{"id":35607,"date":"2026-08-26T16:51:00","date_gmt":"2026-08-26T08:51:00","guid":{"rendered":"https:\/\/www.varidata.com\/uncategorized-zh-tw\/gpu-acceleration-for-ai-using-us-high-configuration-servers\/"},"modified":"2026-08-26T16:53:13","modified_gmt":"2026-08-26T08:53:13","slug":"gpu-acceleration-for-ai-using-us-high-configuration-servers","status":"publish","type":"post","link":"https:\/\/www.varidata.com\/zh-tw\/knowledge-tc\/gpu-acceleration-for-ai-using-us-high-configuration-servers\/","title":{"rendered":"\u5229\u7528\u7f8e\u570b\u9ad8\u914d\u7f6e\u4f3a\u670d\u5668\u7684 GPU \u52a0\u901f\u89e3\u6c7a\u65b9\u6848\u9032\u884c AI \u6a21\u578b\u8a13\u7df4"},"content":{"rendered":"<style>\n    table, th, td {\n        border: 1px solid black;\n        border-collapse: collapse;\n    }\n<\/style>\n<p>\u4f60\u6b63\u9762\u81e8\u4e00\u500b\u56b4\u5cfb\u7684\u73fe\u5be6\u3002<a target=\"_blank\" href=\"https:\/\/www.varidata.com\/zh-tw\/knowledge-tc\/nvidias-latest-rubin-platform-sets-a-new-standard-for-ai\/\">AI \u6a21\u578b<\/a>\u6b63\u4ee5\u6307\u6578\u7d1a\u6210\u9577\u3002\u81ea 2010 \u5e74\u4ee5\u4f86\uff0c\u6a21\u578b\u53c3\u6578\u5e7e\u4e4e\u6bcf\u5e74\u7ffb\u4e00\u500d\uff0c\u5df2\u8a18\u9304\u7684\u6700\u5927\u6a21\u578b\u9054\u5230 1.6 \u5146\u53c3\u6578\u3002\u8a13\u7df4\u904b\u7b97\u91cf\u6bcf\u516d\u500b\u6708\u7ffb\u500d\u3002Epoch AI \u9810\u6e2c\uff0c\u9019\u4e00\u8da8\u52e2\u5c07\u4ee5\u6bcf\u5e74 4\u20135 \u500d\u7684\u901f\u5ea6\u6301\u7e8c\u3002\u4f60\u76ee\u524d\u7684\u57fa\u790e\u8a2d\u65bd\u6839\u672c\u7121\u6cd5\u8ddf\u4e0a\u3002<\/p>\n<p>\u7b54\u6848\u5728\u65bc\u7cbe\u5fc3\u5efa\u69cb\u7684 GPU \u52a0\u901f\u89e3\u6c7a\u65b9\u6848\u3002\u73fe\u6709\u7684<a target=\"_self\" href=\"https:\/\/www.varidata.com\/zh-tw\/server\/los-angeles\/cn2\/\">\u7f8e\u570b\u9ad8\u914d\u7f6e\u4f3a\u670d\u5668<\/a>\u80fd\u5920\u63d0\u4f9b\u4f60\u6240\u9700\u7684\u5e73\u884c\u904b\u7b97\u80fd\u529b\u3002\u672c\u6307\u5357\u5c07\u70ba\u4f60\u62c6\u89e3\u6574\u500b\u904e\u7a0b\u3002\u4f60\u5c07\u5b78\u6703\u5982\u4f55\u9078\u64c7\u5408\u9069\u7684 GPU\u3001\u512a\u5316\u6548\u80fd\u4e26\u63a7\u7ba1\u6210\u672c\u3002\u4f60\u5c07\u4e86\u89e3\u5176\u4e2d\u6d89\u53ca\u7684\u786c\u9ad4\u3001\u8edf\u9ad4\u4ee5\u53ca\u7b56\u7565\u6027\u6c7a\u7b56\u3002\u4f60\u5c07\u7372\u5f97\u6709\u6548\u52a0\u901f AI \u5c08\u6848\u7684\u95dc\u9375\u77e5\u8b58\u3002<\/p>\n<h2>\u95dc\u9375\u91cd\u9ede<\/h2>\n<ul>\n<li>\n<p>GPU \u52a0\u901f\u5c0d\u73fe\u4ee3 AI \u8a13\u7df4\u81f3\u95dc\u91cd\u8981\uff0c\u76f8\u8f03 CPU \u53ef\u5be6\u73fe 50\u2013100 \u500d\u52a0\u901f\u3002<\/p>\n<\/li>\n<li>\n<p>\u4f9d\u64da\u6a21\u578b\u898f\u6a21\u8207\u5de5\u4f5c\u8ca0\u8f09\u9078\u64c7 GPU\uff1bA100 \u548c H100 \u662f\u5927\u578b\u6a21\u578b\u7684\u9996\u9078\u3002<\/p>\n<\/li>\n<li>\n<p>\u900f\u904e\u6df7\u5408\u7cbe\u5ea6\u8a13\u7df4\u8207 PyTorch \u7b49\u5206\u6563\u5f0f\u6846\u67b6\u512a\u5316\u6548\u80fd\u3002<\/p>\n<\/li>\n<li>\n<p>\u96f2\u7aef GPU \u57f7\u884c\u500b\u9ad4\u5177\u5099\u8f03\u4f4e\u524d\u671f\u6210\u672c\u8207\u9ad8\u5ea6\u5ef6\u5c55\u6027\uff0c\u800c\u5728\u5730\u90e8\u7f72\u5247\u63d0\u4f9b\u66f4\u9ad8\u63a7\u5236\u529b\u8207\u66f4\u4f4e\u5ef6\u9072\u3002<\/p>\n<\/li>\n<li>\n<p>\u5728\u6548\u80fd\u3001\u9810\u7b97\u8207\u53ef\u64f4\u5145\u6027\u4e4b\u9593\u53d6\u5f97\u5e73\u8861\uff0c\u624d\u80fd\u8b93\u4f60\u7684 AI \u57fa\u790e\u8a2d\u65bd\u5177\u5099\u524d\u77bb\u6027\u3002<\/p>\n<\/li>\n<\/ul>\n<h2>\u70ba\u4ec0\u9ebc\u9700\u8981 GPU \u52a0\u901f\u89e3\u6c7a\u65b9\u6848<\/h2>\n<h3>\u73fe\u4ee3 AI \u7684\u904b\u7b97\u9700\u6c42<\/h3>\n<p>\u8a13\u7df4\u4e00\u500b\u985e\u4f3c GPT-4 \u7684\u6a21\u578b\uff0c\u9810\u4f30\u9700\u8981 1.73 \u00d7 10^25 \u6b21\u6d6e\u9ede\u904b\u7b97\u3002\u9019\u500b\u6578\u5b57\u5e7e\u4e4e\u7121\u6cd5\u76f4\u89c0\u7406\u89e3\u3002\u4e0d\u59a8\u5f9e\u786c\u9ad4\u8457\u624b\u3002\u5728 SemiAnalysis \u7684\u5047\u8a2d\u60c5\u5883\u4e0b\uff0c\u8a13\u7df4 GPT-4 \u9700\u8981\u4e0a\u5343\u5f35 GPU \u6301\u7e8c\u904b\u884c\u6578\u6708\u3002\u5728 20% \u6a21\u578b FLOPs \u4f7f\u7528\u7387\u4e0b\uff0c\u4f60\u9700\u8981 8,800 \u5f35 GPU \u904b\u884c\u4e00\u5e74\uff1b\u5728 50% \u4f7f\u7528\u7387\u4e0b\uff0c\u9019\u500b\u6578\u5b57\u4e0b\u964d\u5230 3,520 \u5f35\u3002\u5373\u4f7f\u5c07\u4f3a\u670d\u5668\u58fd\u547d\u62c9\u9577\u5230\u4e09\u5e74\uff0c\u5728 20% \u4f7f\u7528\u7387\u4e0b\u4f60\u4ecd\u7136\u9700\u8981 2,934 \u5f35 GPU\u3002<\/p>\n<p>\u9019\u4e9b\u6578\u5b57\u63ed\u793a\u4e86\u4e00\u500b\u6839\u672c\u4e8b\u5be6\uff1a\u73fe\u4ee3 AI \u6a21\u578b\u5df2\u9060\u9060\u8d85\u51fa\u50b3\u7d71\u904b\u7b97\u67b6\u69cb\u7684\u80fd\u529b\u3002\u5927\u578b\u8a9e\u8a00\u6a21\u578b\u8207\u96fb\u8166\u8996\u89ba\u7cfb\u7d71\u6703\u540c\u6642\u8655\u7406\u6578\u5341\u5104\u500b\u53c3\u6578\u3002\u6bcf\u4e00\u6b21\u8a13\u7df4\u8fed\u4ee3\u90fd\u9700\u8981\u57f7\u884c\u6578\u4ee5\u767e\u842c\u8a08\u7684\u77e9\u9663\u4e58\u6cd5\u3002\u4f60\u7684 CPU \u7121\u6cd5\u6709\u6548\u8ca0\u8377\u9019\u6a23\u7684\u5de5\u4f5c\u91cf\u3002\u5408\u7406\u5efa\u69cb\u7684 GPU \u52a0\u901f\u89e3\u6c7a\u65b9\u6848\u6703\u76f4\u63a5\u5f71\u97ff\u6a21\u578b\u6e96\u78ba\u5ea6\u8207\u8a13\u7df4\u901f\u5ea6\u3002\u9019\u9805\u6295\u8cc7\u6c7a\u5b9a\u4e86\u4f60\u7684\u5c08\u6848\u662f\u9806\u5229\u63a8\u9032\u9084\u662f\u88ab\u8feb\u505c\u6eef\u3002<\/p>\n<h3>\u5f9e CPU \u5230\u5e73\u884c\u904b\u7b97\u7684\u8f49\u8b8a<\/h3>\n<p>CPU \u6309\u9806\u5e8f\u57f7\u884c\u4efb\u52d9\uff0c\u64c5\u9577\u8655\u7406\u8907\u96dc\u3001\u5206\u652f\u8f03\u591a\u7684\u908f\u8f2f\u3002GPU \u5247\u4e0d\u540c\uff0c\u5b83\u64c1\u6709\u6210\u5343\u4e0a\u842c\u500b\u70ba\u5e73\u884c\u57f7\u884c\u800c\u8a2d\u8a08\u7684\u6838\u5fc3\u3002\u9019\u7a2e\u67b6\u69cb\u5dee\u7570\u5e36\u4f86\u4e86\u5de8\u5927\u7684\u6548\u80fd\u843d\u5dee\u3002<\/p>\n<div fullwidth=\"\" class=\"qc-default-table-wrapper \">\n<table style=\"min-width: 100px;\">\n<colgroup>\n<col style=\"min-width: 25px;\">\n<col style=\"min-width: 25px;\">\n<col style=\"min-width: 25px;\">\n<col style=\"min-width: 25px;\"><\/colgroup>\n<tbody>\n<tr>\n<th colspan=\"1\" rowspan=\"1\">\n<p>\u6307\u6a19<\/p>\n<\/th>\n<th colspan=\"1\" rowspan=\"1\">\n<p>GPU \u6548\u80fd<\/p>\n<\/th>\n<th colspan=\"1\" rowspan=\"1\">\n<p>CPU \u6548\u80fd<\/p>\n<\/th>\n<th colspan=\"1\" rowspan=\"1\">\n<p>GPU \u512a\u52e2<\/p>\n<\/th>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u904b\u7b97\u541e\u5410\u91cf<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>&gt;100 teraFLOPS<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>1\u20132 teraFLOPS<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>50\u2013100 \u500d<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u8a18\u61b6\u9ad4\u983b\u5bec<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>1\u20132 TB\/s<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u7d04 100 GB\/s<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>10\u201320 \u500d<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">\n<p>ImageNet CNN \u8a13\u7df4\u6642\u9593<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>1\u20132 \u5929\uff08\u55ae\u5f35 V100\uff09<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>2\u20133 \u9031<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>10\u201350 \u500d<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">\n<p>BERT \u8a13\u7df4\u6642\u9593<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>4 \u5929\uff088 \u5f35 V100 GPU\uff09<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>1\u20132 \u500b\u6708<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u7d04 7\u201315 \u500d<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>\u6578\u64da\u5df2\u7d93\u8aaa\u660e\u4e00\u5207\u3002\u53f2\u4e39\u4f5b\u7814\u7a76\u4eba\u54e1\u767c\u73fe\uff0c\u76f8\u8f03 CPU\uff0c\u63a1\u7528 GPU \u52a0\u901f\u7684\u5377\u7a4d\u7db2\u8def\u53ef\u4ee5\u5be6\u73fe\u8d85\u904e 20 \u500d\u7684\u52a0\u901f\u3002\u80fd\u6e90\u6548\u7387\u540c\u6a23\u5927\u5e45\u63d0\u5347\uff1a\u5728\u795e\u7d93\u7db2\u8def\u8a13\u7df4\u4e0a\uff0cGPU \u52a0\u901f\u7684\u80fd\u6e90\u6548\u7387\u6700\u9ad8\u53ef\u63d0\u5347 15 \u500d\u3002\u4ee5\u6548\u80fd\u6298\u7b97\u5f8c\u7684\u6574\u9ad4\u6301\u6709\u6210\u672c\u4f86\u770b\uff0cGPU \u7cfb\u7d71\u5728\u6df1\u5ea6\u5b78\u7fd2\u5de5\u4f5c\u8ca0\u8f09\u4e0a\u80fd\u63d0\u4f9b 3\u20134 \u500d\u7684\u512a\u52e2\u3002<\/p>\n<p>\u300cGPU \u52a0\u901f\u53ef\u4ee5\u5c07\u8907\u96dc\u795e\u7d93\u7db2\u8def\u7684\u8a13\u7df4\u6642\u9593\u5f9e\u6578\u9031\u7e2e\u77ed\u5230\u6578\u5929\uff0c\u751a\u81f3\u6578\u5c0f\u6642\uff0c\u5fb9\u5e95\u6539\u8b8a AI \u958b\u767c\u7684\u7bc0\u594f\u3002\u300d\u2014\u2014<em>\u300a\u6a5f\u5668\u5b78\u7fd2\u7814\u7a76\u671f\u520a\u300b\uff08Journal of Machine Learning Research\uff09<\/em><\/p>\n<p>\u4f60\u5fc5\u9808\u505a\u51fa\u9078\u64c7\uff1a\u7e7c\u7e8c\u4ef0\u8cf4 CPU \u67b6\u69cb\uff0c\u4e26\u63a5\u53d7\u52d5\u8f12\u6578\u9031\u7684\u8a13\u7df4\u9031\u671f\uff1b\u9084\u662f\u63a1\u7528 GPU \u52a0\u901f\u89e3\u6c7a\u65b9\u6848\uff0c\u628a\u8a13\u7df4\u6642\u9593\u58d3\u7e2e\u5230\u6578\u5929\u3002\u5f8c\u8005\u610f\u5473\u8457\u66f4\u5feb\u7684\u8fed\u4ee3\u901f\u5ea6\u3001\u66f4\u591a\u5be6\u9a57\u6a5f\u6703\uff0c\u4ee5\u53ca\u6700\u7d42\u66f4\u597d\u7684\u6a21\u578b\u8868\u73fe\u3002\u5c0d\u4efb\u4f55\u56b4\u8085\u7684 AI \u5c08\u6848\u800c\u8a00\uff0c\u9078\u64c7\u5df2\u7d93\u975e\u5e38\u660e\u78ba\u3002<\/p>\n<h2>\u9ad8\u6548\u80fd AI \u4f3a\u670d\u5668\u7684\u6838\u5fc3\u7d44\u6210<\/h2>\n<h3>\u6838\u5fc3\u52d5\u529b\uff1aNVIDIA A100 \u8207 H100 GPU<\/h3>\n<p>\u4f60\u7684 GPU \u52a0\u901f\u89e3\u6c7a\u65b9\u6848\u5f9e\u52a0\u901f\u5361\u672c\u8eab\u958b\u59cb\u3002NVIDIA \u7684 A100 \u548c H100 \u5e7e\u4e4e\u4e3b\u5c0e\u4e86 AI \u8a13\u7df4\u9818\u57df\u3002\u9019\u4e9b GPU \u63d0\u4f9b\u4e86 CPU \u7121\u6cd5\u6bd4\u64ec\u7684\u5927\u898f\u6a21\u5e73\u884c\u904b\u7b97\u80fd\u529b\u3002H100 \u662f\u76ee\u524d\u7684\u65d7\u8266\u7522\u54c1\uff0c\u5176 FP16 \u6548\u80fd\u5927\u7d04\u53ef\u9054 2,000 teraFLOPS\uff0c\u800c A100 \u5247\u70ba 312 teraFLOPS\u3002\u9019\u500b\u5dee\u8ddd\u6703\u76f4\u63a5\u53cd\u6620\u5728\u8a13\u7df4\u901f\u5ea6\u4e0a\u3002<\/p>\n<p>\u8a18\u61b6\u9ad4\u983b\u5bec\u540c\u6a23\u95dc\u9375\u3002H100 \u63a1\u7528\u983b\u5bec\u9054 3,200 GB\/s \u7684 HBM3 \u8a18\u61b6\u9ad4\uff1bA100 \u7684 80GB \u7248\u672c\u4f7f\u7528\u983b\u5bec\u70ba 1,935 GB\/s \u7684 HBM2e\u3002\u63a5\u8fd1\u5169\u500d\u7684\u983b\u5bec\u610f\u5473\u8457\u5728\u8a13\u7df4\u8fed\u4ee3\u4e2d\u66f4\u5feb\u7684\u8cc7\u6599\u50b3\u8f38\u3002\u5c0d\u65bc\u6df1\u5ea6\u5b78\u7fd2\u63a8\u85a6\u7cfb\u7d71\u7b49\u5927\u578b\u6a21\u578b\u800c\u8a00\uff0cA100 80GB \u6bcf\u500b\u7bc0\u9ede\u53ef\u5be6\u73fe\u6700\u9ad8 1.3 TB \u7684\u7d71\u4e00\u8a18\u61b6\u9ad4\uff0c\u76f8\u8f03 40GB \u7248\u672c\u5e36\u4f86\u6700\u9ad8 3 \u500d\u7684\u8f38\u9001\u91cf\u63d0\u5347\u3002<\/p>\n<p>\u5c0d\u65bc\u5305\u542b\u6d77\u91cf\u8cc7\u6599\u8868\u7684\u8d85\u5927\u898f\u6a21\u6a21\u578b\uff08\u4f8b\u5982\u6df1\u5ea6\u5b78\u7fd2\u63a8\u85a6\u6a21\u578b DLRM\uff09\uff0cA100 80GB \u6bcf\u7bc0\u9ede\u53ef\u63d0\u4f9b\u9ad8\u9054 1.3 TB \u7684\u7d71\u4e00\u8a18\u61b6\u9ad4\uff0c\u4e26\u80fd\u5be6\u73fe\u6700\u591a 3 \u500d\u65bc A100 40GB \u7684\u8f38\u9001\u91cf\u63d0\u5347\u3002<\/p>\n<p>H100 \u4e5f\u5f15\u5165\u4e86 FP8 Tensor Core \u652f\u63f4\uff0c\u5176\u6548\u80fd\u53ef\u9054 4,000 teraFLOPS\uff0c\u800c A100 \u5b8c\u5168\u4e0d\u652f\u63f4 FP8\u3002\u5c0d\u65bc\u64c1\u6709 1,750 \u5104\u53c3\u6578\u7684 GPT-3 \u7b49\u7d1a\u6a21\u578b\uff0cH100 \u7684\u8a13\u7df4\u901f\u5ea6\u53ef\u6bd4 A100 \u5feb\u81f3 4 \u500d\u3002\u4f60\u9700\u8981\u5728\u6548\u80fd\u6536\u76ca\u8207\u6210\u672c\u4e4b\u9593\u6b0a\u8861\uff1aA100 \u96f6\u552e\u50f9\u7d04\u70ba 17,000 \u7f8e\u5143\uff0c\u800c H100 \u7d04\u70ba 30,000 \u7f8e\u5143\u3002\u79df\u7528\u50f9\u683c\u540c\u6a23\u53cd\u6620\u4e86\u9019\u500b\u5dee\u8ddd\uff1aA100 \u57f7\u884c\u500b\u9ad4\u7d04\u70ba\u6bcf\u5c0f\u6642 1.50 \u7f8e\u5143\uff0c\u800c H100 \u57f7\u884c\u500b\u9ad4\u5247\u5728\u6bcf\u5c0f\u6642 3\u201310 \u7f8e\u5143\u4e4b\u9593\u3002<\/p>\n<div fullwidth=\"\" class=\"qc-default-table-wrapper \">\n<table style=\"min-width: 75px;\">\n<colgroup>\n<col style=\"min-width: 25px;\">\n<col style=\"min-width: 25px;\">\n<col style=\"min-width: 25px;\"><\/colgroup>\n<tbody>\n<tr>\n<th colspan=\"1\" rowspan=\"1\">\n<p>\u6307\u6a19<\/p>\n<\/th>\n<th colspan=\"1\" rowspan=\"1\">\n<p>A100<\/p>\n<\/th>\n<th colspan=\"1\" rowspan=\"1\">\n<p>H100<\/p>\n<\/th>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">\n<p>FP16 Tensor Core<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>312 TFLOPS<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>2,000 TFLOPS<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u8a18\u61b6\u9ad4\u983b\u5bec<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>1,935 GB\/s\uff0880GB\uff09<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>3,200 GB\/s<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">\n<p>FP8 Tensor Core<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u4e0d\u652f\u63f4<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>4,000 TFLOPS<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u6700\u5927 TDP\uff08SXM\uff09<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>400W<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>700W<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<h3>\u914d\u89d2\u9663\u5bb9\uff1aCPU\u3001\u8a18\u61b6\u9ad4\u8207\u5132\u5b58<\/h3>\n<p>GPU \u7121\u6cd5\u55ae\u7368\u904b\u4f5c\u3002\u4f60\u7684\u4f3a\u670d\u5668\u67b6\u69cb\u5fc5\u9808\u70ba\u52a0\u901f\u5361\u63d0\u4f9b\u6301\u7e8c\u7a69\u5b9a\u7684\u8cc7\u6599\u4f9b\u7d66\uff0c\u907f\u514d\u51fa\u73fe\u74f6\u9838\u3002CPU \u8ca0\u8cac\u7cfb\u7d71\u8abf\u5ea6\u8207\u8cc7\u6599\u7de8\u6392\uff0c\u8655\u7406\u4e0d\u9069\u5408\u5927\u898f\u6a21\u5e73\u884c\u7684\u4efb\u52d9\u3002\u4f60\u9700\u8981\u4e00\u9846\u81f3\u5c11 16 \u5be6\u9ad4\u6838\u5fc3\u7684\u4f3a\u670d\u5668\u7d1a AMD EPYC \u6216 Intel Xeon \u8655\u7406\u5668\u3002\u8db3\u5920\u5f37\u7684\u55ae\u6838\u6548\u80fd\u53ef\u4ee5\u907f\u514d CPU \u62d6\u7d2f GPU\u3002<\/p>\n<p>\u8a18\u61b6\u9ad4\u662f\u9023\u63a5 CPU\u3001GPU \u8207\u5132\u5b58\u7684\u6a4b\u6a11\u3002\u7cfb\u7d71\u8a18\u61b6\u9ad4\u5bb9\u91cf\u81f3\u5c11\u61c9\u70ba GPU \u986f\u793a\u8a18\u61b6\u9ad4\u7e3d\u548c\u7684\u5169\u500d\u3002\u5c0d\u65bc\u4e00\u53f0\u642d\u8f09 8 \u5f35 80GB GPU \u7684\u4f3a\u670d\u5668\u800c\u8a00\uff0c\u81f3\u5c11\u9700\u8981 1.28 TB \u8a18\u61b6\u9ad4\u3002\u8a18\u61b6\u9ad4\u4e0d\u8db3\u6703\u5c0e\u81f4\u983b\u7e41\u4ea4\u63db\uff0c\u9032\u800c\u56b4\u91cd\u62d6\u6162\u8a13\u7df4\u901f\u5ea6\u3002\u5132\u5b58\u5c64\u9762\u5247\u5fc5\u9808\u9078\u64c7 NVMe SSD\uff0c\u6a5f\u68b0\u786c\u789f\u6839\u672c\u8ddf\u4e0d\u4e0a\u6d3b\u8e8d AI \u5de5\u4f5c\u8ca0\u8f09\u30021TB NVMe SSD \u662f\u5408\u7406\u7684\u8d77\u9ede\uff0c\u4e26\u5efa\u8b70\u5c07\u4f5c\u696d\u7cfb\u7d71\u8207\u6a21\u578b\u8cc7\u6599\u5206\u5225\u5b58\u653e\u5728\u4e0d\u540c\u78c1\u789f\u3002<\/p>\n<p>\u7db2\u8def\u662f\u6700\u5f8c\u4e00\u584a\u62fc\u5716\u3002\u591a\u4f3a\u670d\u5668\u5206\u6563\u5f0f\u8a13\u7df4\u9700\u8981\u9ad8\u983b\u5bec\u4e92\u806f\uff0c10GbE\u300125GbE \u6216 InfiniBand \u7b49\u65b9\u6848\u53ef\u4ee5\u907f\u514d\u8cc7\u6599\u50b3\u8f38\u6210\u70ba\u74f6\u9838\u3002Exxact\u3001Cisco \u7b49\u9818\u5148\u4f9b\u61c9\u5546\u63d0\u4f9b\u9762\u5411 HPC \u8207 AI \u5de5\u4f5c\u8ca0\u8f09\u6700\u4f73\u5316\u7684 GPU \u4f3a\u670d\u5668\uff0c\u9019\u4e9b\u7cfb\u7d71\u901a\u5e38\u652f\u63f4 PCIe 4.0 \u6216 5.0\uff0c\u4e26\u914d\u5099\u9032\u968e\u6563\u71b1\u65b9\u6848\u3002\u9ad8\u98a8\u91cf\u8a2d\u8a08\u53ef\u5728\u9577\u6642\u9593\u9ad8\u8ca0\u8f09\u4e0b\u7dad\u6301\u7a69\u5b9a\u6548\u80fd\u3002\u4e00\u500b\u5b8c\u5584\u7684 GPU \u52a0\u901f\u89e3\u6c7a\u65b9\u6848\u4ef0\u8cf4\u6240\u6709\u5143\u4ef6\u7684\u5354\u540c\u904b\u4f5c\u3002<\/p>\n<h2>\u70ba\u4f60\u7684\u9700\u6c42\u9078\u64c7\u5408\u9069\u7684 GPU \u4f3a\u670d\u5668<\/h2>\n<h3>\u5c07\u786c\u9ad4\u8207\u6a21\u578b\u898f\u6a21\u548c\u8907\u96dc\u5ea6\u914d\u5c0d<\/h3>\n<p>\u6a21\u578b\u53c3\u6578\u898f\u6a21\u76f4\u63a5\u6c7a\u5b9a\u4f60\u7684\u786c\u9ad4\u9700\u6c42\u3002\u4e00\u500b 70 \u5104\u53c3\u6578\u7684\u6a21\u578b\uff0c\u5728 FP16 \u63a8\u7406\u6642\u5927\u7d04\u9700\u8981 12\u201313 GB \u986f\u793a\u8a18\u61b6\u9ad4\uff1b130 \u5104\u53c3\u6578\u7684\u6a21\u578b\u7d04\u9700 24 GB\uff1b65B \u6a21\u578b\u5247\u6703\u8d85\u904e 130 GB \u986f\u793a\u8a18\u61b6\u9ad4\uff0c\u8feb\u4f7f\u4f60\u63a1\u7528\u591a GPU \u67b6\u69cb\uff0c\u6216\u9078\u64c7\u64c1\u6709 80GB \u986f\u793a\u8a18\u61b6\u9ad4\u7684\u8cc7\u6599\u4e2d\u5fc3\u7d1a GPU\u3002\u9019\u4e9b\u6578\u5b57\u69cb\u6210\u4e86\u4f60\u7684\u8d77\u9ede\u3002<\/p>\n<p>\u8a13\u7df4\u6703\u9032\u4e00\u6b65\u653e\u5927\u9700\u6c42\u3002\u8a13\u7df4\u6240\u9700\u986f\u793a\u8a18\u61b6\u9ad4\u901a\u5e38\u662f\u6a21\u578b\u5927\u5c0f\u7684 2\u20134 \u500d\u3002\u4e00\u500b 130 \u5104\u53c3\u6578\u6a21\u578b\u8a13\u7df4\u5927\u7d04\u9700\u8981 97 GB \u986f\u793a\u8a18\u61b6\u9ad4\u3002LoRA\u3001\u68af\u5ea6\u6aa2\u67e5\u9ede\uff08gradient checkpointing\uff09\u6216\u91cf\u5316\u7b49\u6280\u8853\u53ef\u4ee5\u964d\u4f4e\u9019\u500b\u8ca0\u64d4\u3002\u5f71\u50cf\u6a21\u578b\u7684\u898f\u5247\u5247\u7565\u6709\u4e0d\u540c\uff1aSDXL \u63a8\u7406\u81f3\u5c11\u9700\u8981 8 GB \u986f\u793a\u8a18\u61b6\u9ad4\uff0c\u5efa\u8b70 16 GB\uff1bStyleGAN2 \u6216 StyleGAN3 \u7684\u8a13\u7df4\u5247\u9700\u8981 1\u20138 \u5f35\u81f3\u5c11 12 GB \u986f\u793a\u8a18\u61b6\u9ad4\u7684\u9ad8\u968e GPU\u3002<\/p>\n<p>\u5de5\u4f5c\u8ca0\u8f09\u985e\u578b\u540c\u6a23\u91cd\u8981\u3002\u63a8\u7406\u4f3a\u670d\u5668\u9700\u8981\u70ba\u6bcf\u4f4d\u4f7f\u7528\u8005\u63d0\u4f9b\u5145\u8db3\u986f\u793a\u8a18\u61b6\u9ad4\u53ca\u7a69\u5b9a\u6392\u7a0b\uff1b\u8a13\u7df4\u4f3a\u670d\u5668\u5247\u66f4\u4f9d\u8cf4 HBM \u5bb9\u91cf\u3001\u9ad8\u901f\u4e92\u806f\u8207\u8cc7\u6599\u4e2d\u5fc3\u7d1a\u6563\u71b1\u3002\u5c0d\u65bc\u53c3\u6578\u91cf\u5728 100 \u5104\u4ee5\u5167\u7684\u5c0f\u578b\u6a21\u578b\uff0c\u5728\u5730\u5c0f\u578b\u53e2\u96c6\u662f\u53ef\u884c\u8def\u5f91\u3002\u4e00\u500b 70 \u5104\u53c3\u6578\u6a21\u578b\u5728\u6df7\u5408\u7cbe\u5ea6\u8a13\u7df4\u4e0b\u5927\u7d04\u4f7f\u7528 14 GB \u986f\u793a\u8a18\u61b6\u9ad4\u3002\u4f60\u53ef\u4ee5\u5f9e 4 \u5f35 16 GB \u986f\u793a\u8a18\u61b6\u9ad4\u7684 GPU\uff08\u5982 RTX 3090 \u6216 4090\uff09\u8d77\u6b65\uff1b\u7406\u60f3\u914d\u7f6e\u5247\u662f 2\u20134 \u5f35 40GB A100\u3002\u9019\u500b\u914d\u7f6e\u5728 8 \u5f35 A100 \u4e0a\u5927\u7d04\u53ef\u5728\u4e00\u500b\u6708\u5167\u5b8c\u6210 1 \u5146 token \u7684\u8a13\u7df4\u3002\u7cfb\u7d71\u8a18\u61b6\u9ad4\u81f3\u5c11\u9700\u8981 128 GB\uff0c\u8cc7\u6599\u96c6\u5132\u5b58 1\u20135 TB\uff0c\u6aa2\u67e5\u9ede\u5927\u7d04 500 GB\uff0c\u7db2\u8def\u983b\u5bec\u5247\u5efa\u8b70\u9054\u5230 10 Gbps \u4ee5\u4e0a\u3002<\/p>\n<p>\u5e73\u884c\u7b56\u7565\u6703\u96a8\u6a21\u578b\u898f\u6a21\u800c\u8b8a\u5316\u3002\u53c3\u6578\u91cf\u5c0f\u65bc 70 \u5104\u7684\u6a21\u578b\uff0c\u4f7f\u7528 2\u20138 \u5f35 GPU \u505a\u8cc7\u6599\u5e73\u884c\u5373\u53ef\u53d6\u5f97\u4e0d\u932f\u6210\u6548\uff1b7B\u201370B \u4e4b\u9593\u901a\u5e38\u9700\u8981\u6df7\u5408\u5e73\u884c\uff1b\u8d85\u904e 70B \u7684\u8d85\u5927\u6a21\u578b\uff0c\u5247\u9700\u8981\u5c07\u7ba1\u7dda\u5e73\u884c\u3001\u5f35\u91cf\u5e73\u884c\u8207\u8cc7\u6599\u5e73\u884c\u7d50\u5408\u4f7f\u7528\u3002\u6700\u4f73\u5316\u5668\u8a18\u61b6\u9ad4\u9700\u6c42\u6703\u9032\u4e00\u6b65\u653e\u5927\u9019\u500b\u6311\u6230\uff0c\u4f8b\u5982 Adam \u6700\u4f73\u5316\u5668\u901a\u5e38\u6703\u8b93\u8a18\u61b6\u9ad4\u5360\u7528\u589e\u52a0\u4e09\u500d\u3002<\/p>\n<h3>\u5728\u6548\u80fd\u3001\u9810\u7b97\u8207\u53ef\u64f4\u5145\u6027\u4e4b\u9593\u53d6\u5f97\u5e73\u8861<\/h3>\n<p>\u9810\u7b97\u6703\u5f71\u97ff\u4f60\u7684\u90e8\u7f72\u7b56\u7565\u3002\u96f2\u7aef GPU \u4f3a\u670d\u5668\u63d0\u4f9b\u96a8\u9078\u5b58\u53d6\uff0c\u4e0d\u9700\u8981\u81ea\u5df1\u7ba1\u7406\u786c\u9ad4\uff0c\u63a1\u7528\u4f9d\u4f7f\u7528\u91cf\u8a08\u8cbb\u3002\u9019\u7a2e\u6a21\u5f0f\u9069\u5408\u9031\u671f\u8f03\u77ed\u3001\u8ca0\u8f09\u6ce2\u52d5\u5927\u7684\u5c08\u6848\u3002\u5c08\u7528 GPU \u57f7\u884c\u500b\u9ad4\u5247\u70ba\u6b63\u5f0f\u4e0a\u7dda\u7684\u6a21\u578b\u63d0\u4f9b\u7a69\u5b9a\u6548\u80fd\u3002\u88f8\u6a5f\u4f3a\u670d\u5668\uff08bare-metal\uff09\u53ef\u8b93\u4f60\u5b8c\u5168\u638c\u63a7\u786c\u9ad4\uff0c\u4e26\u6d88\u9664\u865b\u64ec\u5316\u958b\u92b7\uff0c\u4f46\u6210\u672c\u8f03\u9ad8\uff0c\u4e5f\u9700\u8981\u66f4\u591a\u71df\u904b\u7dad\u8b77\u6295\u5165\u3002<\/p>\n<p>\u6210\u672c\u6548\u7387\u95dc\u9375\u53d6\u6c7a\u65bc\u4f7f\u7528\u7387\u3002\u53ea\u6709\u5728\u4f60\u9700\u8981 7\u00d724 \u5c0f\u6642\u904b\u884c\u5927\u898f\u6a21\u8a13\u7df4\u4efb\u52d9\u6642\uff0c\u88f8\u6a5f GPU \u5728\u7d93\u6fdf\u4e0a\u624d\u66f4\u5212\u7b97\u3002\u865b\u64ec\u5316 GPU \u5247\u53ef\u4ee5\u5c07\u4e00\u5f35 A100 \u5207\u5206\u7d66\u591a\u500b\u5de5\u4f5c\u8ca0\u8f09\u4f7f\u7528\uff0c\u4f60\u53ef\u80fd\u53ea\u9700\u70ba\u6bcf\u500b\u5de5\u4f5c\u8ca0\u8f09\u652f\u4ed8\u6bcf\u5c0f\u6642 2\u20133 \u7f8e\u5143\uff0c\u800c\u975e\u70ba\u6574\u5f35 GPU \u652f\u4ed8\u6bcf\u5c0f\u6642 12 \u7f8e\u5143\uff0c\u5f9e\u800c\u6700\u5927\u9650\u5ea6\u964d\u4f4e GPU \u9592\u7f6e\u6642\u9593\u3002<\/p>\n<p>\u4e92\u806f\u6280\u8853\u4e5f\u6703\u986f\u8457\u5f71\u97ff\u6210\u672c\u8207\u6548\u80fd\u3002\u5c0d\u65bc\u898f\u6a21\u5728 512 \u5f35 GPU \u4ee5\u5167\u7684\u53e2\u96c6\uff0c\u57fa\u65bc\u4e59\u592a\u7db2\u8def\u7684 RoCE \u53ef\u4ee5\u5728\u6210\u672c\u7d04\u70ba InfiniBand \u4e00\u534a\u7684\u60c5\u6cc1\u4e0b\uff0c\u63d0\u4f9b 85\u201395% \u7684\u6548\u80fd\uff1b\u5c0d\u65bc 2,048 \u5f35 GPU \u4ee5\u4e0a\u7684\u8d85\u5927\u898f\u6a21\u53e2\u96c6\uff0cInfiniBand \u7684\u6ea2\u50f9\u5247\u66f4\u70ba\u5408\u7406\u3002\u4f60\u9700\u8981\u4f9d\u64da\u5be6\u969b\u53e2\u96c6\u898f\u6a21\u4f86\u9078\u64c7\u3002<\/p>\n<p>\u82e5\u8981\u5177\u5099\u524d\u77bb\u6027\uff0c\u5c31\u5fc5\u9808\u63d0\u524d\u898f\u5283\u3002\u55ae\u4f3a\u670d\u5668\u591a GPU \u914d\u7f6e\u53ef\u4ee5\u652f\u63f4\u5206\u6563\u5f0f\u8a13\u7df4\uff1bGPU \u76f4\u901a\u8207\u5bb9\u5668\u652f\u63f4\u5247\u5141\u8a31\u4f60\u900f\u904e Docker \u6216 Kubernetes \u5be6\u73fe\u6a6b\u5411\u64f4\u5145\uff1b\u63a1\u7528 PCIe Gen4 NVMe SSD \u4e26\u914d\u7f6e RAID\uff0c\u53ef\u4ee5\u5728\u8cc7\u6599\u96c6\u64f4\u5bb9\u6642\u6709\u6548\u907f\u514d I\/O \u74f6\u9838\uff1b\u9ad8\u6838\u5fc3\u6578\u8655\u7406\u5668\u642d\u914d DDR5 ECC \u8a18\u61b6\u9ad4\u53ef\u4ee5\u78ba\u4fdd\u591a\u57f7\u884c\u7dd2\u4efb\u52d9\u7a69\u5b9a\u904b\u4f5c\u3002<\/p>\n<p>\u4f60\u7684 GPU \u52a0\u901f\u89e3\u6c7a\u65b9\u6848\u5fc5\u9808\u5728\u7576\u524d\u9700\u6c42\u8207\u672a\u4f86\u6210\u9577\u4e4b\u9593\u53d6\u5f97\u5e73\u8861\u3002\u5f9e\u76ee\u524d\u6a21\u578b\u9700\u6c42\u51fa\u767c\uff0c\u9078\u64c7\u53ef\u4ee5\u5f8c\u7e8c\u64f4\u5145 GPU \u6578\u91cf\uff0c\u6216\u5e73\u6ed1\u9077\u79fb\u5230\u96f2\u7aef\u57f7\u884c\u500b\u9ad4\u7684\u786c\u9ad4\u67b6\u69cb\u3002\u9019\u6a23\u7684\u7b56\u7565\u80fd\u78ba\u4fdd\u4f60\u7684\u6295\u8cc7\u5728\u672a\u4f86\u5f88\u9577\u4e00\u6bb5\u6642\u9593\u5167\u6301\u7e8c\u767c\u63ee\u50f9\u503c\u3002<\/p>\n<h2>\u900f\u904e\u8edf\u9ad4\u8207\u6846\u67b6\u512a\u5316\u6548\u80fd<\/h2>\n<h3>\u5145\u5206\u904b\u7528 CUDA\u3001TensorFlow \u8207 PyTorch<\/h3>\n<p>\u4f60\u7684 GPU \u52a0\u901f\u89e3\u6c7a\u65b9\u6848\u9060\u4e0d\u53ea\u786c\u9ad4\uff0c\u8edf\u9ad4\u5806\u758a\u6c7a\u5b9a\u4e86\u4f60\u80fd\u5426\u771f\u6b63\u69a8\u4e7e\u9019\u4e9b\u6602\u8cb4 GPU \u7684\u6548\u80fd\u3002CUDA \u662f NVIDIA GPU \u7684\u57fa\u77f3\uff0c\u9019\u500b\u5e73\u884c\u904b\u7b97\u5e73\u53f0\u70ba\u4f60\u63d0\u4f9b\u4e86\u5b58\u53d6\u5e95\u5c64\u786c\u9ad4\u80fd\u529b\u7684\u4ecb\u9762\u3002\u5982\u679c\u9a45\u52d5\u8207 CUDA \u5de5\u5177\u5305\u4e0d\u662f\u6700\u65b0\uff0c\u4f60\u5c31\u6703\u767d\u767d\u6d6a\u8cbb\u53ef\u89c0\u6548\u80fd\u3002<\/p>\n<p>\u6df1\u5ea6\u5b78\u7fd2\u6846\u67b6\u7684\u9078\u64c7\u6703\u6975\u5927\u5f71\u97ff\u4f60\u7684\u65e5\u5e38\u958b\u767c\u9ad4\u9a57\u3002PyTorch \u8207 TensorFlow \u5728 NVIDIA \u4f3a\u670d\u5668\u4e0a\u90fd\u80fd\u63d0\u4f9b\u512a\u7570\u6548\u80fd\uff0c\u4f46\u5404\u6709\u6240\u9577\u3002\u4e0b\u8868\u5c55\u793a\u4e86\u5b83\u5011\u5728\u5e38\u898b\u5de5\u4f5c\u8ca0\u8f09\u4e0a\u7684\u5c0d\u6bd4\uff1a<\/p>\n<div fullwidth=\"\" class=\"qc-default-table-wrapper \">\n<table style=\"min-width: 100px;\">\n<colgroup>\n<col style=\"min-width: 25px;\">\n<col style=\"min-width: 25px;\">\n<col style=\"min-width: 25px;\">\n<col style=\"min-width: 25px;\"><\/colgroup>\n<tbody>\n<tr>\n<th colspan=\"1\" rowspan=\"1\">\n<p>\u5de5\u4f5c\u8ca0\u8f09<\/p>\n<\/th>\n<th colspan=\"1\" rowspan=\"1\">\n<p>PyTorch 2.x\uff08torch.compile\uff09<\/p>\n<\/th>\n<th colspan=\"1\" rowspan=\"1\">\n<p>TensorFlow 2.x\uff08XLA\uff09<\/p>\n<\/th>\n<th colspan=\"1\" rowspan=\"1\">\n<p>\u95dc\u9375\u6d1e\u898b<\/p>\n<\/th>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">\n<p>ResNet-50\uff08A100\uff0cFP16\uff09<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u7d04 1,050 img\/s<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u7d04 980 img\/s<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u555f\u7528 compile \u6642\uff0cPyTorch \u7565\u5feb<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">\n<p>BERT-Large \u5fae\u8abf\uff08A100\uff09<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u7d04 145 samples\/s<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u7d04 140 samples\/s<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u6548\u80fd\u5e7e\u4e4e\u76f8\u540c<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">\n<p>GPT-2 \u8a13\u7df4\uff08H100\uff09<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u539f\u578b\u958b\u767c\u8f03\u5feb<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u5927\u898f\u6a21\u8a13\u7df4\u8f03\u5feb<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u6548\u679c\u53d6\u6c7a\u65bc\u6700\u4f73\u5316\u6295\u5165<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">\n<p>Stable Diffusion\uff08RTX 4090\uff09<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u7d04 4.2 it\/s<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u7d04 3.8 it\/s<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>PyTorch \u64c1\u6709\u66f4\u6210\u719f\u7684\u793e\u7fa4\u7b97\u5b50<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u5927\u898f\u6a21\u5206\u6563\u5f0f\uff08256 \u5f35 GPU\uff09<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u8868\u73fe\u76f8\u8fd1<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u5728 XLA \u52a0\u6301\u4e0b\u7565\u4f54\u512a\u52e2<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>TensorFlow \u7684\u5716\u6700\u4f73\u5316\u5728\u8d85\u5927\u898f\u6a21\u6642\u66f4\u6709\u512a\u52e2<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>\u5728\u5927\u578b\u8a9e\u8a00\u6a21\u578b\u958b\u767c\u9818\u57df\uff0cPyTorch \u5df2\u4f54\u64da\u4e3b\u5c0e\u5730\u4f4d\uff0c\u5176\u5206\u6563\u5f0f\u8a13\u7df4\u5de5\u5177\uff08\u5982 FSDP \u8207 DeepSpeed \u6574\u5408\uff09\u8b93\u5b83\u6210\u70ba\u65b0 LLM \u5c08\u6848\u7684\u9996\u9078\u3002TensorFlow \u5247\u5728\u6df7\u5408\u7cbe\u5ea6\u8a2d\u5b9a\u4e0a\u66f4\u70ba\u7c21\u6f54\uff0c\u53ea\u9700\u4e00\u884c\u7a0b\u5f0f\u78bc\u5373\u53ef\u555f\u7528\uff1bPyTorch \u96d6\u7136\u9700\u8981\u591a\u5beb\u5e7e\u884c\uff0c\u4f46\u63a7\u5236\u7c92\u5ea6\u66f4\u7d30\u3002<\/p>\n<p>\u6df7\u5408\u7cbe\u5ea6\u8a13\u7df4\u662f\u53d6\u5f97\u986f\u8457\u52a0\u901f\u7684\u95dc\u9375\u624b\u6bb5\u3002\u81ea\u52d5\u6df7\u5408\u7cbe\u5ea6\uff08AMP\uff09\u6703\u5728\u5408\u9069\u7684\u4f4d\u7f6e\u4f7f\u7528 FP16\uff0c\u4e26\u904b\u7528 Tensor Core \u5e36\u4f86\u6210\u500d\u6548\u80fd\u63d0\u5347\uff1a<\/p>\n<ul>\n<li>\n<p>\u555f\u7528 AMP \u5f8c\uff0c\u901a\u5e38\u53ef\u4ee5\u7372\u5f97 2\u20134.5 \u500d\u52a0\u901f<\/p>\n<\/li>\n<li>\n<p>\u78ba\u4fdd\u77e9\u9663\u7dad\u5ea6\u70ba 8 \u7684\u500d\u6578\uff0c\u4ee5\u53d6\u5f97\u66f4\u597d\u7684 FP16 \u52a0\u901f\u6548\u679c<\/p>\n<\/li>\n<li>\n<p>\u4f7f\u7528\u68af\u5ea6\u7d2f\u7a4d\u4f86\u5be6\u73fe\u66f4\u5927\u7684\u6709\u6548 batch size<\/p>\n<\/li>\n<li>\n<p>\u4f7f\u7528 PyTorch Profiler \u6216 Nsight Systems \u627e\u51fa\u6548\u80fd\u74f6\u9838<\/p>\n<\/li>\n<li>\n<p>\u5c07 AMP \u8207\u68af\u5ea6\u6aa2\u67e5\u9ede\u7d50\u5408\u4f7f\u7528\uff0c\u53ef\u9032\u4e00\u6b65\u964d\u4f4e\u8a18\u61b6\u9ad4\u5360\u7528<\/p>\n<\/li>\n<\/ul>\n<p>\u59a5\u5584\u61c9\u7528\u9019\u4e9b\u6280\u8853\uff0c\u53ef\u4ee5\u5728\u7bc0\u7701\u6700\u9ad8\u7d04 50% \u986f\u793a\u8a18\u61b6\u9ad4\u7684\u540c\u6642\uff0c\u8b93\u8a13\u7df4\u901f\u5ea6\u518d\u63d0\u5347 30\u2013100%\u3002<\/p>\n<h3>\u5be6\u4f5c\u5206\u6563\u5f0f\u8a13\u7df4\u4e26\u7ba1\u7406\u6563\u71b1\u9650\u5236<\/h3>\n<p>\u55ae\u5361\u8a13\u7df4\u7e3d\u6703\u9047\u5230\u5929\u82b1\u677f\uff0c\u800c\u5206\u6563\u5f0f\u8a13\u7df4\u8b93\u4f60\u6709\u6a5f\u6703\u9032\u4e00\u6b65\u7a81\u7834\u3002DistributedDataParallel\uff08DDP\uff09\u5728\u64f4\u5145 GPU \u6578\u91cf\u6642\u53ef\u5be6\u73fe\u8fd1\u4f3c\u7dda\u6027\u7684\u52a0\u901f\u3002\u6bcf\u5f35 GPU \u90fd\u4fdd\u7559\u4e00\u4efd\u6a21\u578b\u526f\u672c\u4e26\u8655\u7406\u81ea\u5df1\u7684\u8cc7\u6599\u6279\u6b21\uff0c\u68af\u5ea6\u900f\u904e\u4ee5 NCCL \u70ba\u57fa\u790e\u7684 All-Reduce \u901a\u8a0a\u9032\u884c\u5f59\u7e3d\u3002<\/p>\n<p>\u5728\u4e0d\u6539\u8b8a batch size \u7684\u524d\u63d0\u4e0b\uff0c\u4f7f\u7528\u5169\u500b\u7bc0\u9ede\u3001\u516b\u5f35 GPU \u7684 DDP \u8a13\u7df4\uff0c\u76f8\u8f03\u55ae\u5361\u8a13\u7df4\u53ef\u4ee5\u7372\u5f97\u5927\u7d04 13 \u500d\u7684\u52a0\u901f\u3002<\/p>\n<p>\u7576\u6a21\u578b\u9ad4\u7a4d\u8d85\u904e\u55ae\u5361\u986f\u793a\u8a18\u61b6\u9ad4\u6642\uff0c\u4f60\u5c31\u9700\u8981\u66f4\u9032\u968e\u7684\u7b56\u7565\u3002ZeRO \u6703\u5c07\u6700\u4f73\u5316\u5668\u72c0\u614b\u3001\u68af\u5ea6\u8207\u53c3\u6578\u5207\u5206\u4e26\u5206\u6563\u5230\u591a\u5f35 GPU \u4e0a\uff1b\u7ba1\u7dda\u5e73\u884c\u5247\u900f\u904e\u5c07 batch \u5207\u5206\u6210\u591a\u500b\u5fae\u6279\u6b21\u4f86\u5be6\u73fe\u7ba1\u7dda\u5316\u8655\u7406\uff1b\u5f35\u91cf\u5e73\u884c\u5247\u5c07\u5927\u898f\u6a21\u77e9\u9663\u904b\u7b97\u62c6\u5206\u5230\u591a\u5f35 GPU \u4e0a\uff1b\u6df7\u5408\u5e73\u884c\u5247\u7d9c\u5408\u904b\u7528\u4e0a\u8ff0\u65b9\u6cd5\uff0c\u4ee5\u652f\u63f4\u767e\u5104\u3001\u5343\u5104\u53c3\u6578\u7b49\u7d1a\u6a21\u578b\u3002<\/p>\n<p>\u6563\u71b1\u7ba1\u7406\u6c7a\u5b9a\u4e86\u7cfb\u7d71\u80fd\u5426\u6301\u7e8c\u7dad\u6301\u5cf0\u503c\u6548\u80fd\u3002\u50b3\u7d71\u98a8\u51b7\u5728\u9577\u6642\u9593 AI \u8a13\u7df4\u8ca0\u8f09\u4e0b\u5f80\u5f80\u529b\u4e0d\u5f9e\u5fc3\uff0c\u800c\u6c34\u51b7\u5247\u53ef\u4ee5\u6709\u6548\u56e0\u61c9\u9ad8\u71b1\u8a2d\u8a08\u529f\u8017\uff0c\u907f\u514d\u56e0\u6eab\u5ea6\u904e\u9ad8\u89f8\u767c\u964d\u983b\u3002\u5c0d\u65bc\u6301\u7e8c\u904b\u884c\u7684\u5927\u578b\u8a13\u7df4\u4efb\u52d9\u800c\u8a00\uff0c\u6548\u80fd\u6ce2\u52d5\u6703\u76f4\u63a5\u5f71\u97ff\u7d50\u679c\u7684\u53ef\u9760\u6027\u3002\u50cf 8\u00d7H100 \u9019\u6a23\u7684\u9ad8\u5bc6\u5ea6\u591a GPU \u914d\u7f6e\uff0c\u66f4\u9700\u8981\u5747\u8861\u3001\u7a69\u5b9a\u7684\u6563\u71b1\u65b9\u6848\u3002\u6c34\u51b7\u53ef\u4ee5\u70ba\u6bcf\u5f35 GPU \u63d0\u4f9b\u66f4\u4e00\u81f4\u7684\u6eab\u5ea6\u8868\u73fe\u3002\u5b9a\u671f\u66f4\u65b0\u9a45\u52d5\u3001\u78ba\u4fdd\u826f\u597d\u6563\u71b1\u689d\u4ef6\u3001\u59a5\u5584\u898f\u5283\u8a13\u7df4\u4f5c\u696d\u6392\u7a0b\uff0c\u90fd\u662f\u7dad\u6301\u7cfb\u7d71\u9577\u671f\u7a69\u5b9a\u9ad8\u6548\u904b\u884c\u7684\u95dc\u9375\u3002<\/p>\n<h2>\u6210\u672c\u8207\u90e8\u7f72\uff1a\u5728\u7f8e\u570b\u9078\u64c7\u96f2\u7aef\u6216\u5728\u5730\u65b9\u6848<\/h2>\n<p>\u90e8\u7f72\u65b9\u5f0f\u6703\u91cd\u5851\u4f60\u7684\u6574\u9ad4\u9810\u7b97\u8207\u71df\u904b\u7b56\u7565\u3002\u96f2\u7aef\u670d\u52d9\u5c07\u652f\u51fa\u8f49\u70ba\u71df\u904b\u6210\u672c\uff08Opex\uff09\uff0c\u5728\u5730\u53e2\u96c6\u5247\u9700\u8981\u5927\u91cf\u524d\u671f\u8cc7\u672c\u6295\u5165\uff08Capex\uff09\u3002\u5408\u9069\u7684\u65b9\u6848\u53d6\u6c7a\u65bc\u4f60\u7684\u5de5\u4f5c\u8ca0\u8f09\u6a21\u5f0f\u3001\u6a21\u578b\u898f\u6a21\u4ee5\u53ca\u6210\u9577\u9810\u671f\uff0c\u4e26\u4e0d\u5b58\u5728\u5c0d\u6240\u6709\u7d44\u7e54\u90fd\u9069\u7528\u7684\u55ae\u4e00\u7b54\u6848\u3002<\/p>\n<h3>\u96f2\u7aef GPU \u57f7\u884c\u500b\u9ad4\u8207\u5728\u5730\u53e2\u96c6\u6bd4\u8f03<\/h3>\n<p>\u6210\u672c\u56de\u672c\u9031\u671f\u6b63\u5feb\u901f\u7e2e\u77ed\u3002\u5c0d\u6301\u7e8c\u63a8\u7406\u985e\u5de5\u4f5c\u8ca0\u8f09\u800c\u8a00\uff0c\u76f8\u8f03\u8d85\u5927\u898f\u6a21\u96f2\u7aef\u696d\u8005\uff0c\u5728\u5730\u81ea\u5efa\u65b9\u6848\u7684\u6210\u672c\u6253\u5e73\u6642\u9593\u5df2\u7e2e\u77ed\u81f3\u7d04 6 \u500b\u6708\uff0c\u800c\u5148\u524d\u4e00\u4ee3\u901a\u5e38\u9700\u8981 12\u201318 \u500b\u6708\u3002\u9019\u7a2e\u8b8a\u5316\u6703\u76f4\u63a5\u5f71\u97ff\u4f60\u7684\u898f\u756b\u9031\u671f\uff1a\u77ed\u671f\u5c08\u6848\u66f4\u504f\u5411\u96f2\u7aef\u90e8\u7f72\uff0c\u800c\u9577\u671f\u7a69\u5b9a\u8ca0\u8f09\u5247\u66f4\u6709\u7406\u7531\u8003\u616e\u5728\u5730\u53e2\u96c6\u3002<\/p>\n<p>\u7522\u696d\u8861\u91cf\u6210\u529f\u7684\u6a19\u6e96\u4e5f\u767c\u751f\u4e86\u8b8a\u5316\u3002\u95dc\u9375\u6307\u6a19\u5df2\u5f9e\u55ae\u7d14\u7684 FLOPS \u6f14\u8b8a\u70ba\u300c\u55ae\u4f4d\u6210\u672c\u4e0b\u7684 tokens \u6bcf\u79d2\u300d\u3002\u4f60\u5fc5\u9808\u6bd4\u8f03\u5728\u5728\u5730\u53e2\u96c6\u4e0a\u7522\u751f\u4e00\u767e\u842c\u500b token \u7684\u6524\u63d0\u6210\u672c\uff0c\u8207\u96f2\u7aef API \u96f6\u552e\u50f9\u683c\u4e4b\u9593\u7684\u5dee\u7570\uff0c\u9019\u6703\u8feb\u4f7f\u4f60\u5f9e\u300c\u6548\u7387\u300d\u800c\u975e\u300c\u6975\u9650\u6548\u80fd\u300d\u7684\u89d2\u5ea6\u4f86\u8a55\u4f30\u65b9\u6848\u512a\u52a3\u3002<\/p>\n<p>\u64f4\u5145\u6027\u8207\u5ef6\u9072\u4e5f\u5b58\u5728\u53d6\u6368\u3002\u96f2\u7aef\u57f7\u884c\u500b\u9ad4\u5177\u5099\u5f48\u6027\u64f4\u5145\u8207\u81ea\u52d5\u8abf\u6574\u80fd\u529b\uff0c\u53ef\u4ee5\u4f9d\u64da\u5373\u6642\u9700\u6c42\u5feb\u901f\u8abf\u6574\u8cc7\u6e90\uff0c\u4f46\u914d\u984d\u9650\u5236\u8207\u5340\u57df\u8cc7\u6e90\u7dca\u5f35\u53ef\u80fd\u6210\u70ba\u96b1\u6027\u969c\u7919\uff0c\u4e5f\u5bb9\u6613\u51fa\u73fe\u610f\u5916\u8cbb\u7528\u3002\u5728\u5730\u53e2\u96c6\u5247\u9700\u8981\u5728\u524d\u671f\u5b8c\u6210\u5468\u5168\u898f\u756b\u8207\u786c\u9ad4\u63a1\u8cfc\uff0c\u64f4\u5145\u9031\u671f\u8f03\u9577\u3001\u6295\u5165\u4e5f\u8f03\u9ad8\u3002<\/p>\n<p>\u5728\u5ef6\u9072\u65b9\u9762\uff0c\u5728\u5730\u90e8\u7f72\u901a\u5e38\u4f54\u512a\u52e2\u3002\u4f3a\u670d\u5668\u8207\u8cc7\u6599\u4f86\u6e90\u7684\u7269\u7406\u8ddd\u96e2\u66f4\u8fd1\uff0c\u53ef\u6700\u5927\u7a0b\u5ea6\u964d\u4f4e\u7db2\u8def\u5ef6\u9072\uff1b\u5ba2\u88fd\u5316\u7db2\u8def\u67b6\u69cb\u9084\u80fd\u5728\u78ba\u4fdd\u9ad8\u541e\u5410\u91cf\u7684\u540c\u6642\u7dad\u6301\u6975\u4f4e\u5ef6\u9072\u3002\u96f2\u7aef\u6548\u80fd\u5247\u53d6\u6c7a\u65bc\u7db2\u8def\u983b\u5bec\u8207\u8cc7\u6599\u4e2d\u5fc3\u8ca0\u8f09\uff0c\u591a\u6578\u96f2\u7aef\u4f9b\u61c9\u5546\u53ef\u4ee5\u63d0\u4f9b\u63a5\u8fd1\u5728\u5730\u7684\u6548\u80fd\uff0c\u4f46\u5be6\u969b\u9ad4\u9a57\u4ecd\u6703\u53d7\u5230\u6a5f\u623f\u5730\u7406\u4f4d\u7f6e\u5f71\u97ff\u3002<\/p>\n<div fullwidth=\"\" class=\"qc-default-table-wrapper \">\n<table style=\"min-width: 75px;\">\n<colgroup>\n<col style=\"min-width: 25px;\">\n<col style=\"min-width: 25px;\">\n<col style=\"min-width: 25px;\"><\/colgroup>\n<tbody>\n<tr>\n<th colspan=\"1\" rowspan=\"1\">\n<p>\u8003\u91cf\u9762\u5411<\/p>\n<\/th>\n<th colspan=\"1\" rowspan=\"1\">\n<p>\u96f2\u7aef GPU \u57f7\u884c\u500b\u9ad4<\/p>\n<\/th>\n<th colspan=\"1\" rowspan=\"1\">\n<p>\u5728\u5730\u53e2\u96c6<\/p>\n<\/th>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u53ef\u64f4\u5145\u6027<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u501f\u52a9\u81ea\u52d5\u64f4\u5145\u8f15\u9b06\u5ef6\u5c55\uff1b\u4f46\u53ef\u80fd\u53d7\u914d\u984d\u9650\u5236<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u9700\u898f\u756b\u3001\u63a1\u8cfc\u8207\u5b89\u88dd\uff1b\u53d7\u9650\u65bc\u73fe\u6709 GPU \u6578\u91cf<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u5ef6\u9072<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u63a5\u8fd1\u5728\u5730\u901f\u5ea6\uff0c\u4f46\u6703\u53d7\u8cc7\u6599\u4e2d\u5fc3\u4f4d\u7f6e\u5f71\u97ff<\/p>\n<\/td>\n<td colspan=\"1\" rowspan=\"1\">\n<p>\u53ef\u900f\u904e\u5ba2\u88fd\u7db2\u8def\u8a2d\u5b9a\u5be6\u73fe\u6975\u4f4e\u5ef6\u9072<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<h3>\u9078\u64c7\u7f8e\u570b\u5728\u5730\u670d\u52d9\u5546\u8207\u6cd5\u898f\u9075\u5faa\u8003\u91cf<\/h3>\n<p>\u4f4d\u65bc\u7f8e\u570b\u7684\u8cc7\u6599\u4e2d\u5fc3\u5728 AI \u5de5\u4f5c\u8ca0\u8f09\u65b9\u9762\u5177\u6709\u5176\u7368\u7279\u512a\u52e2\uff1a\u5c0d\u672c\u571f\u696d\u52d9\u800c\u8a00\uff0c\u4f4e\u5ef6\u9072\u5b58\u53d6\u9ad4\u9a57\u66f4\u4f73\uff1b\u5b8c\u5584\u7684\u57fa\u790e\u8a2d\u65bd\u53ef\u4ee5\u78ba\u4fdd\u9ad8\u53ef\u7528\u6027\uff1b\u9075\u5faa\u5728\u5730\u8cc7\u6599\u6cd5\u898f\u4e5f\u80fd\u7c21\u5316\u4f60\u7684\u5408\u898f\u58d3\u529b\u3002AWS\u3001GCP \u548c Azure \u5728\u7f8e\u570b\u90fd\u90e8\u7f72\u4e86\u5927\u91cf\u5340\u57df\uff0c\u6bcf\u5bb6\u4f9b\u61c9\u5546\u63d0\u4f9b\u7684 GPU \u57f7\u884c\u500b\u9ad4\u985e\u578b\u8207\u5b9a\u50f9\u7b56\u7565\u4e5f\u4e0d\u76e1\u76f8\u540c\uff0c\u4f60\u5fc5\u9808\u9032\u884c\u4ed4\u7d30\u6bd4\u8f03\u3002<\/p>\n<p>\u5728\u654f\u611f\u7522\u696d\u4e2d\uff0c\u6cd5\u898f\u9075\u5faa\u5c24\u70ba\u91cd\u8981\u3002\u91ab\u7642\u8cc7\u6599\u5fc5\u9808\u7b26\u5408 HIPAA\uff0c\u91d1\u878d\u8cc7\u6599\u5247\u9700\u9075\u5b88 FINRA \u7b49\u76e3\u7ba1\u8981\u6c42\u3002\u7f8e\u570b\u8cc7\u6599\u4e2d\u5fc3\u5c0d\u9019\u4e9b\u898f\u7bc4\u8f03\u70ba\u719f\u6089\uff0c\u4e26\u5728\u57fa\u790e\u8a2d\u65bd\u8a2d\u8a08\u4e2d\u9810\u5148\u7d0d\u5165\u9019\u4e9b\u8981\u6c42\u3002\u4f60\u7684 GPU \u52a0\u901f\u89e3\u6c7a\u65b9\u6848\u5fc5\u9808\u5f9e\u4e00\u958b\u59cb\u5c31\u5c07\u9019\u4e9b\u9650\u5236\u7d0d\u5165\u8003\u91cf\u3002<\/p>\n<p>\u8cc7\u6599\u5728\u5730\u5316\u8981\u6c42\u4e5f\u53ef\u80fd\u5f71\u97ff\u4f60\u7684\u9078\u64c7\u3002\u6709\u4e9b\u6a5f\u69cb\u5fc5\u9808\u5c07\u8cc7\u6599\u56b4\u683c\u63a7\u7ba1\u5728\u7f8e\u570b\u5883\u5167\uff0c\u96f2\u7aef\u4f9b\u61c9\u5546\u901a\u5e38\u63d0\u4f9b\u5340\u57df\u9650\u5b9a\u7684\u5132\u5b58\u8207\u904b\u7b97\u670d\u52d9\uff0c\u800c\u5728\u5730\u53e2\u96c6\u5247\u5929\u751f\u6eff\u8db3\u9019\u9805\u9700\u6c42\u3002\u4f60\u7684\u5408\u898f\u5718\u968a\u61c9\u5c0d\u5169\u7a2e\u65b9\u6848\u9032\u884c\u8a73\u7d30\u8a55\u4f30\u3002<\/p>\n<p>\u6700\u7d42\uff0c\u4f60\u9700\u8981\u5728\u6210\u672c\u3001\u63a7\u5236\u529b\u8207\u6cd5\u898f\u9075\u5faa\u4e4b\u9593\u505a\u51fa\u5e73\u8861\uff1a\u96f2\u7aef\u5177\u5099\u9ad8\u5f48\u6027\u8207\u8f03\u4f4e\u524d\u671f\u6210\u672c\uff0c\u800c\u5728\u5730\u53e2\u96c6\u5247\u63d0\u4f9b\u66f4\u7a69\u5b9a\u7684\u6548\u80fd\u8207\u8cc7\u6599\u4e3b\u6b0a\u3002\u6700\u5408\u9069\u7684\u65b9\u6848\uff0c\u53d6\u6c7a\u65bc\u4f60\u7684\u5de5\u4f5c\u8ca0\u8f09\u6a21\u5f0f\u8207\u76e3\u7ba1\u8981\u6c42\u3002<\/p>\n<div dividerstyle=\"solid\" size=\"large\" color=\"#D1D1D1\" class=\"qc-divider-wrapper\">\n<div class=\"qc-divider\" style=\"border-top-style: solid; width: 100%; border-top-color: rgb(209, 209, 209);\"><\/div>\n<\/div>\n<p>\u4f60\u7684 GPU \u52a0\u901f\u89e3\u6c7a\u65b9\u6848\uff0c\u662f\u5f37\u5927\u7684 NVIDIA \u786c\u9ad4\u3001\u5747\u8861\u7684\u4f3a\u670d\u5668\u67b6\u69cb\u4ee5\u53ca\u9ad8\u5ea6\u6700\u4f73\u5316\u7684\u8edf\u9ad4\u5806\u758a\u5171\u540c\u4f5c\u7528\u7684\u7d50\u679c\u3002\u7406\u60f3\u7684 GPU \u9078\u64c7\u53d6\u6c7a\u65bc\u5177\u9ad4\u5de5\u4f5c\u8ca0\u8f09\u3002<\/p>\n<div fullwidth=\"\" class=\"qc-default-table-wrapper \">\n<table style=\"min-width: 50px;\">\n<colgroup>\n<col style=\"min-width: 25px;\">\n<col style=\"min-width: 25px;\"><\/colgroup>\n<tbody>\n<tr>\n<th colspan=\"1\" rowspan=\"1\">\n<p>\u5de5\u4f5c\u8ca0\u8f09\u985e\u578b<\/p>\n<\/th>\n<th colspan=\"1\" rowspan=\"1\">\n<p>\u63a8\u85a6 GPU<\/p>\n<\/th>\n<\/tr>\n<tr>\n<td colspan=\"1\" 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GPU\u3002\u6240\u9700\u6578\u91cf\u4e3b\u8981\u53d6\u6c7a\u65bc\u6a21\u578b\u5927\u5c0f\u8207\u76ee\u6a19\u8a13\u7df4\u6642\u9593\u3002\u5efa\u8b70\u5f9e\u8f03\u5c0f\u898f\u6a21\u958b\u59cb\uff0c\u4e26\u4f9d\u9700\u6c42\u9010\u6b65\u64f4\u5145\u3002<\/p>\n<h3>\u79df\u7528 GPU \u4f3a\u670d\u5668\u8207\u8cfc\u8cb7 GPU \u4f3a\u670d\u5668\u6709\u4ec0\u9ebc\u5dee\u5225\uff1f<\/h3>\n<p>\u79df\u7528\u53ef\u4ee5\u5c07\u6210\u672c\u8f49\u70ba\u71df\u904b\u652f\u51fa\uff0c\u7121\u9700\u524d\u671f\u5927\u984d\u6295\u5165\uff1b\u8cfc\u8cb7\u5247\u9700\u8981\u8f03\u9ad8\u8cc7\u672c\u652f\u51fa\uff0c\u4f46\u5c0d\u65bc\u9577\u671f\u3001\u6301\u7e8c\u904b\u884c\u7684\u5de5\u4f5c\u8ca0\u8f09\u4f86\u8aaa\uff0c\u5f80\u5f80\u80fd\u5728\u9577\u671f\u53d6\u5f97\u6210\u672c\u512a\u52e2\u3002\u54ea\u7a2e\u65b9\u5f0f\u66f4\u5212\u7b97\uff0c\u95dc\u9375\u5728\u65bc\u4f3a\u670d\u5668\u7684\u5be6\u969b\u4f7f\u7528\u7387\uff1a\u5982\u679c\u9700\u8981 7\u00d724 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TensorFlow\u3002\u6700\u7d42\u9078\u64c7\u4ecd\u61c9\u8003\u91cf\u5718\u968a\u65e2\u6709\u7d93\u9a57\u3002<\/p>\n<h3>\u5728\u9577\u6642\u9593\u8a13\u7df4\u4e2d\uff0c\u5982\u4f55\u907f\u514d GPU \u904e\u71b1\uff1f<\/h3>\n<p>\u6c34\u51b7\u65b9\u6848\u53ef\u4ee5\u66f4\u597d\u5730\u56e0\u61c9\u6301\u7e8c\u9ad8\u8ca0\u8f09\uff0c\u4e26\u6709\u6548\u907f\u514d\u56e0\u6eab\u5ea6\u904e\u9ad8\u89f8\u767c\u964d\u983b\uff1b\u50b3\u7d71\u98a8\u51b7\u5728\u9577\u6642\u9593 AI 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href=\"https:\/\/www.varidata.com\/zh-tw\/knowledge-tc\/gpu-acceleration-for-ai-using-us-high-configuration-servers\/\">Read More&#8230;<\/a><\/p>\n","protected":false},"author":11,"featured_media":35601,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[268],"tags":[],"class_list":["post-35607","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-knowledge-tc"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.2 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>\u5229\u7528\u7f8e\u570b\u9ad8\u914d\u7f6e\u4f3a\u670d\u5668\u7684 GPU \u52a0\u901f\u89e3\u6c7a\u65b9\u6848\u9032\u884c AI \u6a21\u578b\u8a13\u7df4<\/title>\n<meta name=\"description\" content=\"\u4e86\u89e3\u5982\u4f55\u900f\u904e\u7f8e\u570b\u9ad8\u914d\u7f6e\u4f3a\u670d\u5668\u7684 GPU \u52a0\u901f\u89e3\u6c7a\u65b9\u6848\uff0c\u5c07 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