nj\u00eb sistem ruajt\u00ebs t\u00eb bazuar n\u00eb 10 disqe DC1000M U.2 NVMe. n\u00eb raportin nga ekspozita e superkompjuter\u00ebve<\/a><\/noindex>. <\/p>\n

\"5.8
\nSistemi ruajt\u00ebs bazuar n\u00eb 10 disqe DC1000M U.2 NVMe plot\u00ebson dinjitetsh\u00ebm serverin me p\u00ebrshpejtues grafik\u00eb. Burimi: Kingston<\/i><\/p>\n

Ky sistem ruajt\u00ebs realizohet n\u00eb form\u00ebn e nj\u00eb nj\u00ebsie raft 1U ose m\u00eb t\u00eb madhe dhe mund t\u00eb shkall\u00ebzohet sipas numrit t\u00eb disqeve DC1000M U.2 NVMe, ku secili ka kapacitet prej 3.84-7.68 TB. DC1000M \u00ebsht\u00eb modeli i par\u00eb NVMe SSD n\u00eb formatin U.2 n\u00eb gam\u00ebn e disqeve Kingston p\u00ebr qendrat t\u00eb dh\u00ebnash. Ai ka nj\u00eb tregues q\u00ebndrueshm\u00ebrie (DWPD, Drive writes per day), q\u00eb lejon riparjen e t\u00eb dh\u00ebnave n\u00eb kapacitet t\u00eb plot\u00eb nj\u00eb her\u00eb n\u00eb dit\u00eb gjat\u00eb koh\u00ebzgjatjes s\u00eb garantuar t\u00eb disku. <\/p>\n

N\u00eb testin fio v3.13 n\u00eb sistemin operativ Ubuntu 18.04.3 LTS, Linux kernel 5.0.0-31-generic, mostrat e ekspozit\u00ebs treguan shpejt\u00ebsi leximi (Sustained Read) prej 5.8 milion IOPS me nj\u00eb kapacitet t\u00eb q\u00ebndruesh\u00ebm (Sustained Bandwidth) prej 23.8 Gbit\/s.<\/p>\n

Ari\u00ebl Peres, menaxheri i biznesit t\u00eb SSD n\u00eb Kingston, e p\u00ebrshkruan k\u00ebshtu sistemin e ri t\u00eb ruajtjes: \"Ne jemi t\u00eb gatsh\u00ebm t\u00eb ofrojm\u00eb gjenerat\u00ebn e ardhshme t\u00eb server\u00ebve me zgjidhjet SSD U.2 NVMe, p\u00ebr t\u00eb eliminuar shum\u00eb nga ngushticat n\u00eb transferimin e t\u00eb dh\u00ebnave q\u00eb tradicionalisht lidhen me sistemet e ruajtjes. Kombinimi i uniteteve NVMe SSD dhe memorjes son\u00eb premium, Server Premier DRAM, e b\u00ebn Kingston nj\u00eb nga ofruesit m\u00eb t\u00eb plot\u00eb n\u00eb industrin\u00eb e zgjidhjeve p\u00ebr p\u00ebrpunimin e t\u00eb dh\u00ebnave.\"<\/p>\n

\"5.8
\nTesti gfio v3.13 tregoi nj\u00eb kapacitet prej 23.8 Gbps p\u00ebr sistemin e ruajtjes tregues me disk DC1000M U.2 NVMe. Burimi: Kingston<\/i><\/p>\n

Si do t\u00eb duket nj\u00eb sistem tipik p\u00ebr aplikacione HPC, ku \u00ebsht\u00eb implementuar teknologjia GPUDirect Storage ose ndonj\u00eb teknologji e ngjashme? Kjo \u00ebsht\u00eb nj\u00eb arkitektur\u00eb me ndarje fizike t\u00eb blloqeve funksionale brenda raftit: nj\u00eb deri n\u00eb dy nj\u00ebsit\u00eb p\u00ebr memorjen, disa t\u00eb tjera p\u00ebr nj\u00ebsit\u00eb llogaritus GPU dhe CPU, dhe nj\u00eb ose disa nj\u00ebsit\u00eb p\u00ebr sistemin e ruajtjes.<\/p>\n

Me njoftimin e GPUDirect Storage dhe mund\u00ebsin\u00eb e shfaqjes s\u00eb teknologjive t\u00eb ngjashme nga ofrues t\u00eb tjer\u00eb GPU, p\u00ebr Kingston po zgjeron k\u00ebrkesa p\u00ebr sisteme ruajtjeje q\u00eb kan\u00eb p\u00ebr q\u00ebllim aplikacionet me performanc\u00eb t\u00eb lart\u00eb. Nj\u00eb tregues do t\u00eb jet\u00eb shpejt\u00ebsia e leximit t\u00eb t\u00eb dh\u00ebnave nga sistemi i ruajtjes, e barabart\u00eb me kapacitetin e kartave rrjet 40 ose 100 Gbit n\u00eb hyrje t\u00eb nj\u00ebsive t\u00eb llogaritjes me GPU. Pra, sistemet ultra t\u00eb shpejta t\u00eb ruajtjes, p\u00ebrfshir\u00eb NVMe jasht\u00eb p\u00ebrmes Fabric, do t\u00eb b\u00ebhen mainstream p\u00ebr aplikacionet HPC. P\u00ebrve\u00e7 shkenc\u00ebs dhe llogaritjeve financiare, ato do t\u00eb gjejn\u00eb p\u00ebrdorim n\u00eb shum\u00eb fusha praktike t\u00eb tjera, si sistemet e siguris\u00eb n\u00eb nivelin e qytetit Safe City ose qendrat e v\u00ebzhgimit n\u00eb transport, ku k\u00ebrkohet shpejt\u00ebsi njohjeje dhe identifikimi n\u00eb nivelin e miliona imazheve HD n\u00eb sekond\u00eb,\" tha ai p\u00ebr tregun e sistemeve t\u00eb ruajtjes s\u00eb lart\u00eb.<\/p>\n

Informacione t\u00eb tjera rreth produkteve Kingston mund t\u00eb gjenden n\u00eb faqen zyrtare<\/a><\/noindex> t\u00eb kompanis\u00eb.
\n
Burimi: habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

\u041f\u0440\u0438\u0432\u0435\u0442 \u0425\u0430\u0431\u0440! \u041d\u0430\u0431\u043e\u0440\u044b \u0434\u0430\u043d\u043d\u044b\u0445 \u0434\u043b\u044f Big Data \u0438 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u044d\u043a\u0441\u043f\u043e\u043d\u0435\u043d\u0446\u0438\u0430\u043b\u044c\u043d\u043e \u0440\u0430\u0441\u0442\u0443\u0442 \u0438 \u043d\u0430\u0434\u043e \u0443\u0441\u043f\u0435\u0432\u0430\u0442\u044c \u0438\u0445 \u043e\u0431\u0440\u0430\u0431\u0430\u0442\u044b\u0432\u0430\u0442\u044c. \u041d\u0430\u0448 \u043f\u043e\u0441\u0442 \u043e \u0435\u0449\u0435 \u043e\u0434\u043d\u043e\u0439 \u0438\u043d\u043d\u043e\u0432\u0430\u0446\u0438\u043e\u043d\u043d\u043e\u0439 \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0438 \u0432 \u043e\u0431\u043b\u0430\u0441\u0442\u0438 \u0432\u044b\u0441\u043e\u043a\u043e\u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0445 \u0432\u044b\u0447\u0438\u0441\u043b\u0435\u043d\u0438\u0439 (HPC, High Performance Computing), \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043d\u043e\u0439 \u043d\u0430 \u0441\u0442\u0435\u043d\u0434\u0435 Kingston \u043d\u0430 Supercomputing-2019. \u042d\u0442\u043e \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u0435 Hi-End \u0441\u0438\u0441\u0442\u0435\u043c \u0445\u0440\u0430\u043d\u0435\u043d\u0438\u044f \u0434\u0430\u043d\u043d\u044b\u0445 (\u0421\u0425\u0414) \u0432 \u0441\u0435\u0440\u0432\u0435\u0440\u0430\u0445 \u0441 \u0433\u0440\u0430\u0444\u0438\u0447\u0435\u0441\u043a\u0438\u043c\u0438 \u043f\u0440\u043e\u0446\u0435\u0441\u0441\u043e\u0440\u0430\u043c\u0438 (GPU) \u0438 \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0435\u0439 \u0448\u0438\u043d\u044b GPUDirect […]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[688],"tags":[],"class_list":["post-54686","post","type-post","status-publish","format-standard","hentry","category-administrirovanie"],"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\udd475.8 milion IOPS: p\u00ebrse kaq shum\u00eb? | ProHoster","description":"P\u00ebrsh\u00ebndetje Habr! 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