{"id":103157,"date":"2022-02-01T15:36:44","date_gmt":"2022-02-01T13:36:46","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/metod-identifikaczii-sistemy-polzovatelya-na-osnove-informaczii-o-gpu"},"modified":"2022-02-01T15:36:44","modified_gmt":"2022-02-01T13:36:46","slug":"metod-identifikaczii-sistemy-polzovatelya-na-osnove-informaczii-o-gpu","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sq\/blog\/news\/metod-identifikaczii-sistemy-polzovatelya-na-osnove-informaczii-o-gpu","title":{"rendered":"Metoda e identifikimit t\u00eb sistemit t\u00eb p\u00ebrdoruesit mbi baz\u00ebn e informacionit n\u00eb lidhje me GPU","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

K\u00ebrkuesit nga Universiteti i Ben-Gurion (Izrael), Universiteti i Lille (Franc\u00eb) dhe Universiteti i Adelaide (Australi) kan\u00eb zhvilluar nj\u00eb teknik\u00eb t\u00eb re p\u00ebr identifikimin e pajisjeve t\u00eb p\u00ebrdoruesve p\u00ebrmes p\u00ebrcaktimit t\u00eb parametrave t\u00eb pun\u00ebs s\u00eb GPU n\u00eb shfletuesin web. Metoda ka marr\u00eb emrin \"Drawn Apart\" dhe bazohet n\u00eb p\u00ebrdorimin e WebGL p\u00ebr t\u00eb marr\u00eb nj\u00eb profil t\u00eb performanc\u00ebs s\u00eb GPU-s\u00eb, i cili lejon nj\u00eb rritje t\u00eb konsiderueshme t\u00eb sakt\u00ebsis\u00eb s\u00eb metodave pasive t\u00eb gjurmimit, q\u00eb punojn\u00eb pa p\u00ebrdorimin e cookie-ve dhe pa ruajtur nj\u00eb identifikues n\u00eb sistemin e p\u00ebrdoruesit. <\/p>\n

Metodat q\u00eb marrin parasysh karakteristikat e vizatimit, GPU-s\u00eb, grumbullit grafik dhe drejtuesve ishin p\u00ebrdorur edhe m\u00eb par\u00eb, por ato ishin t\u00eb kufizuara n\u00eb mund\u00ebsin\u00eb e ndarjes s\u00eb pajisjeve vet\u00ebm n\u00eb nivelin e modeleve t\u00eb ndryshme t\u00eb kartave grafike dhe GPU, dmth. mund t\u00eb aplikoheshin vet\u00ebm si nj\u00eb faktor shtes\u00eb p\u00ebr t\u00eb rritur probabilitetin e identifikimit. Karakteristika kryesore e metod\u00ebs s\u00eb re \"Drawn Apart\" \u00ebsht\u00eb se ajo nuk kufizohet n\u00eb ndarjen e modeleve t\u00eb ndryshme t\u00eb GPU-s\u00eb, por p\u00ebrpiqet t\u00eb zbuloj\u00eb dallime mes GPU-s\u00eb identike t\u00eb nj\u00eb modeli, t\u00eb shkaktuara nga heterogjeniteti i procesit t\u00eb prodhimit t\u00eb \u00e7ip\u00ebve, t\u00eb paracaktuar p\u00ebr llogaritjet masive t\u00eb paralel\u00ebve. V\u00ebrehet se variacionet q\u00eb ndodhin gjat\u00eb procesit t\u00eb prodhimit lejojn\u00eb formimin e gjurm\u00ebve unike p\u00ebr modele t\u00eb nj\u00ebjta pajisjesh.

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

Doli se k\u00ebto dallime mund t\u00eb identifikohen p\u00ebrmes num\u00ebrimit t\u00eb blloqeve t\u00eb ekzekutimit dhe analiz\u00ebs s\u00eb performanc\u00ebs s\u00eb tyre n\u00eb GPU. Si primitivi p\u00ebr identifikimin e modeleve t\u00eb ndryshme t\u00eb GPU-s\u00eb, u p\u00ebrdor\u00ebn verifikimet e bazuara n\u00eb nj\u00eb grup funksionesh trigonometrike, operacione logjike dhe llogaritje me pik\u00eb t\u00eb floating. P\u00ebr t\u00eb zbuluar dallimet n\u00eb GPU q\u00eb jan\u00eb identike, u vler\u00ebsua numri i rrjedhave q\u00eb ekzekutohen nj\u00ebkoh\u00ebsisht gjat\u00eb ekzekutimit t\u00eb shader-\u00ebve t\u00eb maj\u00ebs. Supozohet se efekti i identifikuar \u00ebsht\u00eb shkaktuar nga dallimet n\u00eb temperaturat dhe konsumimin e energjis\u00eb t\u00eb ekzemplar\u00ebve t\u00eb ndrysh\u00ebm t\u00eb \u00e7ipave (m\u00eb par\u00eb, nj\u00eb efekt i ngjash\u00ebm ishte demonstruar p\u00ebr CPU - procesor\u00ebt identik\u00eb gjat\u00eb ekzekutimit t\u00eb kodit t\u00eb nj\u00ebjt\u00eb treguan konsumim t\u00eb ndrysh\u00ebm t\u00eb energjis\u00eb). <\/p>\n

Duke qen\u00eb se operacionet p\u00ebrmes WebGL kryhen n\u00eb m\u00ebnyr\u00eb asinkrone, p\u00ebr t\u00eb matur koh\u00ebn e ekzekutimit t\u00eb tyre nuk mund t\u00eb p\u00ebrdoret drejtp\u00ebrdrejt API i JavaScript performance.now(), prandaj jan\u00eb propozuar tre truke p\u00ebr matjen e koh\u00ebs. <\/p>\n