{"id":34617,"date":"2026-09-13T08:00:55","date_gmt":"2026-09-13T00:00:55","guid":{"rendered":"https:\/\/www.simcentric.com\/?p=34617"},"modified":"2026-09-11T18:12:19","modified_gmt":"2026-09-11T10:12:19","slug":"gpu-utilization-during-gpt-6-training-and-idle-resource-handling","status":"publish","type":"post","link":"https:\/\/www.simcentric.com\/tc\/japan-dedicated-server-tc\/gpu-utilization-during-gpt-6-training-and-idle-resource-handling\/","title":{"rendered":"GPT-6 \u8a13\u7df4\u671f\u9593\u7684 GPU \u5229\u7528\u7387\u8207\u9592\u7f6e\u8cc7\u6e90\u8655\u7406"},"content":{"rendered":"

\u4f60\u7684\u73fe\u4ee3\u5316 GPU \u53e2\u96c6<\/a>\u5728\u7406\u8ad6\u4e0a\u64c1\u6709\u9a5a\u4eba\u7684\u5cf0\u503c\u6548\u80fd\u3002\u4f46\u5c0d\u8a31\u591a\u5718\u968a\u4f86\u8aaa\uff0c\u73fe\u5be6\u537b\u622a\u7136\u4e0d\u540c\u3002\u4f60\u5e38\u5e38\u6703\u770b\u5230\u5e73\u5747 GPU \u5229\u7528\u7387\u9a5f\u964d\u5230 30% \u4ee5\u4e0b\u3002\u627f\u8afe\u8207\u73fe\u5be6\u4e4b\u9593\u7684\u9019\u9053\u9d3b\u6e9d\uff0c\u6703\u8b93\u4f60\u4ed8\u51fa\u9ad8\u6602\u4ee3\u50f9\u3002\u600e\u6a23\u624d\u80fd\u628a GPU \u5229\u7528\u7387\u63a8\u8fd1 90%\uff1f\u90a3\u4e9b\u4f9d\u7136\u9592\u7f6e\u7684 GPU \u53c8\u8a72\u5982\u4f55\u8655\u7406\uff1f\u5728\u9019\u7a2e\u9762\u5411\u5927\u578b\u8a9e\u8a00\u6a21\u578b\u5de5\u4f5c\u7684 AI \u8a13\u7df4<\/a>\u74b0\u5883\u4e2d\uff0c\u4f60\u5fc5\u9808\u63a1\u53d6\u56b4\u8b39\u7684\u65b9\u6cd5\u3002\u898f\u6a21\u3001\u6210\u672c\u8207\u7b97\u529b\u6d6a\u8cbb\u5e36\u4f86\u7684\u7dad\u904b\u75db\u9ede\uff0c\u8981\u6c42\u4f60\u7acb\u523b\u884c\u52d5\u3002\u6bcf\u4e00\u5f35\u9592\u7f6e\u7684 GPU\uff0c\u90fd\u662f\u5c0d\u9810\u7b97\u8207\u9032\u5ea6\u7684\u76f4\u63a5\u6253\u64ca\u3002\u5728\u5982\u6b64\u898f\u6a21\u4e0b\u7ba1\u7406\u4e00\u500b LLM\uff0c\u5e7e\u4e4e\u5bb9\u4e0d\u5f97\u4efb\u4f55\u4f4e\u6548\u3002\u4f60\u9700\u8981\u4e00\u5957\u6e05\u6670\u7684\u8a13\u7df4\u6700\u4f73\u5316\u7b56\u7565\u3002<\/p>\n

\u70ba\u5927\u578b\u8a9e\u8a00\u6a21\u578b\u8a13\u7df4\u5b9a\u7fa9 GPU \u5229\u7528\u7387\u6307\u6a19<\/strong><\/h2>\n

\u70ba\u4ec0\u9ebc\u539f\u59cb\u5229\u7528\u7387\u767e\u5206\u6bd4\u6703\u8aa4\u5c0e\u4f60<\/h3>\n

\u4f60\u6253\u958b nvidia-smi<\/code>\uff0c\u770b\u5230 GPU \u5229\u7528\u7387\u662f 100%\u3002\u4f60\u4ee5\u70ba\u786c\u9ad4\u904b\u4f5c\u5f97\u7121\u6bd4\u5b8c\u7f8e\u3002\u9019\u500b\u5224\u65b7\u5176\u5be6\u4e26\u4e0d\u6210\u7acb\u3002\u4f60\u770b\u5230\u7684\u9019\u500b\u767e\u5206\u6bd4\uff0c\u8861\u91cf\u7684\u53ea\u662f\u4e00\u500b\u975e\u5e38\u72f9\u7a84\u7684\u9762\u5411\u3002\u5b83\u53ea\u8ffd\u8e64\u5728\u53d6\u6a23\u8996\u7a97\u671f\u9593\uff0c\u662f\u5426\u6709\u4efb\u4f55\u6838\u5fc3\u5728\u57f7\u884c\u3002\u5b83\u4e26\u4e0d\u80fd\u8861\u91cf\u4f60\u7684\u6a21\u578b\u662f\u5426\u9ad8\u6548\u5229\u7528\u4e86\u786c\u9ad4\u3002<\/p>\n

\u6839\u64da NVML \u7684\u5b9a\u7fa9\uff0c\u300cutilization\uff08\u5229\u7528\u7387\uff09\u300d\u8868\u793a\u5728\u904e\u53bb\u4e00\u500b\u53d6\u6a23\u9031\u671f\u5167\uff0c\u67d0\u4e9b\u6d3b\u52d5\u767c\u751f\u7684\u6642\u9593\u767e\u5206\u6bd4\u3002GPU utilization \u8868\u793a\u4e00\u500b\u6216\u591a\u500b\u6838\u5fc3\u57f7\u884c\u6642\u6240\u5360\u7684\u6642\u9593\u767e\u5206\u6bd4\u3002Memory utilization \u8868\u793a\u5168\u57df\u8a18\u61b6\u9ad4\u88ab\u8b80\u53d6\u6216\u5beb\u5165\u6642\u6240\u5360\u7684\u6642\u9593\u767e\u5206\u6bd4\u3002<\/p><\/blockquote>\n

\u8003\u616e\u4e00\u500b\u7c21\u55ae\u7684\u6838\u5fc3\uff1a\u5b83\u53ea\u5728\u4e00\u500b Streaming Multiprocessor \u4e0a\u57f7\u884c\u7121\u9650\u8ff4\u5708\u3002\u4f60\u7684 GPU \u53ef\u80fd\u64c1\u6709\u6578\u5341\u500b SM\u3002\u771f\u6b63\u7684\u8a08\u7b97\u4f7f\u7528\u7387\uff0c\u5176\u5be6\u7b49\u65bc 1 \u9664\u4ee5 SM \u7e3d\u6578\u3002\u7136\u800c\uff0cnvidia-smi<\/code> \u4ecd\u53ef\u80fd\u986f\u793a 100% \u5229\u7528\u7387\u3002\u9019\u6a23\u7684\u5dee\u7570\u6703\u88fd\u9020\u4e00\u7a2e\u865b\u5047\u7684\u4fe1\u5fc3\u3002\u4f60\u4ee5\u70ba\u81ea\u5df1\u6602\u8cb4\u7684\u53e2\u96c6\u5df2\u7d93\u5728\u6700\u4f73\u72c0\u614b\u4e0b\u904b\u4f5c\u3002\u5be6\u969b\u4e0a\uff0c\u4f60\u7684\u6a21\u578b\u53ef\u80fd\u53ea\u662f\u8f15\u5fae\u89f8\u53ca\u4e86\u786c\u9ad4\u80fd\u529b\u3002\u539f\u59cb\u5229\u7528\u7387\u6578\u5b57\u63a9\u84cb\u4e86\u771f\u76f8\uff0c\u4e5f\u63a9\u84cb\u4e86\u4f60\u7684 AI \u8a13\u7df4\u6548\u7387\u554f\u984c\u3002<\/p>\n

\u95dc\u9375\u6307\u6a19\uff1aMFU\u3001HFU \u8207\u8a18\u61b6\u9ad4\u983b\u5bec<\/h3>\n

\u4f60\u9700\u8981\u66f4\u597d\u7684\u6e2c\u91cf\u65b9\u5f0f\u3002\u6a21\u578b FLOPs \u5229\u7528\u7387\uff08Model FLOPs Utilization\uff0cMFU\uff09\u80fd\u63d0\u4f9b\u66f4\u6e05\u6670\u7684\u8996\u89d2\u3002MFU \u5c07\u6a21\u578b\u5be6\u969b\u57f7\u884c\u7684\u6d6e\u9ede\u904b\u7b97\uff0c\u8207\u786c\u9ad4\u7406\u8ad6\u5cf0\u503c\u9032\u884c\u5c0d\u6bd4\u3002\u9019\u500b\u6307\u6a19\u80fd\u63ed\u793a\u4f60\u7a76\u7adf\u5229\u7528\u4e86\u591a\u5c11 GPU \u7684\u6578\u5b78\u8a08\u7b97\u80fd\u529b\u3002<\/p>\n

\u786c\u9ad4 FLOPs \u5229\u7528\u7387\uff08Hardware FLOPs Utilization\uff0cHFU\uff09\u5247\u63d0\u4f9b\u4e86\u53e6\u4e00\u500b\u89d2\u5ea6\u3002\u5b83\u6703\u628a\u786c\u9ad4\u57f7\u884c\u7684\u6240\u6709\u64cd\u4f5c\u90fd\u8a08\u7b97\u9032\u53bb\uff0c\u5305\u62ec\u90a3\u4e9b\u4f4e\u6548\u7684\u64cd\u4f5c\u3002\u5f88\u591a\u6642\u5019\uff0c\u771f\u6b63\u7684\u9650\u5236\u4e26\u4e0d\u662f\u8a08\u7b97\uff0c\u800c\u662f\u8a18\u61b6\u9ad4\u983b\u5bec\u3002\u4f60\u7684\u6a21\u578b\u53ef\u80fd\u4e0d\u662f\u5728\u7b49\u7b97\u529b\uff0c\u800c\u662f\u5728\u7b49\u8cc7\u6599\u642c\u79fb\u3002GPU \u4e4b\u9593\u7684\u901a\u8a0a\u958b\u92b7\u540c\u6a23\u6703\u9020\u6210\u505c\u9813\u3002\u9019\u4e9b\u74f6\u9838\uff0c\u6bd4\u55ae\u7d14\u7684 SM \u6d3b\u8e8d\u5ea6\u66f4\u91cd\u8981\u3002\u4f60\u5fc5\u9808\u628a\u9019\u4e9b\u6307\u6a19\u7d50\u5408\u8d77\u4f86\u4e00\u8d77\u8ffd\u8e64\u3002\u5b83\u5011\u6703\u63ed\u793a\u4f60\u7684 LLM \u8a13\u7df4\u7a76\u7adf\u628a\u6548\u80fd\u6d6a\u8cbb\u5728\u4e86\u54ea\u88e1\u3002\u53ea\u6709\u9019\u6a23\uff0c\u4f60\u624d\u80fd\u771f\u6b63\u627e\u5230\u6700\u4f73\u5316\u6a5f\u6703\u3002<\/p>\n

\u8b58\u5225\u5927\u578b\u8a9e\u8a00\u6a21\u578b\u8a13\u7df4\u4e2d\u7684\u74f6\u9838<\/strong><\/h2>\n

\u8a08\u7b97\u3001\u8a18\u61b6\u9ad4\u8207\u901a\u8a0a\u958b\u92b7<\/h3>\n

\u4e00\u6b21\u5927\u578b\u8a9e\u8a00\u6a21\u578b\u8a13\u7df4\uff0c\u901a\u5e38\u6703\u906d\u9047\u4e09\u985e\u4e3b\u8981\u74f6\u9838\u3002\u8a08\u7b97\u53d7\u9650\u7684\u5c64\u6703\u628a\u7b97\u8853\u55ae\u5143\u63a8\u5230\u6975\u9650\u3002\u8a18\u61b6\u9ad4\u53d7\u9650\u7684\u6b0a\u91cd\u66f4\u65b0\u6703\u56e0\u7b49\u5f85\u8cc7\u6599\u642c\u79fb\u800c\u505c\u6eef\u3002\u901a\u8a0a\u53d7\u9650\u7684\u68af\u5ea6\u540c\u6b65\uff0c\u5247\u6703\u8b93\u6574\u500b\u53e2\u96c6\u5728 GPU \u4ea4\u63db\u68af\u5ea6\u6642\u66ab\u505c\u3002\u6bcf\u4e00\u7a2e\u74f6\u9838\uff0c\u90fd\u6703\u5077\u8d70\u539f\u672c\u53ef\u7528\u65bc\u6709\u6548\u5de5\u4f5c\u7684\u6642\u9593\u3002<\/p>\n

\u901a\u8a0a\u958b\u92b7\u5f80\u5f80\u7834\u58de\u529b\u6700\u5927\u3002\u4e00\u500b\u64c1\u6709 1,000 \u5f35 GPU \u7684\u53e2\u96c6\uff0c\u7406\u8ad6\u80fd\u529b\u6975\u5176\u9a5a\u4eba\u3002\u4f46\u5728\u5be6\u52d9\u4e2d\uff0c\u786c\u9ad4\u82b1\u5728\u300c\u4ea4\u8ac7\u300d\u4e0a\u7684\u6642\u9593\uff0c\u5f80\u5f80\u6bd4\u300c\u601d\u8003\u300d\u9084\u591a\u3002<\/p>\n

\u4e00\u500b\u64c1\u6709 1,000 \u5f35 GPU \u7684\u53e2\u96c6\u5177\u5099\u9a5a\u4eba\u7684\u7406\u8ad6\u80fd\u529b\uff0c\u4f46\u5728\u5be6\u969b\u4e2d\uff0c\u786c\u9ad4\u5f80\u5f80\u628a\u66f4\u591a\u6642\u9593\u82b1\u5728\u300c\u4ea4\u8ac7\u300d\u800c\u4e0d\u662f\u300c\u601d\u8003\u300d\u4e0a\u3002\u5728\u5206\u6563\u5f0f\u8a13\u7df4\u4e2d\uff0c\u68af\u5ea6\u540c\u6b65\u5c31\u662f\u74f6\u9838\u3002\u5982\u679c\u67d0\u500b\u7bc0\u9ede\u7684\u53cd\u5411\u50b3\u64ad\u665a\u4e86 10 \u5206\u9418\u624d\u5b8c\u6210\uff0c\u90a3\u9ebc\u6574\u500b\u53e2\u96c6\u90fd\u5fc5\u9808\u7b49\u5f85\uff0c\u9019\u6703\u5c0e\u81f4\u9577\u6642\u9593\u7684\u9592\u7f6e\u8a08\u7b97\u6642\u9593\u3002<\/p><\/blockquote>\n

\u68af\u5ea6\u540c\u6b65\u4e2d\u7684 all-reduce \u5c31\u6703\u5e36\u4f86\u9019\u7a2e\u5ef6\u9072\u3002\u5728\u6a38\u7d20\u7684\u8cc7\u6599\u5e73\u884c\u8a13\u7df4\u88e1\uff0c\u6bcf\u500b\u53c3\u6578\u5f35\u91cf\u90fd\u9700\u8981\u5404\u81ea\u9032\u884c\u4e00\u6b21 all-reduce\u3002\u6210\u5343\u4e0a\u842c\u6b21\u5c0f\u578b\u64cd\u4f5c\uff0c\u6bcf\u4e00\u6b21\u90fd\u8981\u627f\u64d4\u555f\u52d5\u5ef6\u9072\u3002\u6574\u500b\u53e2\u96c6\u5c31\u5728\u7b49\u5f85\u901a\u8a0a\u5b8c\u6210\u3002\u4f60\u53ef\u4ee5\u900f\u904e\u66f4\u597d\u7684\u6f14\u7b97\u6cd5\u4f86\u964d\u4f4e\u9019\u90e8\u5206\u958b\u92b7\uff1a<\/p>\n

\n\n\n\n\n<\/colgroup>\n\n\n\n\n
\u6f14\u7b97\u6cd5<\/th>\n\u5ef6\u9072\u6b65\u6578<\/th>\n\u5c0d GPU \u9592\u7f6e\u6642\u9593\u7684\u5f71\u97ff<\/th>\n<\/tr>\n
Ring All-Reduce<\/td>\n2(N-1) \u500b\u9806\u5e8f\u6b65\u9a5f<\/td>\n\u5728\u5927\u898f\u6a21\u5834\u666f\u4e0b\u5ef6\u9072\u8f03\u9ad8\uff1b\u9592\u7f6e\u6642\u9593\u6703\u96a8 GPU \u6578\u91cf\u7dda\u6027\u589e\u52a0\u3002<\/td>\n<\/tr>\n
Tree All-Reduce<\/td>\n2*log2(N) \u500b\u6b65\u9a5f<\/td>\n\u5ef6\u9072\u66f4\u4f4e\uff1b\u8207 ring all-reduce \u76f8\u6bd4\uff0c\u53ef\u5728\u5927\u578b\u53e2\u96c6\u4e2d\u986f\u8457\u6e1b\u5c11\u9592\u7f6e\u6642\u9593\u3002<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

Tree All-Reduce \u5c07\u5ef6\u9072\u6b65\u6578\u5f9e\u7dda\u6027\u964d\u4f4e\u5230\u5c0d\u6578\u7d1a\u3002\u5982\u6b64\u4e00\u4f86\uff0c\u53e2\u96c6\u7b49\u5f85\u7684\u6642\u9593\u5c31\u66f4\u5c11\u3002\u8a18\u61b6\u9ad4\u53d7\u9650\u7684\u64cd\u4f5c\u540c\u6a23\u6703\u5077\u8d70\u6548\u80fd\u3002\u6b0a\u91cd\u66f4\u65b0\u548c\u6700\u4f73\u5316\u5668\u6b65\u9a5f\u90fd\u9700\u8981\u8b80\u5beb\u53c3\u6578\u3002\u4e00\u6b21\u6700\u4f73\u5316\u5668\u66f4\u65b0\uff0c\u9700\u8981\u5f9e\u8a18\u61b6\u9ad4\u4e2d\u8b80\u53d6\u5b8c\u6574\u7684\u6a21\u578b\u72c0\u614b\u3002\u6b64\u6642\u8a18\u61b6\u9ad4\u983b\u5bec\u5c31\u6703\u6210\u70ba\u9650\u5236\u56e0\u7d20\u3002\u50cf\u5927\u578b\u77e9\u9663\u4e58\u6cd5\u9019\u6a23\u7684\u8a08\u7b97\u53d7\u9650\u5c64\uff0c\u78ba\u5be6\u80fd\u8b93\u4e00\u5f35 GPU \u4fdd\u6301\u5fd9\u788c\uff0c\u4f46\u5373\u4fbf\u5982\u6b64\uff0c\u4ecd\u7136\u5b58\u5728\u6700\u4f73\u5316\u7a7a\u9593\u3002<\/p>\n

\u5132\u5b58\u8207\u8cc7\u6599\u8f09\u5165\uff1a\u96b1\u85cf\u7684\u7f6a\u9b41\u798d\u9996<\/h3>\n

\u4f60\u53ef\u80fd\u5df2\u7d93\u6700\u4f73\u5316\u4e86\u6bcf\u4e00\u500b\u8a08\u7b97\u8207\u901a\u8a0a\u6b65\u9a5f\uff0c\u53ef GPU \u9084\u662f\u8655\u65bc\u9592\u7f6e\u72c0\u614b\u3002\u771f\u6b63\u7684\u539f\u56e0\uff0c\u5f80\u5f80\u96b1\u85cf\u5728\u5132\u5b58 I\/O \u88e1\u3002\u5f88\u591a\u8cc7\u6599\u79d1\u5b78\u5bb6\u6703\u770b\u5230 GPU \u5229\u7528\u7387\u4f4e\u5230 30%\uff0c\u539f\u56e0\u5c31\u662f\u5728\u7b49\u5f85\u8cc7\u6599\u8f09\u5165\u3002\u8a08\u7b97\u6d41\u7a0b\u6703\u505c\u4f4f\uff0c\u56e0\u70ba\u786c\u9ad4\u5b8c\u6210\u5de5\u4f5c\u7684\u901f\u5ea6\uff0c\u6bd4\u5132\u5b58\u7cfb\u7d71\u63d0\u4f9b\u65b0\u8cc7\u6599\u7684\u901f\u5ea6\u9084\u5feb\u3002<\/p>\n

LLM \u8a13\u7df4\u6d41\u7a0b\u4f9d\u8cf4\u9ad8\u901f\u7684\u8cc7\u6599\u4f9b\u7d66\u3002\u5982\u679c\u5132\u5b58\u7cfb\u7d71\u8ddf\u4e0d\u4e0a\uff0c\u53e2\u96c6\u88e1\u7684\u6bcf\u4e00\u5f35\u52a0\u901f\u5668\u90fd\u53ea\u80fd\u7b49\u5f85\u3002\u898f\u6a21\u8d8a\u5927\uff0c\u9019\u500b\u554f\u984c\u8d8a\u56b4\u91cd\u3002\u4f60\u5fc5\u9808\u7cbe\u5fc3\u8a2d\u8a08\u8cc7\u6599\u8f09\u5165\u6d41\u7a0b\u3002\u4f7f\u7528\u975e\u540c\u6b65\u9810\u53d6\u3002\u5feb\u53d6\u9ad8\u983b\u5b58\u53d6\u8cc7\u6599\u3002\u628a\u8a13\u7df4\u8cc7\u6599\u653e\u5728\u9ad8\u901f\u672c\u6a5f NVMe \u78c1\u789f\u4e0a\u3002\u6bcf\u4e00\u6b65\uff0c\u90fd\u662f\u5728\u6e1b\u5c11\u786c\u9ad4\u7b49\u5f85\u8cc7\u6599\u7684\u6642\u9593\u3002\u6700\u4f73\u5316 AI \u8a13\u7df4\u6d41\u7a0b\uff0c\u610f\u5473\u8457\u8981\u95dc\u6ce8\u6574\u689d\u93c8\u8def\u4e0a\u7684\u6bcf\u4e00\u500b\u74b0\u7bc0\u3002<\/p>\n

\u900f\u904e\u5e73\u884c\u5316\u6700\u5927\u5316 GPU \u5229\u7528\u7387<\/strong><\/h2>\n

\u5e73\u8861\u8cc7\u6599\u5e73\u884c\u3001\u5f35\u91cf\u5e73\u884c\u8207\u7ba1\u7dda\u5e73\u884c<\/h3>\n

\u4f60\u7121\u6cd5\u53ea\u7528\u55ae\u4e00\u88dd\u7f6e\u8a13\u7df4\u4e00\u500b\u5927\u578b\u8a9e\u8a00\u6a21\u578b\u3002\u6a21\u578b\u672c\u8eab\u5c31\u6703\u8d85\u904e\u4efb\u4f55\u55ae\u5f35 GPU \u7684\u8a18\u61b6\u9ad4\u5bb9\u91cf\u3002\u4f60\u5fc5\u9808\u628a\u5de5\u4f5c\u62c6\u5206\u5230\u591a\u5f35 GPU \u4e0a\u3002\u4e3b\u8981\u6709\u4e09\u7a2e\u62c6\u5206\u7b56\u7565\u3002\u6bcf\u4e00\u7a2e\u5728\u901a\u8a0a\u958b\u92b7\u8207\u8a08\u7b97\u6548\u7387\u4e0a\u90fd\u6709\u4e0d\u540c\u6b0a\u8861\u3002\u9078\u5c0d\u7d44\u5408\uff0c\u6703\u76f4\u63a5\u5f71\u97ff\u6574\u9ad4\u6548\u80fd\u3002<\/p>\n

\u8cc7\u6599\u5e73\u884c\u6703\u5728\u6bcf\u500b\u52a0\u901f\u5668\u4e0a\u8907\u88fd\u5b8c\u6574\u6a21\u578b\u3002\u6bcf\u500b\u88dd\u7f6e\u8655\u7406\u4e0d\u540c\u6279\u6b21\u7684\u8cc7\u6599\u3002\u6bcf\u500b\u8a13\u7df4\u6b65\u9a5f\u4e4b\u5f8c\uff0c\u88dd\u7f6e\u4e4b\u9593\u900f\u904e all-reduce \u4ea4\u63db\u68af\u5ea6\u3002\u9019\u7a2e\u65b9\u5f0f\u7684\u901a\u8a0a\u983b\u7387\u8f03\u4f4e\u3002\u4f46\u5b83\u8981\u6c42\u55ae\u4e00\u6a21\u578b\u80fd\u5920\u88dd\u9032\u55ae\u4e00\u88dd\u7f6e\u3002\u5c0d\u65bc\u8d85\u5927\u578b\u6a21\u578b\u4f86\u8aaa\uff0c\u5149\u6a21\u578b\u672c\u8eab\u5c31\u5df2\u7d93\u8d85\u9650\u4e86\u3002<\/p>\n

\u5f35\u91cf\u5e73\u884c\u5247\u628a\u55ae\u5c64\u7684\u6b0a\u91cd\u5207\u5206\u5230\u591a\u5f35 GPU \u4e0a\u3002\u6bcf\u500b\u88dd\u7f6e\u6301\u6709\u6bcf\u500b\u5f35\u91cf\u7684\u4e00\u90e8\u5206\u3002\u88dd\u7f6e\u4e4b\u9593\u5fc5\u9808\u5728\u6bcf\u4e00\u5c64\u5167\u90e8\u53cd\u8986\u4ea4\u63db\u4e2d\u9593\u7d50\u679c\uff0c\u4e26\u900f\u904e all-reduce \u5b8c\u6210\u540c\u6b65\u3002\u9019\u6703\u5e36\u4f86\u5f88\u9ad8\u7684\u901a\u8a0a\u958b\u92b7\u3002\u9019\u7a2e\u6280\u8853\u8981\u6c42\u4f7f\u7528\u50cf NVLink \u9019\u6a23\u7684\u9ad8\u983b\u5bec\u4e92\u9023\u3002\u66f4\u9ad8\u7684\u5f35\u91cf\u5e73\u884c\u5ea6\u6703\u964d\u4f4e\u6bcf\u500b\u88dd\u7f6e\u7684\u8a18\u61b6\u9ad4\u5360\u7528\uff0c\u4f46\u4e5f\u6703\u7e2e\u5c0f\u77e9\u9663\u898f\u6a21\uff0c\u5c0e\u81f4\u90a3\u4e9b\u70ba\u5927\u578b\u77e9\u9663\u6700\u4f73\u5316\u7684\u6838\u5fc3\u7121\u6cd5\u88ab\u5145\u5206\u5229\u7528\u3002<\/p>\n

\u7ba1\u7dda\u5e73\u884c\u6703\u628a\u6a21\u578b\u5206\u6210\u82e5\u5e72\u968e\u6bb5\u3002\u6bcf\u500b\u968e\u6bb5\u7531\u4e00\u7d44\u9023\u7e8c\u5c64\u7d44\u6210\u3002\u67d0\u500b\u88dd\u7f6e\u7fa4\u7d44\u8ca0\u8cac\u4e00\u500b\u968e\u6bb5\u3002\u6d3b\u5316\u503c\u5728\u968e\u6bb5\u4e4b\u9593\u50b3\u905e\u3002\u9019\u7a2e\u65b9\u5f0f\u7684\u901a\u8a0a\u983b\u7387\u8f03\u4f4e\uff0c\u4f46\u6703\u906d\u9047 pipeline bubble\uff08\u7ba1\u7dda\u6c23\u6ce1\uff09\u2014\u2014\u4e5f\u5c31\u662f\u968e\u6bb5\u9593\u7684\u9592\u7f6e\u6642\u9593\u3002\u67d0\u500b\u8f03\u6162\u6216\u8a18\u61b6\u9ad4\u8ca0\u8f09\u8f03\u9ad8\u7684\u968e\u6bb5\uff0c\u6703\u62d6\u6162\u5f8c\u7e8c\u6240\u6709\u968e\u6bb5\u3002<\/p>\n

\u5c0d\u65bc\u8d85\u5927\u578b\u6a21\u578b\uff0c\u4f60\u5fc5\u9808\u628a\u9019\u4e09\u7a2e\u7b56\u7565\u7d50\u5408\u8d77\u4f86\u3002\u9019\u7a2e\u65b9\u6cd5\u88ab\u7a31\u70ba 3D \u5e73\u884c\uff0c\u4e5f\u5c31\u662f\u628a\u8cc7\u6599\u5e73\u884c\u3001\u5f35\u91cf\u5e73\u884c\u548c\u7ba1\u7dda\u5e73\u884c\u758a\u52a0\u4f7f\u7528\u3002\u5b83\u7684\u901a\u8a0a\u6210\u672c\u6700\u9ad8\u3002\u4f60\u9700\u8981\u5177\u5099\u62d3\u6a38\u611f\u77e5\u80fd\u529b\u7684\u6392\u7a0b\u65b9\u5f0f\uff0c\u624d\u80fd\u907f\u514d\u74f6\u9838\u3002\u591a\u6578\u751f\u7522\u7cfb\u7d71\u6703\u63a1\u7528\u6df7\u5408\u914d\u7f6e\uff0c\u4f8b\u5982\u5f35\u91cf\u5e73\u884c\u5ea6\u70ba 2\u3001\u7ba1\u7dda\u5e73\u884c\u5ea6\u70ba 2\u3002\u9019\u6a23\u7684\u5e73\u8861\u53ef\u4ee5\u5728\u62c6\u5206\u6a21\u578b\u7684\u540c\u6642\uff0c\u628a\u901a\u8a0a\u63a7\u5236\u5728\u53ef\u63a5\u53d7\u7bc4\u570d\u5167\u3002\u67d0\u4e9b\u6a21\u578b\u898f\u6a21\u4e0b\uff0c\u7d93\u904e\u6539\u9020\u7684 ZeRO stage-3 \u8b8a\u9ad4\uff0c\u5728\u901a\u8a0a\u958b\u92b7\u4e0a\u751a\u81f3\u53ef\u80fd\u512a\u65bc\u5f35\u91cf\u5e73\u884c\u3002<\/p>\n

\u900f\u904e\u5fae\u6279\u6b21\u8655\u7406\u6e1b\u5c11\u7ba1\u7dda\u6c23\u6ce1<\/h3>\n

\u5728\u7ba1\u7dda\u5e73\u884c\u4e2d\uff0cpipeline bubble \u662f\u6700\u4e3b\u8981\u7684\u9592\u7f6e\u6642\u9593\u4f86\u6e90\u3002\u6c23\u6ce1\u5927\u5c0f\u53d6\u6c7a\u65bc\u968e\u6bb5\u6578\u8207\u5fae\u6279\u6b21\u6578\u3002\u5176\u4f4e\u6548\u7a0b\u5ea6\u5927\u81f4\u8207 \\(Nstages – 1\\) \u9664\u4ee5 \\(Nmicrobatches\\) \u6210\u6b63\u6bd4\u3002\u82e5\u6709 8 \u500b\u968e\u6bb5\u300116 \u500b\u5fae\u6279\u6b21\uff0c\u7406\u8ad6\u6c23\u6ce1\u53ef\u9054\u5230\u7d04 44%\u3002<\/p>\n

\u5fae\u6279\u6b21\u8655\u7406\u80fd\u5920\u964d\u4f4e\u9019\u7a2e\u6c23\u6ce1\u3002\u8207\u5176\u8655\u7406\u4e00\u500b\u5927\u6279\u6b21\uff0c\u4e0d\u5982\u628a\u5b83\u62c6\u6210\u8a31\u591a\u66f4\u5c0f\u7684\u5fae\u6279\u6b21\u3002\u4f60\u628a\u9019\u4e9b\u5fae\u6279\u6b21\u4e00\u500b\u63a5\u4e00\u500b\u5730\u9001\u5165\u7ba1\u7dda\u3002\u9019\u6a23\u4fbf\u80fd\u5728\u6240\u6709\u968e\u6bb5\u4e2d\u5f62\u6210\u7a69\u5b9a\u7684\u5de5\u4f5c\u6d41\u3002\u9810\u71b1\u968e\u6bb5\u4f9d\u820a\u5b58\u5728\u4e00\u4e9b\u9592\u7f6e\u6642\u9593\uff0c\u4f46\u5728\u7a69\u614b\u4e0b\uff0c\u5404\u968e\u6bb5\u90fd\u80fd\u6301\u7e8c\u4fdd\u6301\u5fd9\u788c\u3002<\/p>\n

1F1B \u6392\u7a0b\u6bd4\u65e9\u671f\u65b9\u6cd5\u66f4\u9ad8\u6548\u3002\u5b83\u5305\u62ec\u4e00\u500b\u9810\u71b1\u968e\u6bb5\u3001\u4e00\u500b\u7a69\u614b\u968e\u6bb5\u2014\u2014\u6bcf\u500b worker \u57f7\u884c\u4e00\u6b21\u524d\u5411\u50b3\u64ad\u548c\u4e00\u6b21\u53cd\u5411\u50b3\u64ad\u2014\u2014\u4ee5\u53ca\u4e00\u500b\u6536\u5c3e\u968e\u6bb5\uff0c\u7528\u65bc\u5b8c\u6210\u5269\u9918\u53cd\u5411\u50b3\u64ad\u3002\u8207 GPipe \u65b9\u6cd5\u76f8\u6bd4\uff0c\u5b83\u964d\u4f4e\u4e86\u8a18\u61b6\u9ad4\u4f7f\u7528\u3002<\/p>\n

\u66f4\u5148\u9032\u7684\u6392\u7a0b\u7b56\u7565\uff0c\u4f8b\u5982 Zero Bubble\uff0c\u53ef\u4ee5\u900f\u904e\u628a\u524d\u5411\u8207\u53cd\u5411\u8a08\u7b97\u9032\u4e00\u6b65\u62c6\u5206\u6210\u66f4\u5c0f\u55ae\u5143\uff0c\u4f86\u7e7c\u7e8c\u6e1b\u5c11\u9592\u7f6e\u6642\u9593\u3002\u9019\u4e9b\u7b56\u7565\u6703\u4ea4\u932f\u5b89\u6392\u53cd\u5411\u50b3\u64ad\u4e2d\u7684\u4e0d\u540c\u8a08\u7b97\u90e8\u5206\uff0c\u5f9e\u800c\u5728\u4fdd\u6301\u540c\u6b65\u8a13\u7df4\u512a\u52e2\u7684\u540c\u6642\uff0c\u5c07\u6c23\u6ce1\u58d3\u7e2e\u5230\u63a5\u8fd1\u65bc\u96f6\u3002\u5c0d\u65bc\u6700\u5927\u5316 AI \u8a13\u7df4\u541e\u5410\u800c\u8a00\uff0c\u9019\u4e00\u9ede\u81f3\u95dc\u91cd\u8981\u3002<\/p>\n

\u4f46\u5fae\u6279\u6b21\u8655\u7406\u4e5f\u6709\u4ee3\u50f9\u3002\u8981\u6e1b\u5c11\u6c23\u6ce1\uff0c\u5c31\u9700\u8981\u8db3\u5920\u591a\u7684\u5fae\u6279\u6b21\u3002\u9019\u5f80\u5f80\u6703\u8feb\u4f7f\u4f60\u63a1\u7528\u975e\u5e38\u5927\u7684\u5168\u57df batch size\u3002\u904e\u5927\u7684 batch size \u53ef\u80fd\u640d\u5bb3\u6536\u6582\u6548\u679c\u3002\u7576\u4f60\u628a\u7ba1\u7dda\u5e73\u884c\u8207\u8cc7\u6599\u5e73\u884c\u7d50\u5408\u6642\uff0c\u9084\u5fc5\u9808\u8003\u616e\u55ae\u88dd\u7f6e batch size \u88ab\u9032\u4e00\u6b65\u6524\u8584\u7684\u554f\u984c\u3002\u4f60\u5fc5\u9808\u5728\u9ad8\u541e\u5410\u8207\u9ad8\u6a21\u578b\u54c1\u8cea\u4e4b\u9593\u53d6\u5f97\u5e73\u8861\u3002\u5c0d\u65bc 8 \u500b\u7ba1\u7dda\u968e\u6bb5\uff0c\u7406\u8ad6\u6548\u7387\u53ef\u9054 87.5%\u3002\u4f46\u73fe\u5be6\u7cfb\u7d71\u901a\u5e38\u53ea\u80fd\u9054\u5230 60% \u5230 75%\uff0c\u539f\u56e0\u5728\u65bc\u5fae\u6279\u6b21\u8655\u7406\u984d\u5916\u958b\u92b7\u8207\u8ca0\u8f09\u4e0d\u5747\u8861\u3002\u9019\u662f\u5927\u898f\u6a21 LLM \u8a13\u7df4\u4e2d\u7684\u5e38\u898b\u6311\u6230\u3002<\/p>\n

\u6700\u4f73\u5316\u8a13\u7df4\u8ff4\u5708\u4ee5\u63d0\u5347 GPU \u5229\u7528\u7387<\/strong><\/h2>\n

\u5229\u7528\u6df7\u5408\u7cbe\u5ea6\u8207\u68af\u5ea6\u7d2f\u7a4d<\/h3>\n

\u4f60\u53ef\u4ee5\u900f\u904e\u5f9e FP32 \u5207\u63db\u5230 BF16 \u4f86\u63d0\u5347\u541e\u5410\u3002\u4e0b\u8868\u5c55\u793a\u4e86\u5169\u8005\u7684\u95dc\u9375\u5dee\u7570\uff1a<\/p>\n

\n\n\n\n\n<\/colgroup>\n\n\n\n\n\n\n
\u6307\u6a19<\/th>\nFP32<\/th>\nBF16\uff08\u6df7\u5408\u7cbe\u5ea6\uff09<\/th>\n<\/tr>\n
A100 Tensor Core \u541e\u5410<\/td>\n\u8f03\u4f4e<\/td>\n\u7d04 312 TFLOPS<\/td>\n<\/tr>\n
\u6bcf\u500b\u6578\u503c\u7684\u8a18\u61b6\u9ad4\u5360\u7528<\/td>\n32 \u4f4d\u5143<\/td>\n16 \u4f4d\u5143\uff08\u6e1b\u5c11 50%\uff09<\/td>\n<\/tr>\n
\u52d5\u614b\u7bc4\u570d<\/td>\n\u8207 FP32 \u76f8\u540c<\/td>\n\u8207 FP32 \u76f8\u540c<\/td>\n<\/tr>\n
\u662f\u5426\u9700\u8981 loss scaling<\/td>\n\u4e0d\u9700\u8981<\/td>\n\u4e0d\u9700\u8981<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

BF16 \u70ba\u6307\u6578\u5206\u914d 8 \u4f4d\u5143\u3001\u70ba\u5c3e\u6578\u5206\u914d 7 \u4f4d\u5143\u3002\u56e0\u6b64\u5b83\u64c1\u6709\u8207 FP32 \u76f8\u540c\u5927\u5c0f\u7684\u6307\u6578\u4f4d\u3002\u5b83\u7684\u52d5\u614b\u7bc4\u570d\u8207 FP32 \u4e00\u81f4\u3002\u9019\u6a23\u4f60\u5c31\u80fd\u907f\u514d\u4e0b\u6ea2\u8207\u4e0a\u6ea2\u554f\u984c\uff0c\u4e5f\u4e0d\u9700\u8981 loss scaling\u3002\u6bcf\u500b\u6578\u503c\u6e1b\u5c11 50% \u7684\u8a18\u61b6\u9ad4\u5360\u7528\uff0c\u610f\u5473\u8457\u4f60\u53ef\u4ee5\u4f7f\u7528\u66f4\u5927\u7684 batch size\u3002\u66f4\u5c0f\u7684\u8cc7\u6599\u9ad4\u7a4d\u4e5f\u6703\u6e1b\u5c11\u50b3\u8f38\u91cf\uff0c\u5f9e\u800c\u5e36\u4f86\u6548\u80fd\u63d0\u5347\u3002<\/p>\n

\u68af\u5ea6\u7d2f\u7a4d\u80fd\u8b93\u4f60\u5728\u4e0d\u589e\u52a0\u984d\u5916\u8a18\u61b6\u9ad4\u6210\u672c\u7684\u524d\u63d0\u4e0b\uff0c\u6a21\u64ec\u66f4\u5927\u7684 batch size\u3002\u6a19\u6e96\u6279\u6b21\u8655\u7406\u6703\u589e\u52a0\u8a18\u61b6\u9ad4\u4f7f\u7528\uff0c\u56e0\u70ba\u4f60\u5fc5\u9808\u4fdd\u5b58\u4e2d\u9593\u6d3b\u5316\u503c\u3002\u68af\u5ea6\u7d2f\u7a4d\u6539\u8b8a\u4e86\u9019\u500b\u904e\u7a0b\u3002\u4f60\u7528\u66f4\u5c0f\u7684 micro-batch \u8655\u7406\u8cc7\u6599\u3002\u4f60\u5728\u9019\u4e9b micro-batch \u4e4b\u9593\u7d2f\u52a0\u68af\u5ea6\u3002\u53ea\u6709\u5728\u7d2f\u7a4d\u5230\u8db3\u5920\u591a\u7684\u68af\u5ea6\u4e4b\u5f8c\uff0c\u624d\u66f4\u65b0\u53c3\u6578\u3002\u6709\u6548 batch size \u7b49\u65bc micro-batch size \u4e58\u4ee5 gradient steps \u518d\u4e58\u4ee5 device count\u3002\u9019\u500b\u6280\u5de7\u8207\u8cc7\u6599\u5e73\u884c\u914d\u5408\u826f\u597d\uff0c\u56e0\u70ba\u6bcf\u500b\u88dd\u7f6e\u90fd\u53ef\u4ee5\u7368\u7acb\u7d2f\u7a4d\u68af\u5ea6\u3002\u4f60\u4e5f\u53ef\u4ee5\u628a\u5b83\u8207\u8de8\u591a\u7bc0\u9ede\u7684\u8cc7\u6599\u5e73\u884c\u7d50\u5408\u8d77\u4f86\u4f7f\u7528\u3002\u900f\u904e\u5e73\u6ed1\u8a08\u7b97\u5cf0\u503c\uff0c\u4f60\u53ef\u4ee5\u8b93 GPU \u5229\u7528\u7387\u7dad\u6301\u5728\u8f03\u9ad8\u6c34\u6e96\u3002<\/p>\n

\u7cbe\u7c21\u8cc7\u6599\u8f09\u5165\u8207\u524d\u8655\u7406<\/h3>\n

\u4f60\u7684\u52a0\u901f\u5668\u5b8c\u6210\u8a08\u7b97\u7684\u901f\u5ea6\uff0c\u53ef\u80fd\u5feb\u65bc\u5132\u5b58\u7cfb\u7d71\u63d0\u4f9b\u8cc7\u6599\u7684\u901f\u5ea6\u3002\u9019\u7a2e\u4e0d\u5339\u914d\u6703\u5c0e\u81f4\u9592\u7f6e\u6642\u9593\u3002\u4f60\u5fc5\u9808\u7cbe\u7c21\u8cc7\u6599\u6d41\u7a0b\u3002<\/p>\n

\u4f7f\u7528\u975e\u540c\u6b65\u9810\u53d6\u8207\u5feb\u901f\u672c\u6a5f\u5132\u5b58\uff0c\u628a\u8cc7\u6599\u8f09\u5165\u8207\u8a08\u7b97\u91cd\u758a\u8d77\u4f86\u57f7\u884c\u3002\u9019\u6a23\u53ef\u4ee5\u6d88\u9664\u505c\u9813\uff0c\u8b93\u4f60\u7684\u786c\u9ad4\u5728 LLM \u8a13\u7df4\u671f\u9593\u59cb\u7d42\u4fdd\u6301\u9ad8\u6548\u904b\u8f49\u3002<\/p>\n

\u4f7f\u7528\u5206\u6790\u5de5\u5177\u8a3a\u65b7\u9592\u7f6e GPU<\/strong><\/h2>\n

\u900f\u904e\u76e3\u63a7\u8b58\u5225\u9592\u7f6e\u72c0\u614b<\/h3>\n

\u4f60\u9700\u8981\u770b\u6e05\u6bcf\u4e00\u79d2\u9418\u52a0\u901f\u5668\u7a76\u7adf\u5728\u505a\u4ec0\u9ebc\u3002\u4f7f\u7528\u53ef\u7528\u7684 GPU \u76e3\u63a7\u5de5\u5177\u4f86\u8ffd\u8e64 SM \u6d3b\u8e8d\u5ea6\u8207\u8a18\u61b6\u9ad4\u983b\u5bec\u5229\u7528\u7387\u3002\u8f03\u4f4e\u7684 SM \u6d3b\u8e8d\u5ea6\u8aaa\u660e GPU \u6b63\u5728\u7b49\u5f85\uff0c\u800c\u4e0d\u662f\u5728\u8a08\u7b97\u3002<\/p>\n

\u76e3\u63a7\u300c\u81f3\u5c11\u6709\u4e00\u500b warp \u8655\u65bc\u6d3b\u8e8d\u72c0\u614b\u7684\u6642\u9593\u5360\u6bd4\u300d\u3002\u5982\u679c\u9019\u500b\u503c\u4f4e\u65bc 0.5\uff0c\u5c31\u8868\u793a\u5229\u7528\u6548\u679c\u4e0d\u4f73\u3002\u82e5\u6578\u503c\u975e\u5e38\u4f4e\uff0c\u5247\u8868\u793a SM \u5728\u5927\u90e8\u5206\u6642\u9593\u88e1\u90fd\u8655\u65bc\u9592\u7f6e\u72c0\u614b\u3002\u8a18\u61b6\u9ad4\u983b\u5bec\u5229\u7528\u7387\u5247\u63ed\u793a\u4e86\u8a18\u61b6\u9ad4\u4ecb\u9762\u662f\u5426\u5728\u7a4d\u6975\u50b3\u8f38\u8cc7\u6599\u3002\u5982\u679c\u9019\u88e1\u7684\u6578\u503c\u4e5f\u5f88\u4f4e\uff0c\u5c31\u8868\u793a\u4f60\u7684\u786c\u9ad4\u662f\u5728\u7b49\u5f85\uff0c\u800c\u4e0d\u662f\u5728\u5de5\u4f5c\u3002<\/p>\n

\u5e38\u898b\u7684\u9592\u7f6e\u6a21\u5f0f\u53ca\u5176\u6839\u56e0<\/h3>\n

\u4f60\u6703\u9047\u5230\u5e7e\u7a2e\u53cd\u8986\u51fa\u73fe\u7684\u9592\u7f6e\u6a21\u5f0f\u3002\u540c\u6b65\u5c4f\u969c\u6703\u9020\u6210\u6700\u660e\u986f\u7684\u505c\u9813\u3002\u7576\u67d0\u500b\u7bc0\u9ede\u5b8c\u6210\u53cd\u5411\u50b3\u64ad\u7684\u6642\u9593\u8f03\u665a\u6642\uff0c\u5176\u4ed6\u6240\u6709\u52a0\u901f\u5668\u90fd\u5fc5\u9808\u7b49\u5f85\u3002\u9019\u7a2e\u6a21\u5f0f\u6703\u8868\u73fe\u70ba\u6240\u6709\u88dd\u7f6e\u540c\u6642\u51fa\u73fe\u9031\u671f\u6027\u7684\u6d3b\u8e8d\u5ea6\u4e0b\u8dcc\u3002<\/p>\n

Pipeline bubble \u662f\u53e6\u4e00\u500b\u6301\u7e8c\u5b58\u5728\u7684\u5143\u5147\u3002\u7ba1\u7dda\u5e73\u884c\u5929\u751f\u5c31\u6703\u5f15\u5165\u9019\u7a2e\u9592\u7f6e\u6a21\u5f0f\u3002\u5fae\u6279\u6b21\u6309\u9806\u5e8f\u7a7f\u904e\u5404\u500b\u968e\u6bb5\u3002\u7ba1\u7dda\u5fc5\u9808\u6392\u7a7a\uff0c\u7136\u5f8c\u65b0\u4efb\u52d9\u624d\u80fd\u7e7c\u7e8c\u9032\u5165\u3002\u5728\u9019\u500b\u8f49\u63db\u904e\u7a0b\u4e2d\uff0c\u6709\u4e9b GPU \u6703\u66ab\u6642\u7a7a\u7f6e\u3002\u5373\u4f7f\u4f7f\u7528\u4e86\u6700\u4f73\u5316\u6392\u7a0b\uff0c\u4ecd\u7136\u53ef\u80fd\u7522\u751f\u986f\u8457\u7684\u9592\u7f6e\u6642\u9593\u3002<\/p>\n

I\/O \u74f6\u9838\u6703\u5c0e\u81f4\u9577\u6642\u9593\u7684\u9592\u7f6e\u3002\u6709\u7814\u7a76\u8868\u660e\uff0c\u8a13\u7df4\u6642\u9593\u4e2d\u591a\u9054 70% \u53ef\u80fd\u82b1\u5728\u7b49\u5f85\u8cc7\u6599\u4e0a\uff0c\u5c0e\u81f4 GPU \u8655\u65bc\u9592\u7f6e\u72c0\u614b\u3002\u8b58\u5225\u9019\u4e9b\u300c\u6307\u7d0b\u300d\u6709\u52a9\u65bc\u4f60\u7cbe\u6e96\u9396\u5b9a\u6700\u4f73\u5316\u65b9\u5411\u3002\u4f60\u7684 LLM \u8a13\u7df4\u6548\u80fd\uff0c\u53d6\u6c7a\u65bc\u4f60\u662f\u5426\u80fd\u5224\u65b7\u54ea\u4e00\u7a2e\u6a21\u5f0f\u4e3b\u5c0e\u4e86\u76ee\u524d\u5de5\u4f5c\u8ca0\u8f09\u3002\u53ea\u6709\u9019\u6a23\uff0c\u4f60\u624d\u80fd\u5c0d\u75c7\u4e0b\u85e5\u3002<\/p>\n

\u900f\u904e\u52d5\u614b\u6392\u7a0b\u8655\u7406\u9592\u7f6e GPU<\/strong><\/h2>\n

\u4f60\u7121\u6cd5\u50c5\u9760\u6700\u4f73\u5316\u5c31\u6d88\u9664\u6240\u6709\u9592\u7f6e\u9031\u671f\u3002\u540c\u6b65\u5c4f\u969c\u3001\u7ba1\u7dda\u6c23\u6ce1\u8207\u8cc7\u6599\u8f09\u5165\u7b49\u5f85\uff0c\u7e3d\u6703\u7559\u4e0b\u7a7a\u6a94\u3002\u554f\u984c\u5728\u65bc\uff0c\u4f60\u8981\u5982\u4f55\u5229\u7528\u9019\u4e9b\u7a7a\u6a94\u3002\u52d5\u614b\u6392\u7a0b\u63d0\u4f9b\u4e86\u4e00\u7a2e\u89e3\u6cd5\u3002\u4f60\u9700\u8981\u628a\u53e2\u96c6\u8996\u70ba\u4e00\u500b\u6d3b\u7684\u7cfb\u7d71\u3002\u4f5c\u696d\u6703\u6839\u64da\u5373\u6642\u53ef\u7528\u8cc7\u6e90\u9032\u884c\u4f38\u7e2e\u3002<\/p>\n

\u5be6\u73fe\u5f48\u6027\u8a13\u7df4\u8207\u6436\u5360<\/h3>\n

\u5f48\u6027\u8a13\u7df4\u6703\u6539\u8b8a\u4f5c\u696d\u908a\u754c\u3002\u4f60\u4e0d\u518d\u5b9a\u7fa9\u4e00\u500b\u56fa\u5b9a\u7684 worker \u6578\u91cf\uff0c\u800c\u662f\u5b9a\u7fa9\u6700\u5c0f\u503c\u8207\u6700\u5927\u503c\u7bc4\u570d\u3002TorchElastic \u662f PyTorch \u7684\u5de5\u4f5c\u8ca0\u8f09\u7ba1\u7406\u5de5\u5177\uff0c\u5b83\u8b93\u9019\u7a2e\u65b9\u5f0f\u8b8a\u5f97\u5207\u5be6\u53ef\u884c\u3002\u4f60\u53ef\u4ee5\u5728\u4f5c\u696d\u5b9a\u7fa9\u4e2d\u8a2d\u5b9a minReplicas<\/code> \u8207 maxReplicas<\/code>\u3002\u7cfb\u7d71\u6703\u5728\u9019\u500b\u7bc4\u570d\u5167\u4e0a\u4e0b\u64f4\u7e2e worker\uff0c\u800c\u4e0d\u5fc5\u4e2d\u65b7\u8a13\u7df4\u3002<\/p>\n

\u9019\u7a2e\u67b6\u69cb\u6703\u628a\u63a7\u5236\u5e73\u9762\u5143\u4ef6\u8207 worker \u7bc0\u9ede\u5206\u96e2\u3002\u4f60\u628a TorchElastic controller \u548c Rendezvous server \u57f7\u884c\u5728\u4e0d\u53ef\u6436\u5360\u7684 CPU \u7bc0\u9ede\u4e0a\u3002\u9019\u4e9b\u6838\u5fc3\u5143\u4ef6\u5fc5\u9808\u4fdd\u6301\u53ef\u7528\u3002worker \u5247\u57f7\u884c\u5728 GPU spot instance \u4e0a\u3002\u6210\u672c\u7bc0\u7701\u5c31\u4f86\u81ea\u9019\u7a2e\u90e8\u7f72\u65b9\u5f0f\u3002\u7576\u67d0\u500b spot \u7bc0\u9ede\u88ab\u9a45\u9010\u6642\uff0cTorchElastic \u4e0d\u6703\u8b93\u6574\u500b\u4f5c\u696d\u5931\u6557\u3002\u53ea\u6709\u7576\u6d3b\u8e8d worker \u6578\u91cf\u8dcc\u7834 minReplicas<\/code> \u6642\uff0ccontroller \u624d\u6703\u5224\u5b9a\u4f5c\u696d\u5931\u6557\u3002\u5426\u5247\uff0c\u5b83\u6703\u91cd\u65b0\u6392\u7a0b\u907a\u5931\u7684 pods\uff0c\u4e26\u5f9e\u6700\u8fd1\u4e00\u6b21 checkpoint \u6062\u5fa9\u8a13\u7df4\u3002<\/p>\n

\u9019\u7a2e\u8a2d\u8a08\u80fd\u512a\u96c5\u5730\u8655\u7406\u6436\u5360\u3002\u5931\u53bb\u4e00\u500b worker \u8b8a\u5f97\u53ef\u4ee5\u63a5\u53d7\u3002\u4f60\u7684\u8a13\u7df4\u8cc7\u6599\u8207\u4f5c\u696d\u72c0\u614b\u5b58\u653e\u5728\u639b\u8f09\u7684\u96f2\u7aef\u5132\u5b58\u4e0a\u3002\u7cfb\u7d71\u53ef\u4ee5\u7121\u7e2b\u6062\u5fa9\u3002\u5982\u6b64\u4e00\u4f86\uff0c\u539f\u672c\u53ef\u80fd\u9592\u7f6e\u7684 GPU \u6642\u9593\uff0c\u5c31\u88ab\u8f49\u5316\u6210\u4e86\u53ef\u7522\u751f\u50f9\u503c\u7684\u8a13\u7df4\u9031\u671f\u3002<\/p>\n

\u7e2e\u5bb9\u8207\u66ab\u505c\u4e4b\u9593\u7684\u53d6\u6368\u975e\u5e38\u95dc\u9375\u3002\u7e2e\u5bb9\u6703\u91cb\u653e GPU \u7d66\u5176\u4ed6\u4f5c\u696d\u4f7f\u7528\u3002\u66ab\u505c\u5247\u6703\u4fdd\u7559\u8cc7\u6e90\u5206\u914d\uff0c\u4f46\u8b93\u5b83\u5011\u8655\u65bc\u9592\u7f6e\u72c0\u614b\u3002\u5c0d\u65bc\u5b58\u5728\u7af6\u722d\u6027\u5de5\u4f5c\u8ca0\u8f09\u7684\u53e2\u96c6\u4f86\u8aaa\uff0c\u7e2e\u5bb9\u66f4\u9ad8\u6548\u3002\u4f60\u53ef\u4ee5\u628a\u786c\u9ad4\u91cb\u653e\u7d66\u66f4\u9ad8\u512a\u5148\u7d1a\u4efb\u52d9\u3002\u66ab\u505c\u53ea\u9069\u5408\u5f88\u77ed\u66ab\u7684\u7a7a\u6a94\u3002\u4f46\u5982\u679c\u66ab\u505c\u6642\u9593\u8f03\u9577\uff0c\u5c31\u6703\u6d6a\u8cbb\u5bb9\u91cf\u3002\u5177\u9ad4\u9078\u64c7\u53d6\u6c7a\u65bc\u4f60\u7684\u5de5\u4f5c\u8ca0\u8f09\u7d50\u69cb\u3002\u5c0d\u65bc LLM \u8a13\u7df4\u800c\u8a00\uff0c\u5728\u53ef\u9810\u6e2c\u7684\u9592\u7f6e\u671f\u9032\u884c\u7e2e\u5bb9\uff0c\u901a\u5e38\u662f\u66f4\u512a\u65b9\u6848\u3002\u4f60\u65e2\u80fd\u628a\u786c\u9ad4\u56de\u6536\u7d66\u5176\u4ed6\u4efb\u52d9\u4f7f\u7528\uff0c\u53c8\u4fdd\u7559\u4e86\u5728\u9700\u8981\u6642\u518d\u6b21\u64f4\u5bb9\u7684\u80fd\u529b\u3002<\/p>\n

Kubernetes \u4e2d\u7684\u52d5\u614b\u8cc7\u6e90\u5206\u914d<\/h3>\n

Kubernetes \u628a\u9019\u7a2e\u52d5\u614b\u884c\u70ba\u64f4\u5c55\u5230\u4e86\u6574\u500b\u53e2\u96c6\u3002NVIDIA GPU Operator \u8ca0\u8cac\u90e8\u7f72\u6240\u9700\u5143\u4ef6\u3002GPU Device Plugin \u4ee5 DaemonSet \u5f62\u5f0f\u57f7\u884c\u5728\u6bcf\u500b GPU \u7bc0\u9ede\u4e0a\u3002\u5728\u521d\u59cb\u5316\u671f\u9593\uff0c\u5916\u639b\u7a0b\u5f0f\u6703\u547c\u53eb NVIDIA Management Library\uff08NVML\uff09\u67e5\u8a62\u53ef\u7528 GPU\u3002\u5b83\u6703\u53d6\u5f97\u986f\u793a\u8a18\u61b6\u9ad4\u5bb9\u91cf\u3001\u8a08\u7b97\u80fd\u529b\u4ee5\u53ca\u4e92\u9023\u62d3\u6a38\u7b49\u8cc7\u8a0a\u3002\u96a8\u5f8c\uff0c\u5916\u639b\u7a0b\u5f0f\u900f\u904e nvidia.com\/gpu<\/code> \u9019\u500b\u8cc7\u6e90\u540d\u7a31\uff0c\u5c07\u9019\u4e9b GPU \u8a3b\u518a\u7d66 kubelet\u3002Pods \u4fbf\u53ef\u900f\u904e\u6a19\u6e96\u8cc7\u6e90\u5ba3\u544a\u4f86\u7533\u8acb GPU\u3002<\/p>\n

\u4f60\u5fc5\u9808\u6c7a\u5b9a\uff0c\u5982\u4f55\u5728\u591a\u500b\u5de5\u4f5c\u8ca0\u8f09\u4e4b\u9593\u5171\u4eab GPU\u3002\u4e3b\u8981\u6709\u4e09\u7a2e\u65b9\u6848\u3002\u4e0b\u8868\u7e3d\u7d50\u4e86\u5b83\u5011\u4e4b\u9593\u7684\u6b0a\u8861\uff1a<\/p>\n

\n\n\n\n\n\n<\/colgroup>\n\n\n\n\n\n
\u65b9\u6848<\/th>\n\u9694\u96e2\u6027<\/th>\n\u9748\u6d3b\u6027<\/th>\n\u6700\u9069\u7528\u5834\u666f<\/th>\n<\/tr>\n
MIG<\/td>\n\u5f37\uff08\u786c\u9ad4\u7d1a\uff09<\/td>\n\u975c\u614b\uff08\u9810\u5b9a\u7fa9\u8a2d\u5b9a\u6a94\uff09<\/td>\n\u63a8\u8ad6\u3001\u591a\u79df\u6236<\/td>\n<\/tr>\n
Time Slicing<\/td>\n\u5f31\uff08\u7121\u986f\u793a\u8a18\u61b6\u9ad4\u9694\u96e2\uff09<\/td>\n\u52d5\u614b\uff08\u7121\u9700\u9810\u5148\u5206\u5340\uff09<\/td>\nNotebook\u3001\u6279\u6b21\u4f5c\u696d<\/td>\n<\/tr>\n
Custom Scheduler<\/td>\n\u8edf\u9694\u96e2\uff08\u57fa\u65bc\u6392\u7a0b\u7b56\u7565\uff09<\/td>\n\u9ad8\u5ea6\u53ef\u914d\u7f6e<\/td>\n\u53d7\u4fe1\u4efb\u7684\u5167\u90e8\u4f7f\u7528\u8005<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

Time slicing \u53ef\u57f7\u884c\u65bc\u4efb\u4f55 NVIDIA GPU \u4e0a\u3002\u5b83\u662f\u6700\u5bb9\u6613\u8d77\u6b65\u7684\u65b9\u6848\u3002\u4f46\u5b83\u4e0d\u63d0\u4f9b\u986f\u793a\u8a18\u61b6\u9ad4\u9694\u96e2\uff0c\u4e5f\u4e0d\u63d0\u4f9b\u6545\u969c\u9694\u96e2\u3002MIG \u63d0\u4f9b\u786c\u9ad4\u7d1a\u9694\u96e2\u548c\u53ef\u9810\u6e2c\u6548\u80fd\uff0c\u4f46\u4f9d\u8cf4\u975c\u614b\u8a2d\u5b9a\u6a94\u3002\u91cd\u65b0\u8a2d\u5b9a MIG profile \u5728\u7dad\u904b\u4e0a\u8f03\u70ba\u8907\u96dc\uff0c\u751a\u81f3\u53ef\u80fd\u9700\u8981\u91cd\u8a2d GPU\u3002Custom scheduler \u64c1\u6709\u5f88\u9ad8\u7684\u9748\u6d3b\u6027\uff0c\u4f46\u4ee3\u50f9\u662f\u66f4\u9ad8\u7684\u7dad\u904b\u8907\u96dc\u5ea6\u3002\u4f60\u9700\u8981\u6839\u64da\u81ea\u8eab\u5de5\u4f5c\u8ca0\u8f09\u9700\u6c42\u4f86\u505a\u9078\u64c7\u3002<\/p>\n

\u5177\u5099 GPU \u611f\u77e5\u80fd\u529b\u7684\u6392\u7a0b\u6a5f\u5236\uff0c\u53ef\u4ee5\u8b93\u9592\u7f6e\u8cc7\u6e90\u8f49\u5316\u70ba\u6709\u6548\u5de5\u4f5c\u3002\u4f60\u53ef\u4ee5\u628a\u4e00\u500b\u7bc0\u9ede\u914d\u7f6e\u70ba\u8b93\u591a\u500b pods \u5171\u4eab\u5176 GPU \u6642\u9593\u3002\u67d0\u500b pod \u5728\u7ba1\u7dda\u6c23\u6ce1\u671f\u9593\u57f7\u884c\uff0c\u5c31\u7b49\u65bc\u5229\u7528\u4e86\u672c\u4f86\u6703\u767d\u767d\u6d41\u5931\u7684\u7b97\u529b\u9031\u671f\u3002NVIDIA GPU Operator \u8ca0\u8cac\u7ba1\u7406\u6240\u6709 GPU \u76f8\u95dc\u8cc7\u6e90\u7684\u90e8\u7f72\u8207\u751f\u547d\u9031\u671f\u3002\u5b83\u6703\u90e8\u7f72\u9a45\u52d5\u7a0b\u5f0f\u3001\u88dd\u7f6e\u5916\u639b\u7a0b\u5f0f\u548c\u76e3\u63a7\u5de5\u5177\u3002GPU Feature Discovery \u5143\u4ef6\u6703\u6383\u63cf\u7bc0\u9ede\u4e0a\u7684 GPU \u80fd\u529b\uff0c\u4e26\u5c07\u986f\u793a\u8a18\u61b6\u9ad4\u5927\u5c0f\u8207 CUDA capability \u7b49\u8cc7\u8a0a\u66b4\u9732\u51fa\u4f86\uff0c\u4f9b\u5de5\u4f5c\u8ca0\u8f09\u4f7f\u7528\u3002MIG Manager \u5247\u5141\u8a31\u628a\u786c\u9ad4\u5207\u5206\u70ba\u66f4\u5c0f\u7684\u5be6\u4f8b\u3002\u6bcf\u500b\u5206\u5340\u90fd\u53ef\u4ee5\u5206\u914d\u7d66\u4e0d\u540c\u5de5\u4f5c\u8ca0\u8f09\u3002\u9019\u6a23\u4e00\u4f86\uff0c\u4e00\u5f35\u5be6\u9ad4 GPU \u5c31\u80fd\u88ab\u591a\u500b\u5de5\u4f5c\u8ca0\u8f09\u5171\u4eab\uff0c\u5f9e\u800c\u6700\u5927\u5316 GPU \u5229\u7528\u7387\u3002<\/p>\n

LLM \u8a13\u7df4\u4f5c\u696d\u4fdd\u7559\u5176\u5df2\u5206\u914d\u7684\u5bb9\u91cf\u3002\u8f14\u52a9\u4efb\u52d9\u5247\u53bb\u586b\u88dc\u7a7a\u9699\u3002\u6bcf\u4e00\u500b\u9592\u7f6e\u9031\u671f\uff0c\u90fd\u6703\u8b8a\u6210\u4e00\u6b21\u7522\u51fa\u50f9\u503c\u7684\u6a5f\u6703\u3002<\/p>\n

\u5c07\u9592\u7f6e GPU \u91cd\u65b0\u7528\u65bc\u8f14\u52a9\u5de5\u4f5c\u8ca0\u8f09<\/strong><\/h2>\n

\u5728\u7ba1\u7dda\u6c23\u6ce1\u671f\u9593\u9032\u884c\u63a8\u6e2c\u5f0f\u63a8\u8ad6<\/h3>\n

Pipeline bubble \u6703\u5728\u8a13\u7df4\u8a08\u756b\u4e2d\u88fd\u9020\u51fa\u53ef\u9810\u6e2c\u7684\u7a7a\u6a94\u3002\u9019\u4e9b GPU \u9592\u7f6e\u8996\u7a97\u6703\u898f\u5f8b\u6027\u5730\u53cd\u8986\u51fa\u73fe\u3002\u4f60\u53ef\u4ee5\u7528\u5b83\u5011\u4f86\u505a\u6709\u50f9\u503c\u7684\u5de5\u4f5c\u3002\u63a8\u6e2c\u5f0f\u63a8\u8ad6\u5c31\u662f\u4e00\u500b\u5f88\u6709\u5438\u5f15\u529b\u7684\u9078\u64c7\u3002\u9019\u7a2e\u6280\u8853\u6703\u8b93\u8349\u7a3f\u6a21\u578b\u5148\u65bc\u4e3b\u9a57\u8b49\u6a21\u578b\u57f7\u884c\u3002\u8349\u7a3f\u6a21\u578b\u63d0\u524d\u751f\u6210 token \u5e8f\u5217\u3002\u96a8\u5f8c\uff0c\u4f60\u7684\u4e3b\u6a21\u578b\u4e26\u884c\u9a57\u8b49\u591a\u500b token\u3002\u9019\u6a23\u5c31\u80fd\u5728\u4e0d\u72a7\u7272\u6e96\u78ba\u6027\u7684\u524d\u63d0\u4e0b\uff0c\u52a0\u901f\u63a8\u8ad6\u904e\u7a0b\u3002<\/p>\n

SpecInF \u5c31\u662f\u9019\u4e00\u601d\u8def\u7684\u4e00\u500b\u5be6\u969b\u5be6\u4f5c\u3002\u8a72\u7cfb\u7d71\u6703\u5728\u8a08\u7b97\u6c23\u6ce1\u671f\u9593\u6392\u7a0b\u63a8\u6e2c\u5f0f\u63a8\u8ad6\u4efb\u52d9\u3002\u8a13\u7df4\u4f5c\u696d\u59cb\u7d42\u4fdd\u6709\u6700\u9ad8\u512a\u5148\u7d1a\u3002\u63a8\u8ad6\u5de5\u4f5c\u53ea\u5728\u7a7a\u6a94\u4e2d\u586b\u5145\u57f7\u884c\u3002\u5982\u6b64\u4e00\u4f86\uff0c\u6d6a\u8cbb\u6389\u7684\u9031\u671f\u5c31\u8f49\u5316\u6210\u4e86\u6709\u50f9\u503c\u7684\u8f38\u51fa\u3002\u4f60\u7372\u5f97\u4e86\u984d\u5916\u7684\u63a8\u8ad6\u541e\u5410\uff0c\u537b\u4e0d\u5fc5\u5ef6\u9577\u8a13\u7df4\u6642\u9593\u7dda\u3002\u95dc\u9375\u5728\u65bc\u6392\u7a0b\u7cbe\u5ea6\u3002\u4f60\u5fc5\u9808\u8b93\u63a8\u8ad6\u4efb\u52d9\u8207\u6bcf\u4e00\u500b\u6c23\u6ce1\u7684\u7cbe\u78ba\u6301\u7e8c\u6642\u9577\u76f8\u5339\u914d\u3002\u8f03\u77ed\u7684\u6c23\u6ce1\u9069\u5408\u5c0f\u578b\u8349\u7a3f\u6a21\u578b\u3002\u8f03\u9577\u7684\u7a7a\u6a94\uff0c\u5247\u53ef\u4ee5\u5bb9\u7d0d\u66f4\u91cd\u4e00\u4e9b\u7684\u9a57\u8b49\u5de5\u4f5c\u3002<\/p>\n

\u5728\u8cc7\u6e90\u9694\u96e2\u4e0b\u57f7\u884c\u8f14\u52a9\u4efb\u52d9<\/h3>\n

\u9664\u4e86\u63a8\u8ad6\u4e4b\u5916\uff0c\u4f60\u9084\u53ef\u4ee5\u5728\u9592\u7f6e\u6642\u6bb5\u57f7\u884c\u5176\u4ed6\u5de5\u4f5c\u8ca0\u8f09\u3002\u8cc7\u6599\u524d\u8655\u7406\u901a\u5e38\u6703\u6d88\u8017\u5927\u91cf CPU \u6642\u9593\u3002\u4f60\u53ef\u4ee5\u5728\u8a13\u7df4\u66ab\u505c\u671f\u9593\uff0c\u628a\u9019\u985e\u5de5\u4f5c\u5378\u8f09\u5230 GPU \u4e0a\u3002\u91dd\u5c0d\u9a57\u8b49\u96c6\u7684\u8a55\u4f30\u4efb\u52d9\u4e5f\u5f88\u9069\u5408\u3002\u5b83\u5011\u9700\u8981\u7684\u662f\u7a81\u767c\u5f0f\u7b97\u529b\uff0c\u800c\u4e0d\u662f\u6301\u7e8c\u5360\u7528\u3002\u5c0d\u66f4\u5c0f\u6a21\u578b\u9032\u884c\u9762\u5411\u4e0b\u6e38\u4efb\u52d9\u7684\u5fae\u8abf\uff0c\u4e5f\u662f\u4e00\u500b\u53ef\u884c\u9078\u9805\u3002\u6bcf\u4e00\u7a2e\u8f14\u52a9\u4f5c\u696d\uff0c\u90fd\u80fd\u70ba\u4f60\u7684 LLM \u751f\u614b\u589e\u52a0\u50f9\u503c\u3002<\/p>\n

\u5728\u5171\u4eab\u786c\u9ad4\u6642\uff0c\u8cc7\u6e90\u9694\u96e2\u81f3\u95dc\u91cd\u8981\u3002\u4f60\u7d55\u4e0d\u80fd\u8b93\u8f14\u52a9\u4efb\u52d9\u62d6\u6162\u4e3b\u8981\u8a13\u7df4\u4f5c\u696d\u3002\u786c\u9ad4\u5206\u5340\u65b9\u6848\uff0c\u4f8b\u5982 NVIDIA Multi-Instance GPU\uff08MIG\uff09\uff0c\u53ef\u4ee5\u628a\u4e00\u5f35\u5be6\u9ad4 GPU \u5283\u5206\u6210\u591a\u500b\u76f8\u4e92\u9694\u96e2\u7684\u5be6\u4f8b\u3002\u6bcf\u500b\u5206\u5340\u90fd\u64c1\u6709\u5c08\u5c6c\u7684\u986f\u793a\u8a18\u61b6\u9ad4\u8207\u8a08\u7b97\u5207\u7247\u3002\u9019\u7a2e\u786c\u9ad4\u7d1a\u9694\u96e2\u53ef\u4ee5\u9632\u6b62\u5f7c\u6b64\u5e72\u64fe\u3002Time slicing \u5247\u63d0\u4f9b\u4e86\u66f4\u9748\u6d3b\u7684\u66ff\u4ee3\u65b9\u6848\u3002\u591a\u500b\u5de5\u4f5c\u8ca0\u8f09\u900f\u904e\u5feb\u901f\u5167\u5bb9\u5207\u63db\u4f86\u5171\u4eab\u540c\u4e00\u5f35 GPU\u3002\u9019\u7a2e\u65b9\u5f0f\u53ef\u57f7\u884c\u65bc\u4efb\u4f55 NVIDIA \u786c\u9ad4\u4e0a\u3002\u7136\u800c\uff0c\u5b83\u7684\u9694\u96e2\u80fd\u529b\u5f31\u65bc MIG\u3002<\/p>\n

\u4f60\u7684\u9078\u64c7\u53d6\u6c7a\u65bc\u5de5\u4f5c\u8ca0\u8f09\u7279\u5fb5\u3002MIG \u9069\u5408\u5c0d\u6548\u80fd\u6709\u56b4\u683c\u8981\u6c42\u7684\u751f\u7522\u74b0\u5883\u3002Time slicing \u66f4\u9069\u5408\u63a2\u7d22\u6027\u4efb\u52d9\u548c\u958b\u767c\u5de5\u4f5c\u3002\u4f60\u9084\u5fc5\u9808\u8003\u616e\u5b89\u5168\u908a\u754c\u3002\u4e0d\u53d7\u4fe1\u4efb\u7684\u5de5\u4f5c\u8ca0\u8f09\u9700\u8981 MIG \u63d0\u4f9b\u7684\u66f4\u5f37\u9694\u96e2\u3002\u53d7\u4fe1\u4efb\u7684\u5167\u90e8\u4efb\u52d9\u5247\u53ef\u4ee5\u5b89\u5168\u5730\u4f7f\u7528 Time slicing\u3002\u9019\u7a2e\u8cc7\u6e90\u5206\u914d\u7b56\u7565\uff0c\u80fd\u78ba\u4fdd\u6bcf\u4e00\u5f35 GPU \u90fd\u5728\u5275\u9020\u50f9\u503c\u3002\u4f60\u7684\u8a13\u7df4\u6548\u80fd\u5f97\u5230\u4fdd\u8b77\uff0c\u800c\u9592\u7f6e\u5bb9\u91cf\u5247\u88ab\u7528\u65bc\u5176\u4ed6\u7528\u9014\u3002\u6700\u7d42\u7d50\u679c\uff0c\u662f\u4e00\u500b\u6301\u7e8c\u671d\u591a\u500b\u76ee\u6a19\u540c\u6642\u904b\u8f49\u7684\u53e2\u96c6\u3002<\/p>\n

\n
<\/div>\n<\/div>\n

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\u4f60\u7684\u73fe\u4ee3\u5316 GPU \u53e2\u96c6\u5728\u7406\u8ad6\u4e0a\u64c1\u6709\u9a5a\u4eba\u7684\u5cf0\u503c\u6548\u80fd\u3002\u4f46\u5c0d\u8a31\u591a\u5718\u968a\u4f86\u8aaa\uff0c\u73fe\u5be6\u537b\u622a\u7136\u4e0d\u540c\u3002\u4f60\u5e38\u5e38\u6703\u770b\u5230\u5e73\u5747 GPU […]<\/p>\n

Read More…<\/a><\/p>\n","protected":false},"author":1,"featured_media":34613,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[8116],"tags":[13255,13256,13257,12244,5971],"class_list":["post-34617","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-japan-dedicated-server-tc","tag-gpt-6-training","tag-idle-gpu-resources","tag-llm-optimization","tag-gpu-utilization","tag-ai-infrastructure-tc"],"acf":[],"yoast_head":"\nGPT-6 \u8a13\u7df4\u671f\u9593\u7684 GPU \u5229\u7528\u7387\u8207\u9592\u7f6e\u8cc7\u6e90\u8655\u7406<\/title>\n<meta name=\"description\" content=\"\u900f\u904e\u89e3\u6c7a\u8a08\u7b97\u3001\u8a18\u61b6\u9ad4\u8207\u901a\u8a0a\u74f6\u9838\u4f86\u63d0\u5347 GPT-6 \u8a13\u7df4\u671f\u9593\u7684 GPU \u5229\u7528\u7387\uff0c\u4e26\u5c07\u9592\u7f6e GPU \u8f49\u5316\u70ba\u53ef\u7522\u751f\u50f9\u503c\u7684\u8cc7\u6e90\u3002\" 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