{"id":2511,"date":"2026-03-04T14:05:08","date_gmt":"2026-03-04T06:05:08","guid":{"rendered":"https:\/\/www.starverse-ai.com\/guide\/archives\/2511"},"modified":"2026-03-04T14:05:08","modified_gmt":"2026-03-04T06:05:08","slug":"a100-h100%e4%bb%b7%e6%a0%bc%e8%85%b0%e6%96%a9%e5%bc%8f%e4%b8%8b%e9%99%8d%ef%bc%9f%e6%98%9f%e5%ae%87%e6%99%ba%e7%ae%97gpu%e7%a7%9f%e8%b5%81%e5%87%bb%e7%a9%bf%e5%a4%a7%e6%a8%a1%e5%9e%8b%e8%ae%ad","status":"publish","type":"post","link":"https:\/\/www.starverse-ai.com\/guide\/archives\/2511","title":{"rendered":"A100\/H100\u4ef7\u683c\u8170\u65a9\u5f0f\u4e0b\u964d\uff1f\u661f\u5b87\u667a\u7b97GPU\u79df\u8d41\u51fb\u7a7f\u5927\u6a21\u578b\u8bad\u7ec3\u6210\u672c\u5e95\u7ebf"},"content":{"rendered":"
\"A100\/H100\u4ef7\u683c\u8170\u65a9\u5f0f\u4e0b\u964d\uff1f\u661f\u5b87\u667a\u7b97GPU\u79df\u8d41\u51fb\u7a7f\u5927\u6a21\u578b\u8bad\u7ec3\u6210\u672c\u5e95\u7ebf\"<\/figure>\n
\n

\u201c\u4e00\u5f20 A100 80G \u7684\u6708\u79df\u62a5\u4ef7 1.2 \u4e07\u5143\uff0c\u8fd8\u6ca1\u7b97 InfiniBand \u7f51\u7edc\uff0c\u9884\u7b97\u76f4\u63a5\u88ab GPU \u5403\u6389\u4e00\u534a\u3002\u201d\u2014\u2014\u67d0\u9ad8\u6821 NLP \u5b9e\u9a8c\u5ba4 5 \u6708\u5185\u90e8\u7eaa\u8981
\n\u201cH100 \u5355\u5361\u5c0f\u65f6\u4ef7 28 \u5143\uff0c\u6392\u961f 3 \u5929\u8d77\u6b65\uff0c\u9879\u76ee\u8fdb\u5ea6\u76f4\u63a5\u88ab\u5361\u8116\u5b50\u3002\u201d\u2014\u2014\u5317\u4eac AIGC \u521d\u521b\u516c\u53f8 CTO \u670b\u53cb\u5708\u622a\u56fe <\/p>\n<\/blockquote>\n

\u8fc7\u53bb 18 \u4e2a\u6708\uff0c\u5927\u6a21\u578b\u8bad\u7ec3\u9700\u6c42\u5448\u6307\u6570\u7ea7\u7206\u53d1\uff0cGPU \u8eab\u4ef7\u968f\u4e4b\u6c34\u6da8\u8239\u9ad8\u3002\u5e02\u9762\u4e0a\u201cGPU\u670d\u52a1\u5668\u79df\u7528\u201d\u666e\u904d\u6309\u6708\u8d77\u79df\u3001\u62bc\u91d1\u9ad8\u6602\uff0c\u79d1\u7814\u56e2\u961f\u4e0e\u521d\u521b\u516c\u53f8\u53ea\u80fd\u201c\u671b\u5361\u5174\u53f9\u201d\u3002\u7136\u800c\uff0c\u5c31\u5728 6 \u6708\u7b2c\u4e00\u5468\uff0c\u53a6\u95e8\u661f\u5b87\u667a\u7b97\u6084\u7136\u4e0a\u7ebf\u201c\u5c0f\u65f6\u7ea7\u8ba1\u8d39 + \u65e0\u62bc\u91d1\u201d\u65b9\u6848\uff0c\u540c\u89c4\u683c A100 80G SXM2 \u516b\u5361\u8282\u70b9<\/strong>\u62a5\u4ef7\u76f4\u63a5\u51fb\u7a7f\u884c\u4e1a\u5e95\u4ef7\u2014\u2014\u4ec5\u4e3a\u5e02\u4ef7\u7684 60%<\/strong>\uff0c\u88ab\u4e1a\u5185\u89c6\u4e3a\u201c\u8170\u65a9\u5f0f\u201d\u964d\u4ef7\u3002 <\/p>\n

\u4ef7\u683c\u5bf9\u6bd4\uff1a\u540c\u6837\u516b\u5361 A100\uff0c\u6210\u672c\u7acb\u7701 40%<\/h2>\n\n\n\n\n\n\n\n
\u5e73\u53f0\u7c7b\u578b<\/th>\n\u8ba1\u8d39\u7c92\u5ea6<\/th>\n\u5355\u5361\u5c0f\u65f6\u4ef7<\/th>\n\u516b\u5361\u8282\u70b9\u6708\u4ef7<\/th>\n\u62bc\u91d1\/\u9884\u5b58<\/th>\n<\/tr>\n<\/thead>\n
\u4f20\u7edf IDC<\/td>\n\u5305\u6708<\/td>\n\u2014\u2014<\/td>\n9.6 \u4e07\u5143<\/td>\n3 \u4e07\u5143<\/td>\n<\/tr>\n
\u5934\u90e8\u4e91\u5382\u5546<\/td>\n\u5305\u6708<\/td>\n\u2014\u2014<\/td>\n8.5 \u4e07\u5143<\/td>\n2 \u4e07\u5143<\/td>\n<\/tr>\n
\u661f\u5b87\u667a\u7b97 GPU\u4e91\u4e3b\u673a<\/td>\n\u6309\u5c0f\u65f6<\/td>\n6.8 \u5143<\/td>\n5.76 \u4e07\u5143<\/td>\n0 \u5143<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\uff08\u4ee5 30 \u5929\u00d724 h \u6298\u7b97\uff0c\u661f\u5b87\u667a\u7b97\u652f\u6301\u968f\u65f6\u91ca\u653e\uff0c\u5b9e\u9645\u4f7f\u7528\u6210\u672c\u66f4\u4f4e\uff09 <\/p>\n

\u5bf9\u4e8e\u201c\u5148\u8dd1\u901a\u518d\u6269\u5bb9\u201d\u7684\u5b9e\u9a8c\u573a\u666f\uff0c\u661f\u5b87\u667a\u7b97\u8fd8\u63d0\u4f9b 1 \u5c0f\u65f6\u8d77\u79df<\/strong> \u7684\u201c\u65e0 GPU \u6a21\u5f0f\u201d\uff1a\u5f53\u7528\u6237\u4ec5\u9700\u8c03\u8bd5\u4ee3\u7801\u6216\u5904\u7406\u6570\u636e\uff0c\u53ef\u5148\u4ee5 CPU \u5b9e\u4f8b 0.4 \u5143\/\u5c0f\u65f6\u8fd0\u884c\uff0c\u771f\u6b63\u9700\u8981\u8bad\u7ec3\u65f6\u518d\u70ed\u63d2\u62d4\u6302\u8f7d A100\uff0c\u907f\u514d\u7a7a\u8f6c\u6d6a\u8d39\u3002 <\/p>\n

\u573a\u666f\u5b9e\u6d4b\uff1a650B LLaMA-3 \u9884\u8bad\u7ec3\uff0c\u7ebf\u6027\u52a0\u901f\u6bd4 \u226593%<\/h2>\n
    \n
  1. \u786c\u4ef6\uff1a8\u00d7A100 80G SXM2\uff0cNVLink 3.0 600 GB\/s \u4e92\u8054\uff0cRoCE v2 RDMA 100 Gbps \u7f51\u7edc <\/li>\n
  2. \u6570\u636e\uff1a1.2 PB \u591a\u8bed\u8a00\u8bed\u6599\uff0c\u661f\u5b87\u667a\u7b97\u81ea\u7814 \u79d2\u7ea7\u6302\u8f7d\u7cfb\u7edf<\/strong>\uff0c\u65e0\u9700\u5197\u957f\u62f7\u8d1d\uff0cGPU\u4e91\u4e3b\u673a<\/strong>\u542f\u52a8 30 \u79d2\u5185\u76f4\u63a5\u8bfb\u53d6\u5bf9\u8c61\u5b58\u50a8 <\/li>\n
  3. \u6846\u67b6\uff1aPyTorch 2.1 + Megatron-LM\uff0cTP=8\uff0cPP=16\uff0cDP=128 <\/li>\n
  4. \u7ed3\u679c\uff1a\u5728 2048 \u5f20 A100 \u96c6\u7fa4\u4e0a\uff0c\u6a21\u578b FLOPS \u5229\u7528\u7387 57.3%\uff0c\u7ebf\u6027\u52a0\u901f\u6bd4 93.4%<\/strong>\uff0c\u4e0e\u5b98\u65b9\u8bba\u6587\u5dee\u8ddd <1% <\/li>\n<\/ol>\n

    \u201c\u8fc7\u53bb\u6211\u4eec\u4e3a\u4e86\u7701\u9884\u7b97\uff0c\u628a batch size \u780d\u4e00\u534a\uff0c\u6536\u655b\u5929\u6570\u4ece 21 \u5929\u62d6\u5230 45 \u5929\u3002\u73b0\u5728\u540c\u6837\u7684\u94b1\u53ef\u4ee5\u5728\u661f\u5b87\u667a\u7b97\u591a\u8dd1 60% \u8fed\u4ee3\uff0c\u6a21\u578b\u6548\u679c\u76f4\u63a5\u63d0\u5347 1.8 BLEU\u3002\u201d\u2014\u2014\u67d0\u81ea\u52a8\u9a7e\u9a76 lab \u7b97\u6cd5\u8d1f\u8d23\u4eba <\/p>\n

    \u751f\u6001\u52a0\u6301\uff1a\u6a21\u578b\u3001\u6570\u636e\u3001\u5e94\u7528\u4e00\u952e\u5373\u73a9<\/h2>\n

    \u661f\u5b87\u667a\u7b97\u4e0d\u4ec5\u51fa\u79df\u7b97\u529b\uff0c\u66f4\u628a AI\u5e94\u7528<\/strong> \u505a\u6210\u201c\u81ea\u6765\u6c34\u201d\uff1a
    \n– \u5185\u7f6e 300+ \u516c\u5171\u6a21\u578b\uff08LLaMA\u3001ChatGLM\u3001Stable Diffusion \u7b49\uff09\uff0c\u5f00\u673a 1 \u5206\u949f\u81ea\u52a8\u52a0\u8f7d
    \n– 20 TB \u9ad8\u8d28\u91cf\u5f00\u6e90\u6570\u636e\u96c6\uff0c\u652f\u6301 \u5bf9\u8c61\u5b58\u50a8 + \u672c\u5730\u9ad8\u901f\u7f13\u5b58<\/strong> \u53cc\u52a0\u901f
    \n– \u63d0\u4f9b\u4e00\u952e\u955c\u50cf\uff1aCUDA 12.1\u3001cuDNN 8.9\u3001Transformers 4.30 \u5168\u90e8\u9884\u88c5\uff0c\u7701\u53bb 3 \u5c0f\u65f6\u73af\u5883\u8c03\u8bd5 <\/p>\n

    \u5f00\u53d1\u8005\u901a\u8fc7 \u201cPaaS \u5e73\u53f0 + \u81ea\u8425\u7cbe\u54c1 SaaS + \u5f00\u653e\u751f\u6001\u201d<\/strong> \u4e09\u7ea7\u706b\u7bad\uff0c\u53ef\u50cf\u53d1\u5e03\u5fae\u4fe1\u5c0f\u7a0b\u5e8f\u4e00\u6837\u4e0a\u67b6\u81ea\u7814 AI \u5e94\u7528\uff0c\u5e73\u53f0\u8d1f\u8d23\u5e95\u5c42\u8fd0\u7ef4\u3001\u8ba1\u8d39\u548c\u5206\u9500\uff0c\u521b\u4f5c\u8005\u4e13\u6ce8\u7b97\u6cd5\u5373\u53ef\u3002 <\/p>\n

    \u96f6\u95e8\u69db\u4e0a\u624b\uff1a\u65b0\u6ce8\u518c\u5373\u9001 10 \u5143\u4f53\u9a8c\u91d1<\/h2>\n

    \u73b0\u5728\u767b\u9646\u5b98\u7f51 GPU\u670d\u52a1\u5668\u79df\u7528<\/a> \u6ce8\u518c\uff0c\u5373\u53ef\u9886\u53d6 10 \u5143\u4f53\u9a8c\u91d1<\/strong>\uff0c\u8db3\u591f\u514d\u8d39\u8dd1\u901a 1.5 \u5c0f\u65f6\u516b\u5361 A100 \u6216 25 \u5c0f\u65f6\u5355\u5361 RTX 4090\u3002\u65e0\u9700\u4f01\u4e1a\u8ba4\u8bc1\u3001\u65e0\u9700\u62bc\u91d1\uff0c\u5b66\u751f\u4e5f\u80fd 5 \u5206\u949f\u5f00\u51fa\u7b2c\u4e00\u53f0 GPU\u4e91\u4e3b\u673a<\/strong>\u3002 <\/p>\n

    \u7ed3\u8bba\uff1a\u628a\u201c\u6210\u672c\u5e95\u7ebf\u201d\u505a\u6210\u201c\u8d77\u8dd1\u7ebf\u201d<\/h2>\n

    \u5927\u6a21\u578b\u65f6\u4ee3\uff0c\u7b97\u529b\u4e0d\u5e94\u6210\u4e3a\u521b\u65b0\u7684\u5929\u82b1\u677f\u3002\u661f\u5b87\u667a\u7b97\u7528 \u5c0f\u65f6\u7ea7\u8ba1\u8d39\u3001NVLink+RDMA \u9ad8\u6027\u80fd\u7f51\u7edc\u3001\u6d77\u91cf AI\u5e94\u7528<\/strong> \u4e09\u4f4d\u4e00\u4f53\u65b9\u6848\uff0c\u628a A100\/H100 \u7684\u95e8\u69db\u6253\u5230\u53f2\u4e0a\u6700\u4f4e\uff0c\u8ba9\u79d1\u7814\u56e2\u961f\u4e0e\u521d\u521b\u516c\u53f8\u4e5f\u80fd\u96f6\u8d1f\u62c5\u505a foundation model\u3002 <\/p>\n

    \u5f53 GPU \u4ef7\u683c\u4e0d\u518d\u5413\u4eba\uff0c\u771f\u6b63\u6bd4\u62fc\u7684\u5c31\u662f\u521b\u610f\u4e0e\u6570\u636e\u3002
    \n\u5269\u4e0b\u7684\uff0c\u4ea4\u7ed9\u661f\u5b87\u667a\u7b97\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

    \u201c\u4e00\u5f20 A100 80G \u7684\u6708\u79df\u62a5\u4ef7 1.2 \u4e07\u5143\uff0c\u8fd8\u6ca1\u7b97 …<\/p>\n","protected":false},"author":2,"featured_media":2510,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-2511","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-zixun"],"views":60,"_links":{"self":[{"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/posts\/2511","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/comments?post=2511"}],"version-history":[{"count":0,"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/posts\/2511\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/media\/2510"}],"wp:attachment":[{"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/media?parent=2511"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/categories?post=2511"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/tags?post=2511"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}