{"id":4509,"date":"2025-11-05T11:12:00","date_gmt":"2025-11-05T11:12:00","guid":{"rendered":"https:\/\/lp.szlogic.cn\/knowledge-center\/cpu-vs-gpu-vs-tpu-vs-npu-architecture-comparison-explained\/"},"modified":"2026-06-22T05:33:53","modified_gmt":"2026-06-22T05:33:53","slug":"cpu-vs-gpu-vs-tpu-vs-npu-architecture-comparison-explained","status":"publish","type":"post","link":"https:\/\/resourceslp.szlogic.cn\/fr\/knowledge-center\/cpu-vs-gpu-vs-tpu-vs-npu-architecture-comparison-explained","title":{"rendered":"Comprendre la diff\u00e9rence entre CPU, GPU, TPU et NPU dans les syst\u00e8mes d\u2019IA modernes"},"content":{"rendered":"<figure class=\"wp-block-image aligncenter size-large\"><img fetchpriority=\"high\" decoding=\"async\" width=\"1200\" height=\"712\" src=\"https:\/\/resourceslp.szlogic.cn\/wp-content\/uploads\/2026\/05\/0bc0ebf4840d42efa3bfdc4b846ffe57.webp\" alt=\"CPU vs GPU vs TPU vs NPU in AI Systems\" class=\"wp-image-4506\" srcset=\"https:\/\/resourceslp.szlogic.cn\/wp-content\/uploads\/2026\/05\/0bc0ebf4840d42efa3bfdc4b846ffe57.webp 1200w, https:\/\/resourceslp.szlogic.cn\/wp-content\/uploads\/2026\/05\/0bc0ebf4840d42efa3bfdc4b846ffe57-300x178.webp 300w, https:\/\/resourceslp.szlogic.cn\/wp-content\/uploads\/2026\/05\/0bc0ebf4840d42efa3bfdc4b846ffe57-1024x608.webp 1024w, https:\/\/resourceslp.szlogic.cn\/wp-content\/uploads\/2026\/05\/0bc0ebf4840d42efa3bfdc4b846ffe57-768x456.webp 768w, https:\/\/resourceslp.szlogic.cn\/wp-content\/uploads\/2026\/05\/0bc0ebf4840d42efa3bfdc4b846ffe57-18x12.webp 18w\" sizes=\"(max-width: 1200px) 100vw, 1200px\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">IA, <a target=\"_blank\" rel=\"\" href=\"https:\/\/resourceslp.szlogic.cn\/fr\/knowledge-center\/what-is-cloud-computing-access-servers-storage-apps-online\/\">cloud computing<\/a>, et les dispositifs intelligents p\u00e9riph\u00e9riques red\u00e9finissent la mani\u00e8re dont nous concevons les syst\u00e8mes informatiques. Des termes tels que <strong>CPU<\/strong>, <strong>GPU<\/strong>, <strong>TPU<\/strong>, and <strong>NPU<\/strong> sont d\u00e9sormais centraux dans les discussions portant sur l\u2019entra\u00eenement des mod\u00e8les, l\u2019efficacit\u00e9 de l\u2019inf\u00e9rence et les performances syst\u00e8me.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Bien que ces quatre composants traitent tous des donn\u00e9es, ils sont optimis\u00e9s pour des charges de travail diff\u00e9rentes. Ce guide clarifie leurs diff\u00e9rences architecturales, leurs orientations en mati\u00e8re de performances et leurs applications pratiques dans les syst\u00e8mes d\u2019IA modernes.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>\u2605<\/strong> Qu\u2019est-ce qu\u2019un CPU ? (Unit\u00e9 centrale de traitement)<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Contr\u00f4le et calcul g\u00e9n\u00e9ralistes<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The <a target=\"_blank\" rel=\"\" href=\"https:\/\/resourceslp.szlogic.cn\/fr\/glossary\/what-is-cpu-central-processing-unit\/\"><strong>CPU<\/strong><\/a> est le processeur g\u00e9n\u00e9raliste fondamental des syst\u00e8mes informatiques. Il met l\u2019accent sur <strong>l\u2019ex\u00e9cution \u00e0 faible latence<\/strong>, la logique complexe de branchement et l\u2019orchestration syst\u00e8me.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Caract\u00e9ristiques cl\u00e9s<\/strong><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>Pipeline multi-\u00e9tapes et pr\u00e9diction de branchement<\/p><\/li>\n\n\n\n<li><p>Hi\u00e9rarchie de m\u00e9moire cache \u00e9tendue<\/p><\/li>\n\n\n\n<li><p>Optimis\u00e9 pour les charges de travail s\u00e9quentielles et mixtes<\/p><\/li>\n\n\n\n<li><p>G\u00e8re les syst\u00e8mes d\u2019exploitation, les entr\u00e9es\/sorties, l\u2019ordonnancement et la logique applicative g\u00e9n\u00e9rale<\/p><\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Id\u00e9al pour<\/strong><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>Orchestration syst\u00e8me et t\u00e2ches du syst\u00e8me d\u2019exploitation<\/p><\/li>\n\n\n\n<li><p>Op\u00e9rations de base de donn\u00e9es et logique d\u2019API<\/p><\/li>\n\n\n\n<li><p>Pr\u00e9- et post-traitement des mod\u00e8les d\u2019IA<\/p><\/li>\n\n\n\n<li><p>Pile r\u00e9seau et plan de contr\u00f4le<\/p><\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Limitations<\/strong><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>D\u00e9bit parall\u00e8le inf\u00e9rieur par rapport aux GPU et aux acc\u00e9l\u00e9rateurs<\/p><\/li>\n\n\n\n<li><p>Co\u00fbt plus \u00e9lev\u00e9 par op\u00e9ration d\u2019IA<\/p><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>\u2605<\/strong> Qu\u2019est-ce qu\u2019un GPU ? (Unit\u00e9 de traitement graphique)<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Calcul hautement parall\u00e8le pour l\u2019entra\u00eenement de mod\u00e8les d\u2019apprentissage automatique<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Initialement con\u00e7u pour le graphisme, <a target=\"_blank\" rel=\"\" href=\"https:\/\/resourceslp.szlogic.cn\/fr\/glossary\/what-is-a-gpu-graphics-processing-units\/\"><strong>GPU<\/strong><\/a> excelle dans les <strong>op\u00e9rations flottantes massivement parall\u00e8les<\/strong>, ce qui en fait le composant dominant pour l\u2019entra\u00eenement des r\u00e9seaux de neurones profonds.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Caract\u00e9ristiques cl\u00e9s<\/strong><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>Milliers d\u2019unit\u00e9s arithm\u00e9tiques logiques SIMD\/SIMT<\/p><\/li>\n\n\n\n<li><p>D\u00e9bit \u00e9lev\u00e9 en FP16\/FP32<\/p><\/li>\n\n\n\n<li><p>Extr\u00eamement efficace pour les charges de travail matricielles et tensorielles<\/p><\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Id\u00e9al pour<\/strong><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>Entra\u00eenement de mod\u00e8les d\u2019apprentissage profond<\/p><\/li>\n\n\n\n<li><p><a href=\"https:\/\/resourceslp.szlogic.cn\/fr\/glossary\/what-is-hpc-high-performance-computing\/\" target=\"_blank\" rel=\"\">Calcul haute performance (HPC)<\/a><\/p><\/li>\n\n\n\n<li><p>Rendu, simulation, acc\u00e9l\u00e9ration vid\u00e9o<\/p><\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Limitations<\/strong><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>Consommation \u00e9lectrique \u00e9lev\u00e9e<\/p><\/li>\n\n\n\n<li><p>Moins efficace pour la logique non parall\u00e8le<\/p><\/li>\n\n\n\n<li><p>N\u00e9cessite des frameworks et des noyaux optimis\u00e9s<\/p><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>\u2605<\/strong> Qu\u2019est-ce qu\u2019un TPU ? (Unit\u00e9 de traitement tensoriel)<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Acc\u00e9l\u00e9rateur d\u00e9di\u00e9 \u00e0 l\u2019IA d\u00e9velopp\u00e9 par Google<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">A <a target=\"_blank\" rel=\"\" href=\"https:\/\/resourceslp.szlogic.cn\/fr\/glossary\/tpu-tensor-processing-unit-google-ai-accelerator\/\"><strong>TPU (Unit\u00e9 de traitement tensoriel)<\/strong><\/a> est un circuit int\u00e9gr\u00e9 sp\u00e9cifique au domaine (ASIC) d\u00e9di\u00e9 \u00e0 l\u2019IA, con\u00e7u par Google pour les <strong>multiplications matricielles et op\u00e9rations tensorielles<\/strong>, largement utilis\u00e9 pour l\u2019entra\u00eenement et l\u2019inf\u00e9rence \u00e0 grande \u00e9chelle en apprentissage automatique.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Caract\u00e9ristiques architecturales cl\u00e9s<\/strong><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>Unit\u00e9s de calcul en r\u00e9seau systolique<\/p><\/li>\n\n\n\n<li><p>M\u00e9moire int\u00e9gr\u00e9e \u00e0 tr\u00e8s haute bande passante<\/p><\/li>\n\n\n\n<li><p>Optimis\u00e9 pour TensorFlow et les grands mod\u00e8les de type transformeur<\/p><\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Id\u00e9al pour<\/strong><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>Entra\u00eenement d\u2019IA \u00e0 l\u2019\u00e9chelle du cloud et de grands mod\u00e8les linguistiques (LLM)<\/p><\/li>\n\n\n\n<li><p>Inf\u00e9rence \u00e0 haut d\u00e9bit<\/p><\/li>\n\n\n\n<li><p>Syst\u00e8mes de recommandation, mod\u00e8les de reconnaissance vocale et de vision par ordinateur<\/p><\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Limitations<\/strong><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>Principalement disponible via Google Cloud<\/p><\/li>\n\n\n\n<li><p>Moins flexible que les GPU pour les t\u00e2ches non li\u00e9es \u00e0 l\u2019IA<\/p><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>\u2605<\/strong> Qu\u2019est-ce qu\u2019un NPU ? (Unit\u00e9 de traitement neuronal)<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Inf\u00e9rence IA efficace sur appareil<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">An <a target=\"_blank\" rel=\"\" href=\"https:\/\/resourceslp.szlogic.cn\/fr\/glossary\/npu-neural-processing-unit-architecture-edge-ai-explained\/\"><strong>NPU<\/strong><\/a> acc\u00e9l\u00e8re l\u2019inf\u00e9rence d\u2019apprentissage profond dans <strong>des environnements p\u00e9riph\u00e9riques \u00e0 faible consommation d\u2019\u00e9nergie<\/strong>. Il est d\u00e9sormais standard dans les SoC mobiles, les puces d\u2019IA automobile et les processeurs IoT industriels.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Caract\u00e9ristiques cl\u00e9s<\/strong><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>Pipelines d\u2019ex\u00e9cution neuronale d\u00e9di\u00e9s<\/p><\/li>\n\n\n\n<li><p>Prise en charge du calcul quantifi\u00e9 (INT8\/INT4)<\/p><\/li>\n\n\n\n<li><p>Hautes performances par watt pour les charges de travail li\u00e9es \u00e0 l\u2019IA<\/p><\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Id\u00e9al pour<\/strong><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>IA mobile (vision, reconnaissance vocale, RA\/RV)<\/p><\/li>\n\n\n\n<li><p>Cam\u00e9ras intelligentes et robotique<\/p><\/li>\n\n\n\n<li><p>Automobile <a href=\"https:\/\/resourceslp.szlogic.cn\/fr\/glossary\/what-is-adas-system\/\" target=\"_blank\" rel=\"\">Syst\u00e8mes avanc\u00e9s d\u2019aide \u00e0 la conduite (ADAS)<\/a> calcul<\/p><\/li>\n\n\n\n<li><p>LLM local et inf\u00e9rence p\u00e9riph\u00e9rique<\/p><\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Limitations<\/strong><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>Non adapt\u00e9 \u00e0 l\u2019entra\u00eenement \u00e0 grande \u00e9chelle<\/p><\/li>\n\n\n\n<li><p>Flexibilit\u00e9 restreinte des charges de travail compar\u00e9e \u00e0 celle du CPU\/GPU<\/p><\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image aligncenter size-large\"><img decoding=\"async\" width=\"1024\" height=\"683\" src=\"https:\/\/resourceslp.szlogic.cn\/wp-content\/uploads\/2026\/05\/4dd93454c13b47959397aca90d33749e-1024x683.png\" alt=\"What Is an NPU? (Neural Processing Unit)\" class=\"wp-image-4507\" srcset=\"https:\/\/resourceslp.szlogic.cn\/wp-content\/uploads\/2026\/05\/4dd93454c13b47959397aca90d33749e-1024x683.png 1024w, https:\/\/resourceslp.szlogic.cn\/wp-content\/uploads\/2026\/05\/4dd93454c13b47959397aca90d33749e-300x200.png 300w, https:\/\/resourceslp.szlogic.cn\/wp-content\/uploads\/2026\/05\/4dd93454c13b47959397aca90d33749e-768x512.png 768w, https:\/\/resourceslp.szlogic.cn\/wp-content\/uploads\/2026\/05\/4dd93454c13b47959397aca90d33749e-18x12.png 18w, https:\/\/resourceslp.szlogic.cn\/wp-content\/uploads\/2026\/05\/4dd93454c13b47959397aca90d33749e.png 1536w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>\u2605<\/strong> Tableau comparatif : CPU vs GPU vs TPU vs NPU<\/h2>\n\n\n\n<figure class=\"wp-block-table\">\n<table class=\"has-fixed-layout\">\n<colgroup><col style=\"min-width: 25px;\"\/><col style=\"min-width: 25px;\"\/><col style=\"min-width: 25px;\"\/><col style=\"min-width: 25px;\"\/><col style=\"min-width: 25px;\"\/><\/colgroup><tbody><tr><th colspan=\"1\" rowspan=\"1\"><p>Fonctionnalit\u00e9<\/p><\/th><th colspan=\"1\" rowspan=\"1\"><p>CPU<\/p><\/th><th colspan=\"1\" rowspan=\"1\"><p>GPU<\/p><\/th><th colspan=\"1\" rowspan=\"1\"><p>TPU<\/p><\/th><th colspan=\"1\" rowspan=\"1\"><p>NPU<\/p><\/th><\/tr><tr><td colspan=\"1\" rowspan=\"1\"><p>Focus principal<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>Contr\u00f4le et logique<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>Calcul parall\u00e8le<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>Calcul tensoriel<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>Inf\u00e9rence p\u00e9riph\u00e9rique<\/p><\/td><\/tr><tr><td colspan=\"1\" rowspan=\"1\"><p>Style de calcul<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>S\u00e9riel + parall\u00e8le mixte<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>Parall\u00e9lisme massif<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>R\u00e9seau systolique matriciel<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>Pipelines neuronaux<\/p><\/td><\/tr><tr><td colspan=\"1\" rowspan=\"1\"><p>Atout<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>Souplesse<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>Entra\u00eenement et calcul intensif (HPC)<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>IA \u00e0 grande \u00e9chelle<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>IA \u00e0 faible consommation d\u2019\u00e9nergie<\/p><\/td><\/tr><tr><td colspan=\"1\" rowspan=\"1\"><p>Emplacement optimal<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>Serveurs, ordinateurs personnels<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>Stations de travail, cloud<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>Google Cloud<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>Appareils p\u00e9riph\u00e9riques<\/p><\/td><\/tr><\/tbody>\n<\/table>\n<\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>\u2605 <\/strong>Sc\u00e9narios de d\u00e9ploiement concrets<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Centres de donn\u00e9es<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p><strong>GPU \/ TPU<\/strong> pour l\u2019entra\u00eenement de grands r\u00e9seaux de neurones<\/p><\/li>\n\n\n\n<li><p><strong>CPU<\/strong> pour le plan de contr\u00f4le, l\u2019ordonnancement et les entr\u00e9es\/sorties<\/p><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">P\u00e9riph\u00e9rique et embarqu\u00e9<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p><a href=\"https:\/\/resourceslp.szlogic.cn\/fr\/glossary\/npu-neural-processing-unit-architecture-edge-ai-explained\/\" target=\"_blank\" rel=\"\"><strong>NPU<\/strong><\/a> pour l\u2019inf\u00e9rence en temps r\u00e9el<\/p><\/li>\n\n\n\n<li><p><strong>CPU<\/strong> g\u00e8re le syst\u00e8me d\u2019exploitation, les t\u00e2ches syst\u00e8me et le calcul de secours<\/p><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">Strat\u00e9gie hybride d\u2019IA<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Les piles informatiques modernes combinent de plus en plus <strong>CPU + GPU\/TPU + NPU<\/strong> afin d\u2019optimiser les co\u00fbts, la latence et l\u2019efficacit\u00e9 \u00e9nerg\u00e9tique.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>\u2605 <\/strong>Connectivit\u00e9 et infrastructure mat\u00e9rielle<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Les plateformes de calcul haute performance n\u00e9cessitent un r\u00e9seau et des entr\u00e9es\/sorties robustes. Des interfaces physiques fiables garantissent l\u2019int\u00e9grit\u00e9 des donn\u00e9es entre serveurs, acc\u00e9l\u00e9rateurs et appareils p\u00e9riph\u00e9riques.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Mat\u00e9riels associ\u00e9s de <\/strong><a target=\"_blank\" rel=\"\" href=\"https:\/\/www.l-p.com\/\"><strong>LIEN-PP<\/strong><\/a><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>Haute vitesse <a href=\"https:\/\/www.l-p.com\/store-17516-10g-base-t-rj45-connector.htm\" target=\"_blank\" rel=\"\"><strong>\u2014 composants haute performance qui supportent les d\u00e9ploiements de r\u00e9seaux DSL et FTTC.<\/strong><\/a> (1 G\/2,5 G\/10 G, PoE)<\/p><\/li>\n\n\n\n<li><p><strong>Magn\u00e9tiques Ethernet et <\/strong><a href=\"https:\/\/www.l-p.com\/store-17548-lan-transformer.htm\" target=\"_blank\" rel=\"\"><strong>Transformateurs LAN<\/strong><\/a><\/p><\/li>\n\n\n\n<li><p><a href=\"https:\/\/www.l-p.com\/store-25432-optics-transceivers-sfp-modules.htm\" target=\"_blank\" rel=\"\"><strong>Modules \u00e9metteurs-r\u00e9cepteurs optiques SFP\/QSFP<\/strong><\/a> pour le r\u00e9seau de grappes d\u2019IA<\/p><\/li>\n\n\n\n<li><p>Composants Ethernet embarqu\u00e9s industriels pour les passerelles d\u2019IA p\u00e9riph\u00e9rique<\/p><\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Ces composants prennent en charge le transfert de donn\u00e9es \u00e0 haut d\u00e9bit et faible latence \u2014 essentiel pour les syst\u00e8mes d\u2019IA distribu\u00e9s.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>\u2605 <\/strong>Conclusion<\/h2>\n\n\n\n<figure class=\"wp-block-table\">\n<table class=\"has-fixed-layout\">\n<colgroup><col style=\"width: 117px;\"\/><col style=\"width: 260px;\"\/><col style=\"min-width: 25px;\"\/><\/colgroup><tbody><tr><th colspan=\"1\" rowspan=\"1\" colwidth=\"117\"><p>Processeur<\/p><\/th><th colspan=\"1\" rowspan=\"1\" colwidth=\"260\"><p>R\u00f4le principal<\/p><\/th><th colspan=\"1\" rowspan=\"1\"><p>Utilisation recommand\u00e9e<\/p><\/th><\/tr><tr><td colspan=\"1\" rowspan=\"1\" colwidth=\"117\"><p><a target=\"_blank\" rel=\"\" href=\"https:\/\/resourceslp.szlogic.cn\/fr\/glossary\/what-is-cpu-central-processing-unit\/\"><strong>CPU<\/strong><\/a><\/p><\/td><td colspan=\"1\" rowspan=\"1\" colwidth=\"260\"><p>Calcul g\u00e9n\u00e9raliste<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>Contr\u00f4le syst\u00e8me, calcul mixte<\/p><\/td><\/tr><tr><td colspan=\"1\" rowspan=\"1\" colwidth=\"117\"><p><a target=\"_blank\" rel=\"\" href=\"https:\/\/resourceslp.szlogic.cn\/fr\/glossary\/what-is-a-gpu-graphics-processing-units\/\"><strong>GPU<\/strong><\/a><\/p><\/td><td colspan=\"1\" rowspan=\"1\" colwidth=\"260\"><p>Moteur de calcul parall\u00e8le<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>Entra\u00eenement d\u2019IA, charges de travail HPC<\/p><\/td><\/tr><tr><td colspan=\"1\" rowspan=\"1\" colwidth=\"117\"><p><a target=\"_blank\" rel=\"\" href=\"https:\/\/resourceslp.szlogic.cn\/fr\/glossary\/tpu-tensor-processing-unit-google-ai-accelerator\/\"><strong>TPU<\/strong><\/a><\/p><\/td><td colspan=\"1\" rowspan=\"1\" colwidth=\"260\"><p>Acc\u00e9l\u00e9rateur tensoriel<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>Calcul d\u2019IA pour LLM dans le cloud et apprentissage profond<\/p><\/td><\/tr><tr><td colspan=\"1\" rowspan=\"1\" colwidth=\"117\"><p><a target=\"_blank\" rel=\"\" href=\"https:\/\/resourceslp.szlogic.cn\/fr\/glossary\/npu-neural-processing-unit-architecture-edge-ai-explained\/\"><strong>NPU<\/strong><\/a><\/p><\/td><td colspan=\"1\" rowspan=\"1\" colwidth=\"260\"><p>Inf\u00e9rence d\u2019IA p\u00e9riph\u00e9rique<\/p><\/td><td colspan=\"1\" rowspan=\"1\"><p>IA mobile, embarqu\u00e9e et automobile<\/p><\/td><\/tr><\/tbody>\n<\/table>\n<\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">\u00c0 mesure que les syst\u00e8mes d\u2019IA s\u2019\u00e9tendent vers le cloud, le p\u00e9riph\u00e9rique et les dispositifs embarqu\u00e9s, l\u2019avenir r\u00e9side dans <strong>des architectures de calcul hybrides<\/strong> o\u00f9 chaque type de processeur fonctionne dans son domaine optimal.<\/p>","protected":false},"excerpt":{"rendered":"<p>Apprenez \u00e0 distinguer CPU, GPU, TPU et NPU. Ce guide approfondi explique leurs architectures, leurs cas d\u2019usage et leurs performances en mati\u00e8re d\u2019IA, de cloud et de calcul en p\u00e9riph\u00e9rie.<\/p>","protected":false},"author":1,"featured_media":4508,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1],"tags":[22,23,24,25,26],"class_list":["post-4509","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-knowledge-center","tag-integrated-rj45-connectors","tag-link-pp-lan-transformers","tag-link-pp","tag-modular-jack","tag-optics-transceivers"],"blocksy_meta":[],"acf":[],"_links":{"self":[{"href":"https:\/\/resourceslp.szlogic.cn\/fr\/wp-json\/wp\/v2\/posts\/4509","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/resourceslp.szlogic.cn\/fr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/resourceslp.szlogic.cn\/fr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/resourceslp.szlogic.cn\/fr\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/resourceslp.szlogic.cn\/fr\/wp-json\/wp\/v2\/comments?post=4509"}],"version-history":[{"count":4,"href":"https:\/\/resourceslp.szlogic.cn\/fr\/wp-json\/wp\/v2\/posts\/4509\/revisions"}],"predecessor-version":[{"id":10934,"href":"https:\/\/resourceslp.szlogic.cn\/fr\/wp-json\/wp\/v2\/posts\/4509\/revisions\/10934"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/resourceslp.szlogic.cn\/fr\/wp-json\/wp\/v2\/media\/4508"}],"wp:attachment":[{"href":"https:\/\/resourceslp.szlogic.cn\/fr\/wp-json\/wp\/v2\/media?parent=4509"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/resourceslp.szlogic.cn\/fr\/wp-json\/wp\/v2\/categories?post=4509"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/resourceslp.szlogic.cn\/fr\/wp-json\/wp\/v2\/tags?post=4509"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}