\u73fe\u4ee3AI\u57fa\u790e\u8a2d\u65bd\u4ee3\u8868\u8457\u5c08\u696d\u786c\u9ad4\u548c\u8edf\u9ad4\u7d44\u4ef6\u7684\u8907\u96dc\u6574\u5408\u3002\u5176\u57fa\u790e\u662f\u4e00\u500b\u7cbe\u5fc3\u7de8\u6392\u7684\u8655\u7406\u55ae\u5143\u3001\u8a18\u61b6\u9ad4\u5c64\u6b21\u7d50\u69cb\u548c\u4e92\u9023\u6280\u8853\u7cfb\u7d71\u3002\u9019\u4e9b\u5143\u7d20\u5354\u540c\u5de5\u4f5c\uff0c\u70ba\u8907\u96dc\u7684\u6a5f\u5668\u5b78\u7fd2\u64cd\u4f5c\u63d0\u4f9b\u6240\u9700\u7684\u5de8\u5927\u904b\u7b97\u80fd\u529b\u3002\u8a72\u67b6\u69cb\u5fc5\u9808\u5e73\u8861\u539f\u59cb\u8655\u7406\u80fd\u529b\u8207\u8cc7\u6599\u79fb\u52d5\u6548\u7387\u3001\u71b1\u91cf\u7ba1\u7406\u548c\u6574\u9ad4\u7cfb\u7d71\u53ef\u9760\u6027\u3002<\/p>\n

\u8655\u7406\u55ae\u5143\u548c\u52a0\u901f\u5668<\/strong><\/h2>\n\n\n\n\n\n

\u7d44\u4ef6<\/th>\n	\u4e3b\u8981\u529f\u80fd<\/th>\n	\u95dc\u9375\u7279\u6027<\/th>\n<\/tr>\n
CPU<\/td>\n	\u901a\u7528\u904b\u7b97\uff0c\u7cfb\u7d71\u63a7\u5236<\/td>\n	\u591a\u57f7\u884c\u7dd2\uff0c\u9ad8\u7d1a\u5411\u91cf\u8655\u7406<\/td>\n<\/tr>\n
GPU<\/td>\n	\u4e26\u884c\u8655\u7406\uff0c\u5f35\u91cf\u904b\u7b97<\/td>\n	CUDA\u6838\u5fc3\uff0c\u9ad8\u8a18\u61b6\u9ad4\u983b\u5bec<\/td>\n<\/tr>\n
TPU<\/td>\n	ML\u5c08\u7528\u904b\u7b97<\/td>\n	\u77e9\u9663\u904b\u7b97\uff0c\u4f4e\u7cbe\u5ea6\u512a\u5316<\/td>\n<\/tr>\n<\/table>\n \u8a18\u61b6\u9ad4\u5c64\u6b21\u7d50\u69cb\u548c\u5132\u5b58\u7cfb\u7d71<\/strong><\/h2>\n AI\u4f3a\u670d\u5668\u4e2d\u7684\u8a18\u61b6\u9ad4\u67b6\u69cb\u63a1\u7528\u5206\u5c64\u65b9\u6cd5\uff0c\u5e73\u8861\u901f\u5ea6\u548c\u5bb9\u91cf\u9700\u6c42\u3002\u9ad8\u983b\u5bec\u8a18\u61b6\u9ad4\u63d0\u4f9b\u5c0d\u95dc\u9375\u8cc7\u6599\u7684\u5373\u6642\u5b58\u53d6\uff0c\u800c\u5927\u5bb9\u91cf\u5132\u5b58\u7cfb\u7d71\u7dad\u8b77\u5168\u9762\u7684\u8cc7\u6599\u96c6\u3002\u9019\u7a2e\u5c64\u6b21\u7d50\u69cb\u5be6\u73fe\u4e86\u9ad8\u6548\u7684\u8cc7\u6599\u79fb\u52d5\u548c\u8655\u7406\uff1a<\/p>\n \n L1\/L2\/L3\u5feb\u53d6\uff1a\u8d85\u9ad8\u901f\u81e8\u6642\u5132\u5b58<\/li>\n HBM\uff1a\u76f4\u63a5GPU\u6574\u5408\u8a18\u61b6\u9ad4<\/li>\n \u7cfb\u7d71RAM\uff1a\u5927\u5bb9\u91cf\u4e3b\u8a18\u61b6\u9ad4<\/li>\n NVMe\u5132\u5b58\uff1a\u9ad8\u901f\u6301\u4e45\u5132\u5b58<\/li>\n<\/ul>\n \u4e92\u9023\u6280\u8853<\/strong><\/h2>\n \n \u9ad8\u901f\u4e92\u9023\u69cb\u6210\u4e86AI\u57fa\u790e\u8a2d\u65bd\u7684\u795e\u7d93\u7cfb\u7d71\uff0c\u5be6\u73fe\uff1a<\/p>\n \n \u5167\u90e8\u7d44\u4ef6\u901a\u8a0a\n \n NVLink\uff1aGPU\u9593\u50b3\u8f38\u901f\u5ea6\u9ad8\u9054900 GB\/s<\/li>\n PCIe Gen 4\/5\uff1a\u7cfb\u7d71\u7d1a\u9023\u63a5<\/li>\n<\/ul>\n<\/li>\n \u5916\u90e8\u7db2\u8def\u901a\u8a0a\n \n InfiniBand\uff1a\u9ad8\u541e\u5410\u91cf\u53e2\u96c6\u7db2\u8def<\/li>\n 100\/400 GbE\uff1a\u53ef\u64f4\u5c55\u7db2\u8def\u9aa8\u5e79<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/div>\n \u8edf\u9ad4\u5806\u758a\u6574\u5408<\/strong><\/h2>\n \u8edf\u9ad4\u67b6\u69cb\u7531\u591a\u500b\u6574\u5408\u5c64\u7d44\u6210\uff0c\u9019\u4e9b\u5c64\u7ba1\u7406\u8cc7\u6e90\u5206\u914d\u3001\u5de5\u4f5c\u8ca0\u8f09\u5206\u914d\u548c\u8655\u7406\u512a\u5316\u3002\u5f9e\u57fa\u790e\u4f5c\u696d\u7cfb\u7d71\u5230\u5c08\u9580\u7684ML\u6846\u67b6\uff0c\u6bcf\u4e00\u5c64\u90fd\u70baAI\u64cd\u4f5c\u63d0\u4f9b\u57fa\u672c\u670d\u52d9\u3002\u73fe\u4ee3\u90e8\u7f72\u901a\u5e38\u5be6\u65bd\u5bb9\u5668\u5316\u548c\u7de8\u6392\u5de5\u5177\u4ee5\u4fdd\u6301\u9748\u6d3b\u6027\u548c\u53ef\u64f4\u5c55\u6027\u3002<\/p>\n \u5de5\u4f5c\u8ca0\u8f09\u7ba1\u7406\u7cfb\u7d71<\/strong><\/h2>\n\n\n\n\n\n \u7d44\u4ef6<\/th>\n \u529f\u80fd<\/th>\n \u5f71\u97ff<\/th>\n<\/tr>\n \u6392\u7a0b\u5668<\/td>\n \u8cc7\u6e90\u5206\u914d<\/td>\n \u8655\u7406\u6642\u9593\u512a\u5316<\/td>\n<\/tr>\n \u4f47\u5217\u7ba1\u7406\u5668<\/td>\n \u5de5\u4f5c\u8ca0\u8f09\u512a\u5148\u9806\u5e8f<\/td>\n \u9ad8\u6548\u8cc7\u6e90\u5229\u7528<\/td>\n<\/tr>\n \u8ca0\u8f09\u5e73\u8861\u5668<\/td>\n \u6d41\u91cf\u5206\u914d<\/td>\n \u589e\u5f37\u7cfb\u7d71\u7a69\u5b9a\u6027<\/td>\n<\/tr>\n<\/table>\n \u6563\u71b1\u7ba1\u7406\u548c\u51b7\u537b<\/strong><\/h2>\n \u5148\u9032\u7684\u51b7\u537b\u89e3\u6c7a\u65b9\u6848\u5c0d\u65bc\u7dad\u6301\u9ad8\u5bc6\u5ea6AI\u904b\u7b97\u74b0\u5883\u7684\u6700\u4f73\u904b\u884c\u689d\u4ef6\u81f3\u95dc\u91cd\u8981\u3002\u73fe\u4ee3\u7cfb\u7d71\u63a1\u7528\u7a7a\u6c23\u548c\u6db2\u9ad4\u51b7\u537b\u6280\u8853\u7684\u7d44\u5408\uff0c\u5176\u4e2d\u6d78\u6c92\u5f0f\u51b7\u537b\u5728\u6975\u9650\u6548\u80fd\u5834\u666f\u4e2d\u8d8a\u4f86\u8d8a\u53d7\u6b61\u8fce\u3002\u71b1\u7ba1\u7406\u76f4\u63a5\u5f71\u97ff\u7cfb\u7d71\u53ef\u9760\u6027\u548c\u8655\u7406\u80fd\u529b\uff0c\u4f7f\u5176\u6210\u70ba\u57fa\u790e\u8a2d\u65bd\u8a2d\u8a08\u4e2d\u7684\u95dc\u9375\u8003\u616e\u56e0\u7d20\u3002<\/p>\n \u96fb\u6e90\u5206\u914d\u67b6\u69cb<\/strong><\/h2>\n \n \u96fb\u6e90\u57fa\u790e\u8a2d\u65bd\u5fc5\u9808\u63d0\u4f9b\uff1a<\/p>\n \n \u6e05\u6f54\u3001\u7a69\u5b9a\u7684\u96fb\u529b\u4f9b\u61c9<\/li>\n N+1\u62162N\u5197\u9918<\/li>\n \u9ad8\u6548\u7684\u96fb\u529b\u5206\u914d<\/li>\n \u5373\u6642\u76e3\u63a7\u80fd\u529b<\/li>\n<\/ul>\n<\/div>\n \u6548\u80fd\u76e3\u63a7<\/strong><\/h2>\n\n\n\n\n\n \u6307\u6a19\u985e\u5225<\/th>\n \u95dc\u9375\u6307\u6a19<\/th>\n \u76e3\u63a7\u983b\u7387<\/th>\n<\/tr>\n \u7cfb\u7d71\u6548\u80fd<\/td>\n CPU\/GPU\u4f7f\u7528\u7387\uff0c\u8a18\u61b6\u9ad4\u4f7f\u7528<\/td>\n \u5373\u6642<\/td>\n<\/tr>\n \u74b0\u5883<\/td>\n \u6eab\u5ea6\uff0c\u6fd5\u5ea6\uff0c\u6c23\u6d41<\/td>\n \u6301\u7e8c<\/td>\n<\/tr>\n \u96fb\u529b\u6307\u6a19<\/td>\n \u6d88\u8017\uff0c\u6548\u7387<\/td>\n \u6bcf\u79d2<\/td>\n<\/tr>\n<\/table>\n \u7d50\u8ad6<\/strong><\/h2>\n AI\u4f3a\u670d\u5668\u7684\u67b6\u69cb\u4ee3\u8868\u8457\u70ba\u6a5f\u5668\u5b78\u7fd2\u5de5\u4f5c\u8ca0\u8f09\u512a\u5316\u7684\u5c08\u696d\u786c\u9ad4\u548c\u8edf\u9ad4\u7d44\u4ef6\u7684\u8907\u96dc\u6574\u5408\u3002\u900f\u904e\u4f3a\u670d\u5668\u79df\u7528\u89e3\u6c7a\u65b9\u6848\uff0c\u7d44\u7e54\u53ef\u4ee5\u5229\u7528\u9019\u4e9b\u8907\u96dc\u7684\u7cfb\u7d71\uff0c\u540c\u6642\u5c07\u91cd\u9ede\u653e\u5728\u5176\u6838\u5fc3ML\u76ee\u6a19\u4e0a\u3002\u7406\u89e3\u9019\u4e9b\u67b6\u69cb\u539f\u5247\u80fd\u5920\u5e6b\u52a9\u5728\u57fa\u790e\u8a2d\u65bd\u898f\u5283\u548c\u90e8\u7f72\u65b9\u9762\u505a\u51fa\u66f4\u597d\u7684\u6c7a\u7b56\u3002<\/p>\n","protected":false},"excerpt":{"rendered":" \u4eba\u5de5\u667a\u6167\u548c\u6a5f\u5668\u5b78\u7fd2\u7684\u767c\u5c55\u5c0d\u4f3a\u670d\u5668\u79df\u7528\u57fa\u790e\u8a2d\u65bd\u63d0\u51fa\u4e86\u524d\u6240\u672a\u6709\u7684\u9700\u6c42\u3002\u7406\u89e3AI\u4f3a\u670d\u5668\u67b6\u69cb\u53ca\u5176\u5de5\u4f5c\u539f\u7406\u5c0d\u65bc\u5927\u898f\u6a21\u90e8\u7f72 […]<\/p>\n Read More…<\/a><\/p>\n","protected":false},"author":3,"featured_media":22777,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[4815],"tags":[6811,6810,6097,4765,4609,2200],"class_list":["post-22780","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-america-dedicated-server-tc","tag-ml-workloads-tc","tag-ai-server-architecture-tc","tag-machine-learning-infrastructure-tc","tag-gpu-computing-tc","tag-gpu","tag-dedicated-hosting-tc"],"acf":[],"yoast_head":"\n