{"id":173668,"date":"2013-02-11T13:04:00","date_gmt":"2013-02-11T12:04:00","guid":{"rendered":"https:\/\/cms.galaxiemedia.fr\/tomshardware\/2013\/02\/11\/linfluence-de-la-temperature-sur-les-calculs-gpu\/"},"modified":"2023-06-22T18:52:41","modified_gmt":"2023-06-22T16:52:41","slug":"linfluence-de-la-temperature-sur-les-calculs-gpu","status":"publish","type":"post","link":"https:\/\/www.tomshardware.fr\/linfluence-de-la-temperature-sur-les-calculs-gpu\/","title":{"rendered":"L’influence de la temp\u00e9rature sur les calculs GPU"},"content":{"rendered":"

\"ImageTaux d’erreurs<\/span><\/span><\/span><\/p>\n<\/p>\n

En janvier se tenait le Compas’ 2013<\/a>, un \u00e9v\u00e9nement d\u00e9di\u00e9 au parall\u00e9lisme en informatique. Et un papier a suscit\u00e9 notre attention : \u00ab Tempe\u0301ratures, erreurs mate\u0301rielles et GPU<\/em> \u00bb.<\/p>\n<\/p>\n

Les erreurs de calcul li\u00e9es \u00e0 la temp\u00e9rature<\/h4>\n<\/p>\n

L’id\u00e9e de David Defour et Eric Petit est simple : v\u00e9rifier la tol\u00e9rance des cartes de calcul quand la temp\u00e9rature est \u00e9lev\u00e9e. Ils ont donc r\u00e9cup\u00e9r\u00e9 plusieurs cartes NVIDIA<\/strong> (Telsa, etc.) et effectu\u00e9 des tests en OpenCL<\/strong> pour v\u00e9rifier si les cartes restaient fiables \u00e0 haute temp\u00e9rature. Ce n’est pas un test anodin : les cartes sont de plus en plus souvent install\u00e9es dans des ordinateurs portables ou dans des ordinateurs de type All In One et subissent donc des contraintes bien sup\u00e9rieures \u00e0 des cartes install\u00e9es dans une tour classique, bien ventil\u00e9e.<\/p>\n<\/p>\n

Selon les auteurs, les erreurs de calcul ne sont pas rares : avec un programme comme Folding@Home, les statistiques indiquent que 2\/3 des GPU grand public font des erreurs d\u00e9tectables et que dans certains cas (2 % des GPU), le taux d’erreurs n’est pas n\u00e9gligeable et atteint environ un calcul sur 10 000. Sur les cartes Tesla, plus contr\u00f4l\u00e9es, ce taux d’erreur est n\u00e9gligeable selon les \u00e9tudes.<\/p>\n<\/p>\n

Pour mesurer les taux d’erreurs, plusieurs cartes ont \u00e9t\u00e9 plac\u00e9es dans un bo\u00eetier externe, fourni par NVIDIA avec certaines cartes Tesla (les D870). Le syst\u00e8me de refroidissement et le bo\u00eetier ont \u00e9t\u00e9 modifi\u00e9s pour augmenter la temp\u00e9rature des cartes de fa\u00e7on artificielle. Enfin, un programme de test d\u00e9di\u00e9 a \u00e9t\u00e9 \u00e9crit en OpenCL pour tester les diff\u00e9rentes unit\u00e9s des cartes.<\/p>\n<\/p>\n

Les cartes test\u00e9es sont les suivantes : Tesla C870, GeForce 9800GX2, Tesla T10P, GeForce GTX480, GeForce GTX560 et GeForce GTX670. Les cartes ont toutes une limite de temp\u00e9rature qui arr\u00eate physiquement le GPU, sauf la Tesla C870. Les temp\u00e9ratures limites sont de (respectivement) 130\u00b0C, 115\u00b0C, 110\u00b0C, 105\u00b0C et 100\u00b0C. Comme on le voit, plus on avance dans le temps et plus la temp\u00e9rature limite diminue. De plus, les cartes ont une limite en temp\u00e9rature qui diminue la fr\u00e9quence : \u00e0 partir de 105\u00b0C (et tous les 5\u00b0C), la Tesla C870 divise sa fr\u00e9quence de fonctionnement par deux (600 MHz au d\u00e9part). La GeForce 9800GX2 divise sa fr\u00e9quence par deux \u00e0 105\u00b0C et passe \u00e0 seulement 37 MHz au-del\u00e0 de 115\u00b0C. La Tesla T10P divise sa fr\u00e9quence par deux \u00e0 105\u00b0C alors que les autres mod\u00e8les divisent la fr\u00e9quence par deux \u00e0 partir de 100\u00b0C.<\/p>\n<\/p>\n

Sur les cartes acceptant de fonctionner \u00e0 130\u00b0C (GeForce 9800GX2 et Tesla C870), il n’y a pas eu d’erreur de calcul, m\u00eame apr\u00e8s plusieurs jours. \u00c0 160\u00b0C, une des cartes est morte apr\u00e8s 11 jours de tests. \u00c0 170\u00b0C, les erreurs au niveau des calculs sont fr\u00e9quentes. Visiblement, les auteurs de l’article n’ont pas r\u00e9ussi \u00e0 obtenir des erreurs sur les autres cartes, et pour une bonne raison : les m\u00e9canismes de protection permettent de prot\u00e9ger les cartes.<\/p>\n<\/p>\n

Notons que le test OpenCL utilis\u00e9 a un avantage : il permet de cibler pr\u00e9cis\u00e9ment les unit\u00e9s qui effectuent des calculs dont la r\u00e9ponse est fausse. Il est donc techniquement possible d’isoler ces derniers pour ne garder que les unit\u00e9s qui ne font pas d’erreurs.<\/p>\n<\/p>\n

Pour les amateurs, l’\u00e9tude est disponible au t\u00e9l\u00e9chargement. Il s’agit de l’\u00e9tude num\u00e9ro 2 dans la partie Architecture.<\/p>\n","protected":false},"excerpt":{"rendered":"

En janvier se tenait le Compas' 2013, un \u00e9v\u00e9nement d\u00e9di\u00e9 au parall\u00e9lisme en informatique.<\/p>","protected":false},"author":36,"featured_media":46671,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[487,4072,4107],"tags":[538],"hubs":[],"class_list":["post-173668","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-actualite","category-cartes-graphiques","category-entreprises","tag-nvidia"],"acf":{"post_show_excerpt":false,"post_source":{"title":"Tom's Hardware FR","url":"https:\/\/www.tomshardware.fr\/","target":""}},"yoast_head":"\nL'influence de la temp\u00e9rature sur les calculs GPU<\/title>\n<meta name=\"description\" content=\"En janvier se tenait le Compas' 2013, un \u00e9v\u00e9nement d\u00e9di\u00e9 au parall\u00e9lisme en informatique.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, 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