{"id":21319,"date":"2025-01-02T11:23:19","date_gmt":"2025-01-02T03:23:19","guid":{"rendered":"https:\/\/www.simcentric.com\/uncategorized-sc\/what-are-the-4-layers-of-ai-computing-power\/"},"modified":"2025-01-02T11:25:22","modified_gmt":"2025-01-02T03:25:22","slug":"what-are-the-4-layers-of-ai-computing-power","status":"publish","type":"post","link":"https:\/\/www.simcentric.com\/sc\/america-dedicated-server-sc\/what-are-the-4-layers-of-ai-computing-power\/","title":{"rendered":"AI\u7b97\u529b\u76844\u4e2a\u5c42\u7ea7\u662f\u4ec0\u4e48\uff1f"},"content":{"rendered":"

[vc_row][vc_column][vc_column_text css=””]<\/p>\n

AI\u7b97\u529b<\/a>\u57fa\u7840\u8bbe\u65bd\u7684\u683c\u5c40\u5df2\u7ecf\u6f14\u53d8\u6210\u4e00\u4e2a\u590d\u6742\u7684\u56db\u5c42\u67b6\u6784\uff0c\u6bcf\u4e00\u5c42\u5728\u63d0\u4f9b\u73b0\u4ee3AI\u5de5\u4f5c\u8d1f\u8f7d\u6240\u9700\u7684\u7b97\u529b\u65b9\u9762\u90fd\u53d1\u6325\u7740\u5173\u952e\u4f5c\u7528\u3002\u65e0\u8bba\u60a8\u662f\u8fd0\u884c\u590d\u6742\u7684\u795e\u7ecf\u7f51\u7edc\u8fd8\u662f\u5927\u89c4\u6a21\u90e8\u7f72\u673a\u5668\u5b66\u4e60\u6a21\u578b\uff0c\u4e86\u89e3\u8fd9\u4e9b\u5c42\u7ea7\u5bf9\u4e8e\u4f18\u5316\u7f8e\u56fd\u670d\u52a1\u5668\u79df\u7528<\/a>\u89e3\u51b3\u65b9\u6848\u90fd\u81f3\u5173\u91cd\u8981\u3002<\/p>\n

1. \u57fa\u7840\uff1aAI\u82af\u7247\u5c42<\/strong><\/h2>\n

AI\u7b97\u529b\u7684\u6838\u5fc3\u662f\u4e13\u4e3a\u77e9\u9635\u8fd0\u7b97\u548c\u5e76\u884c\u5904\u7406\u8bbe\u8ba1\u7684\u4e13\u7528\u786c\u4ef6\u3002NVIDIA\u7684A100\u548cH100 GPU\u5728\u8fd9\u4e00\u9886\u57df\u5360\u636e\u4e3b\u5bfc\u5730\u4f4d\uff0c\u53ef\u63d0\u4f9b\u9ad8\u8fbe624 TFLOPS\u7684FP16\u6027\u80fd\u3002\u82f1\u7279\u5c14\u7684Gaudi2\u548cAMD\u7684MI250\u4e3a\u7279\u5b9a\u5de5\u4f5c\u8d1f\u8f7d\uff08\u5982\u81ea\u7136\u8bed\u8a00\u5904\u7406\uff09\u63d0\u4f9b\u4e86\u5177\u6709\u7ade\u4e89\u529b\u7684\u66ff\u4ee3\u65b9\u6848\u3002<\/p>\n

\u6700\u65b0\u4e00\u4ee3AI\u82af\u7247\u5f7b\u5e95\u6539\u53d8\u4e86\u6df1\u5ea6\u5b66\u4e60\u7b97\u529b\u3002\u57fa\u4e8eHopper\u67b6\u6784\u7684NVIDIA H100\u5f15\u5165\u4e86\u53d8\u9769\u6027\u7279\u6027\uff0c\u5982Transformer\u5f15\u64ce\u548cHBM3\u5185\u5b58\uff0c\u4e0e\u5176\u524d\u4ee3\u4ea7\u54c1\u76f8\u6bd4\uff0c\u5728\u5927\u578b\u8bed\u8a00\u6a21\u578b\u4e0a\u5b9e\u73b0\u4e863\u500d\u66f4\u5feb\u7684\u8bad\u7ec3\u901f\u5ea6\u548c30\u500d\u66f4\u5feb\u7684\u63a8\u7406\u901f\u5ea6\u3002AMD\u7684MI250\u51ed\u501f\u5176\u72ec\u7279\u7684MCM\u8bbe\u8ba1\u5728HPC\u5de5\u4f5c\u8d1f\u8f7d\u65b9\u9762\u8868\u73b0\u51fa\u8272\uff0c\u800c\u82f1\u7279\u5c14\u7684Gaudi2\u5219\u4e3a\u7279\u5b9aAI\u6a21\u578b\u63d0\u4f9b\u4e86\u5177\u6709\u6210\u672c\u6548\u76ca\u7684\u8bad\u7ec3\u65b9\u6848\u3002<\/p>\n

\u82af\u7247\u9009\u62e9\u7684\u5173\u952e\u8003\u8651\u56e0\u7d20\uff1a<\/p>\n

\r\n\/\/ \u6027\u80fd\u6bd4\u8f83\u793a\u4f8b\r\nconst chipComparison = {\r\n    'NVIDIA_H100': {\r\n        FP16_TFLOPS: 624,\r\n        memory: '80GB HBM3',\r\n        powerDraw: '700W'\r\n    },\r\n    'AMD_MI250': {\r\n        FP16_TFLOPS: 383,\r\n        memory: '128GB HBM2e',\r\n        powerDraw: '560W'\r\n    }\r\n};\r\n<\/code><\/pre>\n
2. \u67b6\u6784\uff1a\u7cfb\u7edf\u5c42<\/strong><\/h2>\n
\u7cfb\u7edf\u5c42\u5c06\u786c\u4ef6\u7ec4\u4ef6\u7f16\u6392\u6210\u7edf\u4e00\u7684\u7b97\u529b\u5355\u5143\u3002\u73b0\u4ee3AI\u670d\u52a1\u5668\u901a\u5e38\u91c7\u7528NVLink\u6216Infinity Fabric\u8fdb\u884cGPU\u95f4\u901a\u4fe1\uff0c\u5e76\u8f85\u4ee5InfiniBand\u6216100GbE\u7b49\u9ad8\u5e26\u5bbd\u7f51\u7edc\u3002<\/p>\n
\u7cfb\u7edf\u67b6\u6784\u4f18\u5316\u4e0d\u4ec5\u4ec5\u5c40\u9650\u4e8e\u539f\u59cb\u7b97\u529b\u3002\u73b0\u4ee3AI\u96c6\u7fa4\u5b9e\u65bd\u4e86\u590d\u6742\u7684\u51b7\u5374\u89e3\u51b3\u65b9\u6848\uff0c\u5305\u62ec\u76f4\u63a5\u82af\u7247\u6db2\u51b7\uff0c\u8fd9\u80fd\u5b9e\u73b0\u66f4\u9ad8\u7684\u6301\u7eed\u6027\u80fd\u548c\u66f4\u597d\u7684\u80fd\u6e90\u6548\u7387\u3002CXL\uff08Compute Express Link\uff09\u6280\u672f\u7684\u6574\u5408\u6b63\u5728\u6539\u53d8\u5185\u5b58\u67b6\u6784\uff0c\u5141\u8bb8\u5728\u8ba1\u7b97\u8282\u70b9\u4e4b\u95f4\u8fdb\u884c\u66f4\u7075\u6d3b\u548c\u9ad8\u6548\u7684\u8d44\u6e90\u6c60\u5316\u3002<\/p>\n
\u5178\u578b\u7684\u6df1\u5ea6\u5b66\u4e60\u7cfb\u7edf\u67b6\u6784\uff1a<\/p>\n
\r\nsystem_architecture = {\r\n    'compute': '8x NVIDIA A100 GPUs',\r\n    'memory': '2TB DDR5 RAM',\r\n    'storage': {\r\n        'fast_tier': '8TB NVMe',\r\n        'capacity_tier': '100TB NVMe over fabric'\r\n    },\r\n    'network': 'HDR InfiniBand (200Gbps)'\r\n}\r\n<\/code><\/pre>\n
3. \u667a\u80fd\uff1a\u5e73\u53f0\u5c42<\/strong><\/h2>\n
\u5e73\u53f0\u5c42\u63d0\u4f9bAI\u5f00\u53d1\u548c\u90e8\u7f72\u7684\u6846\u67b6\u548c\u5de5\u5177\u3002\u6d41\u884c\u7684\u9009\u62e9\u5305\u62ecPyTorch\u3001TensorFlow\uff0c\u4ee5\u53ca\u8d8a\u6765\u8d8a\u591a\u7684\u652f\u6301GPU\u7684\u4e91\u539f\u751f\u5e73\u53f0\u5982Kubernetes\u3002<\/p>\n
\u5e73\u53f0\u5c42\u6280\u672f\u7684\u6700\u65b0\u8fdb\u5c55\u5f15\u5165\u4e86\u81ea\u52a8\u6a21\u578b\u5e76\u884c\u548c\u6d41\u6c34\u7ebf\u5e76\u884c\u7b56\u7565\u3002\u50cfDeepSpeed\u548cMegatron-LM\u8fd9\u6837\u7684\u6846\u67b6\u901a\u8fc7\u667a\u80fd\u5de5\u4f5c\u8d1f\u8f7d\u5206\u914d\uff0c\u5b9e\u73b0\u4e86\u4e07\u4ebf\u53c2\u6570\u6a21\u578b\u7684\u9ad8\u6548\u8bad\u7ec3\u3002\u5bb9\u5668\u7f16\u6392\u5e73\u53f0\u5df2\u7ecf\u53d1\u5c55\u5230\u80fd\u591f\u5904\u7406\u590d\u6742\u7684AI\u5de5\u4f5c\u6d41\uff0c\u5177\u6709\u4e13\u95e8\u7684\u8c03\u5ea6\u5668\u6765\u4f18\u5316GPU\u5229\u7528\u7387\u548c\u7ba1\u7406\u591a\u79df\u6237\u73af\u5883\u3002<\/p>\n
GPU\u5de5\u4f5c\u8d1f\u8f7d\u7684Kubernetes\u914d\u7f6e\u793a\u4f8b\uff1a<\/p>\n
\r\napiVersion: v1\r\nkind: Pod\r\nmetadata:\r\n  name: gpu-pod\r\nspec:\r\n  containers:\r\n  - name: gpu-container\r\n    image: nvidia\/cuda:11.0-base\r\n    resources:\r\n      limits:\r\n        nvidia.com\/gpu: 2\r\n<\/code><\/pre>\n
4. \u53ef\u8bbf\u95ee\u6027\uff1a\u4e91\u670d\u52a1\u5c42<\/strong><\/h2>\n
\u4e91\u670d\u52a1\u62bd\u8c61\u4e86\u57fa\u7840\u8bbe\u65bd\u7684\u590d\u6742\u6027\uff0c\u63d0\u4f9bGPU\u5b9e\u4f8b\u548cAI\u5e73\u53f0\u5373\u670d\u52a1\u3002\u7f8e\u56fd\u670d\u52a1\u5668\u79df\u7528\u63d0\u4f9b\u5546\u63d0\u4f9b\u8fd9\u4e9b\u670d\u52a1\u65f6\u5177\u6709\u4e0d\u540c\u7a0b\u5ea6\u7684\u62bd\u8c61\u6027\uff0c\u4ece\u88f8\u91d1\u5c5eGPU\u670d\u52a1\u5668\u5230\u5b8c\u5168\u6258\u7ba1\u7684AI\u5e73\u53f0\u90fd\u6709\u6db5\u76d6\u3002<\/p>\n
\u7f8e\u56fd\u670d\u52a1\u5668\u79df\u7528\u63d0\u4f9b\u5546\u6b63\u5728\u5f00\u521bAI\u5de5\u4f5c\u8d1f\u8f7d\u7684\u521b\u65b0\u5b9a\u4ef7\u6a21\u5f0f\uff0c\u5305\u62ec\u7528\u4e8e\u8bad\u7ec3\u4f5c\u4e1a\u7684\u7ade\u4ef7\u5b9e\u4f8b\u548c\u7528\u4e8e\u63a8\u7406\u5de5\u4f5c\u8d1f\u8f7d\u7684\u9884\u7559\u5bb9\u91cf\u3002\u5148\u8fdb\u7684\u76d1\u63a7\u5de5\u5177\u63d0\u4f9bGPU\u4f7f\u7528\u7387\u3001\u5185\u5b58\u5e26\u5bbd\u548c\u529f\u8017\u7684\u5b9e\u65f6\u6d1e\u5bdf\uff0c\u5b9e\u73b0\u52a8\u6001\u8d44\u6e90\u5206\u914d\u548c\u6210\u672c\u4f18\u5316\u3002\u8bb8\u591a\u63d0\u4f9b\u5546\u73b0\u5728\u63d0\u4f9b\u9884\u914d\u7f6e\u8f6f\u4ef6\u5806\u6808\u548c\u81ea\u52a8\u6269\u5c55\u529f\u80fd\u7684\u4e13\u95e8AI\u4f18\u5316\u73af\u5883\u3002<\/p>\n
\u5178\u578b\u4e91GPU\u5b9e\u4f8b\u89c4\u683c\uff1a<\/p>\n
\r\nclass GPUInstance:\r\n    def __init__(self):\r\n        self.gpu_type = \"NVIDIA A100\"\r\n        self.gpu_count = 8\r\n        self.cpu_cores = 96\r\n        self.memory = \"2TB\"\r\n        self.network = \"100 Gbps\"\r\n        self.storage = \"15TB NVMe\"\r\n<\/code><\/pre>\n
\u9009\u62e9\u6b63\u786e\u7684AI\u7b97\u529b\u89e3\u51b3\u65b9\u6848<\/strong><\/h2>\n
\u60a8\u7684AI\u57fa\u7840\u8bbe\u65bd\u9009\u62e9\u53d6\u51b3\u4e8e\u5de5\u4f5c\u8d1f\u8f7d\u7279\u5f81\u3001\u9884\u7b97\u9650\u5236\u548c\u6269\u5c55\u9700\u6c42\u3002\u7f8e\u56fd\u670d\u52a1\u5668\u6258\u7ba1\u8bbe\u65bd\u5728\u7535\u529b\u6210\u672c\u3001\u7f51\u7edc\u8fde\u63a5\u548c\u6cd5\u89c4\u5408\u89c4\u6027\u65b9\u9762\u5177\u6709\u4f18\u52bf\u3002<\/p>\n
\u5728\u9009\u62e9AI\u7b97\u529b\u89e3\u51b3\u65b9\u6848\u65f6\uff0c\u8bf7\u8003\u8651AI\u6a21\u578b\u7684\u5b8c\u6574\u751f\u547d\u5468\u671f\u3002\u5f00\u53d1\u73af\u5883\u53ef\u80fd\u53d7\u76ca\u4e8e\u4e91\u7684\u7075\u6d3b\u6027\uff0c\u800c\u751f\u4ea7\u90e8\u7f72\u901a\u5e38\u9700\u8981\u72ec\u7acb\u670d\u52a1\u5668\u4ee5\u4fdd\u6301\u7a33\u5b9a\u6027\u80fd\u3002\u7f8e\u56fd\u670d\u52a1\u5668\u79df\u7528\u8bbe\u65bd\u901a\u5e38\u63d0\u4f9b\u6df7\u5408\u89e3\u51b3\u65b9\u6848\uff0c\u7ed3\u5408\u4e86\u4e24\u79cd\u65b9\u6cd5\u7684\u4f18\u52bf\uff0c\u5728\u4e91\u548c\u670d\u52a1\u5668\u6258\u7ba1\u8d44\u6e90\u4e4b\u95f4\u5efa\u7acb\u9ad8\u901f\u4e92\u8fde\u3002<\/p>\n
\u9700\u8981\u8003\u8651\u7684\u56e0\u7d20\u5305\u62ec\uff1a<\/p>\n
– \u8bad\u7ec3\u4e0e\u63a8\u7406\u9700\u6c42<\/p>\n
– \u6570\u636e\u4f4d\u7f6e\u548c\u9690\u79c1concerns<\/p>\n
– \u9884\u7b97\u548c\u603b\u62e5\u6709\u6210\u672c\u8ba1\u7b97<\/p>\n
– \u6269\u5c55\u6a21\u5f0f\u548c\u8d44\u6e90\u5229\u7528\u7387<\/p>\n
\u672a\u6765\u8d8b\u52bf\u548c\u53d1\u5c55<\/strong><\/h2>\n
AI\u7b97\u529b\u9886\u57df\u7ee7\u7eed\u968f\u7740\u5149\u5b66\u8ba1\u7b97\u3001\u795e\u7ecf\u5f62\u6001\u82af\u7247\u548c\u91cf\u5b50\u52a0\u901f\u5668\u7b49\u65b0\u5174\u6280\u672f\u800c\u53d1\u5c55\u3002\u7f8e\u56fd\u670d\u52a1\u5668\u79df\u7528\u63d0\u4f9b\u5546\u7ad9\u5728\u91c7\u7528\u8fd9\u4e9b\u521b\u65b0\u7684\u524d\u6cbf\uff0c\u63d0\u4f9b\u5bf9\u5c16\u7aefAI\u7b97\u529b\u8d44\u6e90\u7684\u65e9\u671f\u8bbf\u95ee\u3002<\/p>\n
AI\u7279\u5b9a\u7f51\u7edc\u534f\u8bae\u548c\u5b9a\u5236\u4e92\u8fde\u7684\u51fa\u73b0\u6709\u671b\u8fdb\u4e00\u6b65\u51cf\u5c11\u5206\u5e03\u5f0f\u8bad\u7ec3\u4e2d\u7684\u901a\u4fe1\u5f00\u9500\u3002\u5149\u5b50\u8ba1\u7b97\u89e3\u51b3\u65b9\u6848\u5728\u7279\u5b9aAI\u5de5\u4f5c\u8d1f\u8f7d\u65b9\u9762\u663e\u793a\u51fa\u524d\u666f\uff0c\u53ef\u80fd\u5728\u80fd\u6e90\u6548\u7387\u65b9\u9762\u63d0\u4f9b\u6570\u91cf\u7ea7\u7684\u6539\u8fdb\u3002\u91cf\u5b50\u8ba1\u7b97\u5143\u7d20\u7684\u6574\u5408\u53ef\u80fd\u4f1a\u5f7b\u5e95\u6539\u53d8AI\u5de5\u4f5c\u6d41\u7a0b\u4e2d\u7684\u67d0\u4e9b\u4f18\u5316\u548c\u6a21\u62df\u4efb\u52a1\u3002<\/p>\n
\u7ed3\u8bba<\/strong><\/h2>\n
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[\/vc_column_text][\/vc_column][\/vc_row]<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"
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