{"id":33434,"date":"2019-10-31T21:52:33","date_gmt":"2019-10-31T18:52:33","guid":{"rendered":"https:\/\/prohoster.info\/blog\/kak-rabotaet-szhatie-v-obektno-orientirovannoj-arhitekture-pamyati\/"},"modified":"2019-10-31T21:52:33","modified_gmt":"2019-10-31T18:52:33","slug":"kak-rabotaet-szhatie-v-obektno-orientirovannoj-arhitekture-pamyati","status":"publish","type":"post","link":"https:\/\/prohoster.info\/et\/blog\/administrirovanie\/kak-rabotaet-szhatie-v-obektno-orientirovannoj-arhitekture-pamyati","title":{"rendered":"Kuidas t\u00f6\u00f6tab kokkusurumine objekti-orienteeritud m\u00e4luarhitektuuris","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

MITi insenerite meeskond on v\u00e4lja t\u00f6\u00f6tanud objekt-orienteeritud m\u00e4luhierarhia, et andmeid t\u00f5husamalt t\u00f6\u00f6delda. Artiklis uurime, kuidas see toimib.<\/p>\n

\"Kuidas<\/a><\/noindex><\/a><\/noindex>
\n\/ PxHere<\/noindex> \/ PD<\/i><\/p>\n

Nagu teada, ei kaasne kaasaegsete CPU tootlikkuse kasvuga vastav m\u00e4lu juurdep\u00e4\u00e4su latentsuse v\u00e4henemine. Muutuste erinevus v\u00f5ib ulatuda kuni 10 korda aastas (PDF, lk. 3<\/a><\/noindex>). Tulemusena tekib pudelikael, mis ei v\u00f5imalda t\u00e4ielikult olemasolevaid ressursse \u00e4ra kasutada ning aeglustab andmete t\u00f6\u00f6tlemist.<\/p>\n

Toodangut kahjustab nn dekompressioonilaatne viivitus. M\u00f5nedel juhtudel v\u00f5ib andmete ettevalmistamise dekompressioon v\u00f5tta kuni 64 protsessorits\u00fcklit. <\/p>\n

V\u00f5rdluseks: ujukoma arvude liitmine ja korrutamine v\u00f5tavad<\/a><\/noindex> mitte rohkem kui k\u00fcmme ts\u00fcklit. Probleem seisneb selles, et m\u00e4lu t\u00f6\u00f6tab fikseeritud suurusega andmeblokkidega, samas kui rakendused opereerivad objektidega, mis v\u00f5ivad sisaldada erinevaid andmet\u00fc\u00fcpe ja erineda suuruse poolest. Probleemi lahendamiseks on MITi insenerid v\u00e4lja t\u00f6\u00f6tanud objekt-orienteeritud m\u00e4luhierarhia, mis optimeerib andmete t\u00f6\u00f6tlemist.<\/p>\n

Kuidas tehnoloogia t\u00f6\u00f6tab<\/h2>\n

\nLahenduse aluseks on kolm tehnoloogiat: Hotpads, Zippads ja COCO kompresseerimisalgoritm.<\/p>\n

Hotpads on tarkvaraliselt hallatav \u00fclimemori registrihierarhia (scratchpad<\/a><\/noindex>). Need registrid nimetatakse padadeks (pads) ja neid on kolm \u2014 L1-st kuni L3-ni. Neis hoitakse eri suurusega objekte, metaandmeid ja viidete massiive.<\/p>\n

Sisuliselt on arhitektuur s\u00fcsteem, mis on optimeeritud objektidega t\u00f6\u00f6tamiseks sarnane nagu vahem\u00e4lu. Peda tase, kus objekt asub, s\u00f5ltub sellest, kui sageli seda kasutatakse. Kui m\u00f5ni tase '\u00fcleujub', k\u00e4ivitab s\u00fcsteem mehhanismi, mis sarnaneb 'pr\u00fcgikoristajatele' programmeerimiskeeltes Java v\u00f5i Go. See anal\u00fc\u00fcsib, milliseid objekte kasutatakse harvemini kui teisi, ja liigub automaatselt nende vahel.<\/p>\n

Zippads toimib Hotpads'i alusel \u2014 arhiveerib ja de-arhiveerib andmed, mis sisenevad v\u00f5i v\u00e4ljuvad hierarhia kahe viimase taseme \u2014 p\u00e4d L3 ja p\u00f5hij\u00e4lu. Esimeses ja teises p\u00e4das hoitakse andmeid muutumatul kujul.<\/p><\/blockquote>\n

\n \"Kuidas
\n
\nZippads komprimeerib objekte, mille suurus ei \u00fcleta 128 baiti. Suuremad objektid jagatakse osadeks, mis needj\u00e4rel paigutatakse erinevatesse m\u00e4lu piirkondadesse. Arendajate s\u00f5nul t\u00f5stab selline l\u00e4henemine m\u00e4lu t\u00f5hususe m\u00e4\u00e4ra.<\/p>\n

Objektide kompressimiseks kasutatakse algoritmi COCO (Cross-Object COmpression), millest r\u00e4\u00e4gime edaspidi, kuigi s\u00fcsteem t\u00f6\u00f6tab ka Base-Delta-Immediate<\/a><\/noindex> v\u00f5i FPC<\/a><\/noindex>. Algoritm COCO on diferentsiaalsete kompressioonide liik (differential compression<\/a><\/noindex>). See v\u00f5rdleb objekte \"baas\"-objektidega ja eemaldab korduvad bitid \u2014 vt skeemi allpool:<\/p>\n

\"Kuidas<\/p>\n

MIT-i inseneride s\u00f5nul on nende objektorienteeritud m\u00e4lu hierarhia 17% efektiivsem kui klassikalised l\u00e4henemisviisid. See on palju l\u00e4hemal kaasaegsete rakenduste arhitektuurile, seega on uuel meetodil potentsiaali.<\/p>\n

Oodatavasti hakkavad tehnoloogiat esmajoones kasutama ettev\u00f5tted, mis t\u00f6\u00f6tavad suurte andmete ja masin\u00f5ppe algoritmidega. Veel \u00fcks potentsiaalne suund on pilveplatvormid. IaaS-teenuse pakkujad saavad v\u00f5imekuse paremini hallata virtualiseerimise, andmesalvestuss\u00fcsteemide ja arvutusressurssidega.<\/p>\n

Meie t\u00e4iendavad ressursid ja allikad:<\/b><\/p>\n

\"Kuidas \u00abKuidas me ehitame IaaS-i\u00bb: materjalid 1cloudi t\u00f6\u00f6 kohta<\/a><\/noindex><\/p>\n

\"Kuidas Pilve arhitektuuri evolutsioon 1cloud<\/a><\/noindex>
\n\"Kuidas Objektide salvestusteenus 1cloud<\/a><\/noindex><\/p>\n

\"Kuidas Potentsiaalsed r\u00fcnnakud HTTPS-i vastu ja meetodid nende vastu kaitsmiseks<\/a><\/noindex>
\n\"Kuidas Kuidas sarnanevad ja erinevad Continuous Delivery ja Continuous Integration l\u00e4henemised<\/a><\/noindex>
\n\"Kuidas Kuidas kaitsta serverit internetis: 1cloud'i kogemused<\/a><\/noindex><\/p><\/blockquote>\n

Allikas: habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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