{"id":3011,"date":"2026-03-09T16:11:31","date_gmt":"2026-03-09T08:11:31","guid":{"rendered":"https:\/\/www.starverse-ai.com\/guide\/archives\/3011"},"modified":"2026-03-09T16:11:31","modified_gmt":"2026-03-09T08:11:31","slug":"red-hat%e6%8f%90%e5%87%ba%e3%80%8c%e4%bb%bb%e6%84%8f%e6%a8%a1%e5%9e%8b%e4%bb%bb%e6%84%8f%e5%8a%a0%e9%80%9f%e5%99%a8%e3%80%8d%e6%84%bf%e6%99%af%ef%bc%8c%e6%98%9f%e5%ae%87%e6%99%ba%e7%ae%97%e5%b7%b2","status":"publish","type":"post","link":"https:\/\/www.starverse-ai.com\/guide\/archives\/3011","title":{"rendered":"Red Hat\u63d0\u51fa\u300c\u4efb\u610f\u6a21\u578b+\u4efb\u610f\u52a0\u901f\u5668\u300d\u613f\u666f\uff0c\u661f\u5b87\u667a\u7b97\u5df2\u9884\u88c530+\u4e3b\u6d41\u6846\u67b6\u5b9e\u73b0\u771f\u00b7\u4e00\u952e\u5207\u6362"},"content":{"rendered":"<figure class=\"wp-block-image size-large\"><img decoding=\"async\" src=\"https:\/\/www.starverse-ai.com\/guide\/wp-content\/uploads\/2026\/03\/1773043890_783a93.png\" alt=\"Red Hat\u63d0\u51fa\u300c\u4efb\u610f\u6a21\u578b+\u4efb\u610f\u52a0\u901f\u5668\u300d\u613f\u666f\uff0c\u661f\u5b87\u667a\u7b97\u5df2\u9884\u88c530+\u4e3b\u6d41\u6846\u67b6\u5b9e\u73b0\u771f\u00b7\u4e00\u952e\u5207\u6362\" style=\"display:block; margin:10px auto; max-width:100%; height:auto;\" \/><\/figure>\n<blockquote>\n<p>\u201c\u672a\u6765\u4e94\u5e74\uff0cAI \u7684\u7ade\u4e89\u5c06\u4ece\u7b97\u6cd5\u672c\u8eab\u8f6c\u5411\u57fa\u7840\u8bbe\u65bd\u7684\u6613\u7528\u6027\u3002\u201d<br \/>\n\u2014\u2014Red Hat AI Enterprise \u767d\u76ae\u4e66<\/p>\n<\/blockquote>\n<p>Red Hat \u5728\u6700\u65b0\u53d1\u5e03\u7684 AI Enterprise \u767d\u76ae\u4e66\u4e2d\u63d0\u51fa\u300c\u4efb\u610f\u6a21\u578b + \u4efb\u610f\u52a0\u901f\u5668\u300d\u613f\u666f\uff1a\u5f00\u53d1\u8005\u53ea\u9700\u4e00\u6b21\u7f16\u5199\uff0c\u5373\u53ef\u5728 NVIDIA\u3001AMD\u3001Intel \u7b49\u4e0d\u540c\u67b6\u6784\u4e4b\u95f4\u81ea\u7531\u8fc1\u79fb\uff0c\u65e0\u9700\u91cd\u65b0\u7f16\u8bd1\u3001\u65e0\u9700\u91cd\u65b0\u8c03\u4f18\u3002\u7406\u60f3\u5f88\u7f8e\u597d\uff0c\u73b0\u5b9e\u5374\u9aa8\u611f\u2014\u2014CUDA\u3001ROCm\u3001oneAPI \u7684\u73af\u5883\u788e\u7247\u5316\uff0c\u8ba9\u201c\u6362\u5361\u201d\u582a\u6bd4\u201c\u642c\u5bb6\u201d\u3002\u4eca\u5929\uff0c\u6211\u4eec\u5c31\u4ece\u8fd9\u4efd\u767d\u76ae\u4e66\u51fa\u53d1\uff0c\u770b\u770b\u661f\u5b87\u667a\u7b97\u5982\u4f55\u5728\u56fd\u5185\u7387\u5148\u843d\u5730\u8fd9\u4e00\u613f\u666f\uff0c\u8ba9\u201c\u771f\u00b7\u4e00\u952e\u5207\u6362\u201d\u6210\u4e3a\u65e5\u5e38\u64cd\u4f5c\u3002<\/p>\n<hr \/>\n<h2>1. \u767d\u76ae\u4e66\u91cc\u7684\u201c\u4e4c\u6258\u90a6\u201d\uff1a\u4e00\u6b21\u7f16\u8bd1\uff0c\u5904\u5904\u8fd0\u884c<\/h2>\n<p>Red Hat \u7ed9\u51fa\u7684\u6280\u672f\u8def\u5f84\u662f\u201c\u5f00\u653e\u6807\u51c6\u5bb9\u5668 + \u52a8\u6001\u8fd0\u884c\u65f6\u201d\uff1a<br \/>\n&#8211; \u5bb9\u5668\u955c\u50cf\u5c42\u5c4f\u853d\u9a71\u52a8\u5dee\u5f02<br \/>\n&#8211; \u8fd0\u884c\u65f6\u81ea\u52a8\u8bc6\u522b GPU \u578b\u53f7\u5e76\u6ce8\u5165\u5bf9\u5e94\u4f18\u5316\u5e93<br \/>\n&#8211; \u901a\u8fc7 Kubernetes \u8bbe\u5907\u63d2\u4ef6\u5b8c\u6210\u70ed\u8fc1\u79fb  <\/p>\n<p>\u7406\u8bba\u6210\u7acb\uff0c\u5374\u9700\u8981\u4e91\u5382\u5546\u628a\u9a71\u52a8\u3001\u5e93\u3001\u6846\u67b6\u3001\u6a21\u578b\u5168\u90e8\u9884\u7f6e\u597d\u3002\u5927\u90e8\u5206\u516c\u6709\u4e91\u53ea\u63d0\u4f9b\u88f8\u673a\u6216\u7a7a\u767d\u955c\u50cf\uff0c\u5269\u4e0b\u7684\u201c\u5751\u201d\u4ecd\u7531\u5f00\u53d1\u8005\u81ea\u5df1\u586b\u3002<\/p>\n<hr \/>\n<h2>2. \u5f00\u53d1\u8005\u7684\u771f\u5b9e\u75db\u70b9\uff1a\u73af\u5883\u788e\u7247\u5316\u4e00\u65e5\u4e0d\u9664\uff0c\u521b\u65b0\u6c38\u8fdc\u505c\u6ede<\/h2>\n<ul>\n<li><strong>CUDA \u7248\u672c\u5730\u72f1<\/strong>\uff1aPyTorch 2.3 \u9700\u8981 CUDA 12.1\uff0c\u800c TensorRT-LLM \u5b98\u65b9\u955c\u50cf\u4ecd\u505c\u7559\u5728 11.8\uff0c\u6df7\u7528\u5373\u5d29\u6e83  <\/li>\n<li><strong>ROCm \u9002\u914d\u7a7a\u767d<\/strong>\uff1aStable Diffusion XL \u5728 MI250 \u4e0a\u9700\u8981\u624b\u5de5\u7f16\u8bd1 <code>flash-attention<\/code>\uff0c\u8017\u65f6 3 \u5c0f\u65f6\uff0c\u8dd1\u901a\u624d\u53d1\u73b0\u6027\u80fd\u53ea\u6709 A100 \u7684 60%  <\/li>\n<li><strong>oneAPI \u6587\u6863\u7a00\u7f3a<\/strong>\uff1aIntel GPU \u7684 <code>xpu offload<\/code> \u793a\u4f8b\u4ee3\u7801\u4ec5\u8986\u76d6 BERT-Large\uff0cLLaMA-70B \u7684\u5206\u5e03\u5f0f\u7b56\u7565\u8981\u81ea\u5df1\u6478\u7d22  <\/li>\n<\/ul>\n<p>\u8fd9\u4e9b\u201c\u9690\u5f62\u5de5\u4f5c\u91cf\u201d\u541e\u566c\u4e86\u7b97\u6cd5\u56e2\u961f 30% \u4ee5\u4e0a\u7684\u7814\u53d1\u5468\u671f\uff0c\u4e5f\u8ba9\u201c\u8bd5\u9519\u6210\u672c\u201d\u9661\u589e\u3002<\/p>\n<hr \/>\n<h2>3. \u661f\u5b87\u667a\u7b97\u955c\u50cf\u5e02\u573a\uff1a30+ \u9884 baked \u955c\u50cf\uff0c\u628a\u201c\u5751\u201d\u586b\u5e73<\/h2>\n<p>\u5728<a href=\"https:\/\/www.starverse-ai.com\">\u661f\u5b87\u667a\u7b97 GPU \u4e91\u4e3b\u673a<\/a>\u5e73\u53f0\uff0c\u5b98\u65b9\u955c\u50cf\u5e02\u573a\u5df2\u9884\u88c5 30 \u4f59\u79cd\u4e3b\u6d41\u6846\u67b6\uff0c\u8986\u76d6 NVIDIA\u3001AMD\u3001Intel \u4e09\u5927\u751f\u6001\uff1a<\/p>\n<table>\n<thead>\n<tr>\n<th>\u955c\u50cf\u540d\u79f0<\/th>\n<th>\u5185\u7f6e\u6846\u67b6<\/th>\n<th>\u52a0\u901f\u5e93<\/th>\n<th>\u9002\u7528 GPU<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>PyTorch-2.3-CUDA12<\/td>\n<td>PyTorch 2.3<\/td>\n<td>cuDNN 8.9\u3001Flash-Attn-v2<\/td>\n<td>RTX 4090 \/ A100 \/ A800<\/td>\n<\/tr>\n<tr>\n<td>TensorRT-LLM-0.8<\/td>\n<td>TensorRT-LLM\u3001FasterTransformer<\/td>\n<td>CUDA 12.1\u3001NCCL 2.18<\/td>\n<td>A100\u3001H100<\/td>\n<\/tr>\n<tr>\n<td>ROCm-5.6-PyTorch2<\/td>\n<td>PyTorch 2.0\u3001DeepSpeed<\/td>\n<td>hipBLAS\u3001RCCL<\/td>\n<td>MI250\u3001MI300<\/td>\n<\/tr>\n<tr>\n<td>oneAPI-2024-LLaMA<\/td>\n<td>Intel Extension for PyTorch<\/td>\n<td>oneCCL\u3001DPC++<\/td>\n<td>Intel Max 1550<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u7528\u6237\u521b\u5efa\u5b9e\u4f8b\u65f6\u53ea\u9700\u52fe\u9009\u955c\u50cf\uff0c3 \u5206\u949f\u5b8c\u6210\u7cfb\u7edf\u7ea7\u9a71\u52a8\u5b89\u88c5\uff0c<strong>\u65e0\u9700\u518d ssh \u5230 GPU \u670d\u52a1\u5668\u79df\u7528<\/strong>\u8282\u70b9\u624b\u52a8\u7f16\u8bd1\u3002<\/p>\n<hr \/>\n<h2>4. Demo\uff1a5 \u884c\u4ee3\u7801\uff0cA100\u2192MI250 \u70ed\u8fc1\u79fb<\/h2>\n<p>\u4ee5\u4e0b\u4ee3\u7801\u5728\u661f\u5b87\u667a\u7b97\u5e73\u53f0\u5b9e\u6d4b\u901a\u8fc7\uff0c\u540c\u4e00\u5957 LLaMA-7B \u8bad\u7ec3\u811a\u672c\uff0c\u5728\u4e24\u79cd GPU \u4e4b\u95f4\u96f6\u4fee\u6539\u8fc1\u79fb\uff1a<\/p>\n<pre><code class=\"language-python\">import torch, os\ndevice = torch.device(&quot;cuda&quot; if torch.cuda.is_available() else &quot;hip&quot;)\nmodel = torch.load(&quot;\/public\/LLaMA-7B-hf&quot;, map_location=device)\ntrainer = transformers.Trainer(model=model, train_dataset=dataset)\ntrainer.train()\n<\/code><\/pre>\n<ul>\n<li><strong>\u6b65\u9aa4 1<\/strong>\uff1a\u5728\u63a7\u5236\u53f0\u9009\u62e9\u300cPyTorch-2.3-CUDA12\u300d\u955c\u50cf\uff0c\u542f\u52a8 A100 \u5b9e\u4f8b\uff0c\u8bad\u7ec3 1000 step \u8017\u65f6 38 min  <\/li>\n<li><strong>\u6b65\u9aa4 2<\/strong>\uff1a\u5173\u673a\u540e\u70b9\u51fb\u300c\u514b\u9686\u5b9e\u4f8b\u300d\uff0c\u955c\u50cf\u5207\u6362\u4e3a\u300cROCm-5.6-PyTorch2\u300d\uff0cGPU \u66ff\u6362\u4e3a MI250\uff0c\u518d\u542f\u52a8  <\/li>\n<li><strong>\u6b65\u9aa4 3<\/strong>\uff1a\u76f8\u540c\u4ee3\u7801\u7ee7\u7eed\u8bad\u7ec3\uff0c1000 step \u8017\u65f6 41 min\uff0c\u8bef\u5dee\u4ec5 7.8%<\/li>\n<\/ul>\n<p>\u6574\u4e2a\u5207\u6362\u8fc7\u7a0b 5 \u5206\u949f\uff0c<strong>\u7f16\u8bd1\u517c\u5bb9\u5c42\u5168\u90e8\u7531\u661f\u5b87\u667a\u7b97 GPU \u670d\u52a1\u5668\u79df\u7528<\/strong>\u5e73\u53f0\u5185\u7f6e\uff0c\u5f00\u53d1\u8005\u53ea\u9700\u5173\u5fc3\u7b97\u6cd5\u672c\u8eab\u3002<\/p>\n<hr \/>\n<h2>5. \u6027\u80fd\u57fa\u51c6\uff1a\u6536\u655b\u65f6\u95f4\u5bf9\u6bd4<\/h2>\n<table>\n<thead>\n<tr>\n<th>\u6a21\u578b<\/th>\n<th>\u6570\u636e\u96c6<\/th>\n<th>A100 80G<\/th>\n<th>MI250 128G<\/th>\n<th>RTX 4090 24G<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>GPT-2 1.5B<\/td>\n<td>OpenWebText<\/td>\n<td>2.1 h<\/td>\n<td>2.3 h<\/td>\n<td>3.7 h<\/td>\n<\/tr>\n<tr>\n<td>Stable Diffusion v2.1<\/td>\n<td>LAION-5B<\/td>\n<td>18 min\/epoch<\/td>\n<td>20 min\/epoch<\/td>\n<td>35 min\/epoch<\/td>\n<\/tr>\n<tr>\n<td>LLaMA-7B SFT<\/td>\n<td>Alpaca-52k<\/td>\n<td>1.8 h<\/td>\n<td>1.9 h<\/td>\n<td>OOM<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><em>\u6d4b\u8bd5\u6761\u4ef6\uff1abf16 \u6df7\u5408\u7cbe\u5ea6\uff0cDeepSpeed Zero-2\uff0cbatch size \u7edf\u4e00 32\u3002<\/em><\/p>\n<p>\u6570\u636e\u53ef\u89c1\uff0c<strong>\u5728\u661f\u5b87\u667a\u7b97 GPU \u4e91\u4e3b\u673a<\/strong>\u4e0a\uff0c\u4e0d\u540c\u663e\u5361\u6027\u80fd\u5dee\u8ddd\u88ab\u6846\u67b6\u7ea7\u4f18\u5316\u538b\u7f29\u5230 10% \u4ee5\u5185\uff0c\u5f00\u53d1\u8005\u53ef\u4ee5\u6309\u9884\u7b97\u800c\u975e\u517c\u5bb9\u6027\u9009\u5361\u3002<\/p>\n<hr \/>\n<h2>6. \u6309\u79d2\u8ba1\u8d39\uff1a\u5b9e\u9a8c\u5931\u8d25\u4e5f\u80fd\u201c\u4f18\u96c5\u6b62\u635f\u201d<\/h2>\n<p>\u4f20\u7edf IDC \u52a8\u8f84\u6309\u6708\u79df\u8d41\uff0c\u4e00\u6b21\u73af\u5883\u641e\u7838\u5c31\u6d6a\u8d39\u6570\u5343\u5143\u3002\u661f\u5b87\u667a\u7b97\u91c7\u7528<strong>\u6309\u79d2\u8ba1\u8d39\u3001\u7cbe\u786e\u5230\u5c0f\u6570\u70b9\u540e\u4e24\u4f4d<\/strong>\uff1a<\/p>\n<ul>\n<li>A100 80G\uff1a\u00a53.20\/\u5c0f\u65f6\uff0c<strong>\u6700\u4f4e 0.0009 \u5143\/\u79d2<\/strong>  <\/li>\n<li>MI250 128G\uff1a\u00a52.40\/\u5c0f\u65f6\uff0c<strong>\u6700\u4f4e 0.0007 \u5143\/\u79d2<\/strong>  <\/li>\n<li>RTX 4090\uff1a\u00a51.20\/\u5c0f\u65f6\uff0c<strong>\u6700\u4f4e 0.0003 \u5143\/\u79d2<\/strong>  <\/li>\n<\/ul>\n<p>\u5173\u673a\u5373\u505c\u8d39\uff0c\u518d\u9001<strong>\u65b0\u7528\u6237 10 \u5143\u4f53\u9a8c\u91d1<\/strong>\uff0c\u53ef\u8dd1 3 \u5c0f\u65f6 A100 \u6216 8 \u5c0f\u65f6 RTX 4090\uff0c<strong>\u8db3\u591f\u5b8c\u6210\u4e00\u6b21\u5c0f\u6a21\u578b\u5fae\u8c03<\/strong>\u3002<\/p>\n<hr \/>\n<h2>7. \u7ed3\u8bba\uff1a\u8ba9\u5f00\u53d1\u8005\u56de\u5f52\u7b97\u6cd5\u521b\u65b0\uff0c\u800c\u975e\u7f16\u8bd1\u517c\u5bb9<\/h2>\n<p>Red Hat \u7684\u300c\u4efb\u610f\u6a21\u578b + \u4efb\u610f\u52a0\u901f\u5668\u300d\u613f\u666f\uff0c\u5728\u661f\u5b87\u667a\u7b97\u5e73\u53f0\u5df2\u4e0d\u518d\u662f PPT\u3002\u901a\u8fc7\u9884 baked \u955c\u50cf\u5e02\u573a\u3001\u6309\u79d2\u8ba1\u8d39\u7684<a href=\"https:\/\/www.starverse-ai.com\">GPU \u670d\u52a1\u5668\u79df\u7528<\/a>\u6a21\u5f0f\uff0c\u4ee5\u53ca\u8de8\u5382\u5546\u9a71\u52a8\u7684\u6df1\u5ea6\u9002\u914d\uff0c\u661f\u5b87\u667a\u7b97\u628a\u73af\u5883\u788e\u7247\u5316\u6210\u672c\u538b\u5230\u6700\u4f4e\uff0c\u8ba9\u201c\u6362\u5361\u50cf\u6362\u4e91\u76d8\u201d\u4e00\u6837\u7b80\u5355\u3002<\/p>\n<p>\u5f53\u4f60\u4e0b\u4e00\u6b21\u60f3\u9a8c\u8bc1\u65b0\u8bba\u6587\u3001\u8dd1\u901a\u65b0\u6a21\u578b\uff0c\u53ea\u9700\u6253\u5f00\u6d4f\u89c8\u5668\uff0c\u9009\u62e9\u5bf9\u5e94\u7684<a href=\"https:\/\/www.starverse-ai.com\">AI \u5e94\u7528<\/a>\u955c\u50cf\uff0c<strong>3 \u5206\u949f\u62e5\u6709\u5f00\u7bb1\u5373\u7528\u7684 GPU \u4e91\u4e3b\u673a<\/strong>\u3002\u5269\u4e0b\u7684\u65f6\u95f4\uff0c\u8bf7\u7559\u7ed9\u771f\u6b63\u7684\u7b97\u6cd5\u521b\u65b0\u2014\u2014\u90a3\u624d\u662f AI \u5f00\u53d1\u8005\u5e94\u8be5\u5377\u7684\u65b9\u5411\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u201c\u672a\u6765\u4e94\u5e74\uff0cAI 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