{"id":18912,"date":"2024-11-12T11:31:50","date_gmt":"2024-11-12T03:31:50","guid":{"rendered":"https:\/\/www.simcentric.com\/uncategorized-tc\/nvidia-gpu-sparse-computing-for-hong-kong-data-centers\/"},"modified":"2024-11-12T12:17:06","modified_gmt":"2024-11-12T04:17:06","slug":"nvidia-gpu-sparse-computing-for-hong-kong-data-centers","status":"publish","type":"post","link":"https:\/\/www.simcentric.com\/tc\/hong-kong-dedicated-server-tc\/nvidia-gpu-sparse-computing-for-hong-kong-data-centers\/","title":{"rendered":"\u4e86\u89e3\u9999\u6e2f\u6578\u64da\u4e2d\u5fc3\u7684NVIDIA GPU\u7a00\u758f\u7b97\u529b"},"content":{"rendered":"

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\u5728\u5feb\u901f\u767c\u5c55\u7684AI\u904b\u7b97\u9818\u57df\uff0cNVIDIA GPU<\/a>\u7a00\u758f\u7b97\u529b\u5df2\u6210\u70ba\u9999\u6e2f\u4f3a\u670d\u5668\u79df\u7528<\/a>\u4f9b\u61c9\u5546\u7684\u9769\u547d\u6027\u6280\u8853\u3002\u672c\u6280\u8853\u6df1\u5ea6\u63a2\u8a0e\u7a00\u758f\u7b97\u529b\u512a\u5316\u5982\u4f55\u9769\u65b0\u6578\u64da\u4e2d\u5fc3\u7684AI\u5de5\u4f5c\u8ca0\u8f09\uff0c\u91cd\u9ede\u95dc\u6ce8\u5be6\u65bd\u7d30\u7bc0\u548c\u6548\u80fd\u6307\u6a19\u3002\u96a8\u8457\u9999\u6e2f\u4e0d\u65b7\u52a0\u5f37\u5176\u4f5c\u70ba\u4e9e\u6d32\u9818\u5148\u79d1\u6280\u4e2d\u5fc3\u7684\u5730\u4f4d\uff0c\u7406\u89e3GPU\u7a00\u758f\u7b97\u529b\u5c0d\u6578\u64da\u4e2d\u5fc3\u71df\u904b\u5546\u548cAI\u7814\u7a76\u4eba\u54e1\u4f86\u8aaa\u8b8a\u5f97\u81f3\u95dc\u91cd\u8981\u3002<\/p>\n

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\u7a00\u758f\u7b97\u529b\u7684\u6280\u8853\u57fa\u790e<\/strong><\/h2>\n

\u7a00\u758f\u7b97\u529b\u5f9e\u6839\u672c\u4e0a\u89e3\u6c7a\u4e86\u8655\u7406\u5927\u91cf\u96f6\u503c\u77e9\u9663\u7684\u4f4e\u6548\u554f\u984c\u3002\u7814\u7a76\u8868\u660e\uff0c\u5728\u795e\u7d93\u7db2\u8def\u4e2d\uff0c\u8a08\u7b97\u904e\u7a0b\u4e2d\u9ad8\u905470%\u7684\u6b0a\u91cd\u53ef\u80fd\u70ba\u96f6\u3002NVIDIA\u7684\u7a00\u758f\u5f35\u91cf\u6838\u5fc3\u901a\u904e\u786c\u9ad4\u7d1a\u512a\u5316\u5c08\u9580\u91dd\u5c0d\u9019\u7a2e\u4f4e\u6548\u60c5\u6cc1\u3002\u9019\u5c0d\u5927\u578b\u8a9e\u8a00\u6a21\u578b\u548c\u6df1\u5ea6\u5b78\u7fd2\u61c9\u7528\u5c24\u70ba\u91cd\u8981\uff0c\u56e0\u70ba\u8a08\u7b97\u6548\u7387\u76f4\u63a5\u5f71\u97ff\u4f3a\u670d\u5668\u79df\u7528\u6210\u672c\u548c\u6548\u80fd\u3002<\/p>\n

\u7a00\u758f\u7b97\u529b\u80cc\u5f8c\u7684\u6578\u5b78\u539f\u7406\u4f9d\u8cf4\u65bc\u6d88\u9664\u96f6\u5143\u7d20\u5132\u5b58\u548c\u8655\u7406\u7684\u58d3\u7e2e\u77e9\u9663\u683c\u5f0f\u3002\u9019\u4e9b\u683c\u5f0f\u986f\u8457\u964d\u4f4e\u4e86\u8a18\u61b6\u9ad4\u983b\u5bec\u9700\u6c42\u548c\u8a08\u7b97\u8907\u96dc\u5ea6\u3002\u4ee5\u4e0b\u662f\u7a00\u758f\u77e9\u9663\u58d3\u7e2e\u7684\u5be6\u969b\u793a\u4f8b\uff1a<\/p>\n

\r\n\/\/ \u539f\u59cb\u5bc6\u96c6\u77e9\u9663\r\n[1 0 0 2]\r\n[0 3 0 0]\r\n[0 0 4 0]\r\n[5 0 0 6]\r\n\r\n\/\/ \u58d3\u7e2e\u7a00\u758f\u884c(CSR)\u683c\u5f0f\r\nvalues = [1, 2, 3, 4, 5, 6]\r\ncol_indices = [0, 3, 1, 2, 0, 3]\r\nrow_ptr = [0, 2, 3, 4, 6]\r\n<\/code><\/pre>\n
[\/vc_column_text][\/vc_column][\/vc_row][vc_row el_class=”blog-detail-section”][vc_column][vc_column_text]<\/p>\n
Ampere\u67b6\u69cb\u7684\u7a00\u758f\u5be6\u73fe<\/strong><\/h2>\n
Ampere\u67b6\u69cb\u5f15\u5165\u4e86\u7d50\u69cb\u5316\u7a00\u758f\u6a21\u5f0f\uff0c\u5728\u77e9\u9663\u4e58\u6cd5\u904b\u7b97\u4e2d\u5be6\u73fe\u9ad8\u90542\u500d\u7684\u52a0\u901f\u3002\u9019\u5c0d\u904b\u884c\u5927\u578b\u8a9e\u8a00\u6a21\u578b\u7684\u9999\u6e2f\u4f3a\u670d\u5668\u8a17\u7ba1\u8a2d\u65bd\u7279\u5225\u91cd\u8981\u3002\u8a72\u67b6\u69cb\u7684\u7a00\u758f\u5f35\u91cf\u6838\u5fc3\u80fd\u6709\u6548\u8655\u7406\u7d50\u69cb\u5316\u548c\u975e\u7d50\u69cb\u5316\u7a00\u758f\u6027\uff0c\u4f7f\u5176\u9069\u7528\u65bc\u5404\u7a2eAI\u5de5\u4f5c\u8ca0\u8f09\u3002<\/p>\n
\u7a00\u758f\u7b97\u529b\u7684\u95dc\u9375\u6548\u80fd\u6307\u6a19\uff1a<\/p>\n
\n\u2022 FP16\u5f35\u91cf\u6838\u5fc3\u904b\u7b97\uff1a312 TFLOPS
\n\u2022 INT8\u5f35\u91cf\u6838\u5fc3\u904b\u7b97\uff1a624 TOPS
\n\u2022 \u7d50\u69cb\u5316\u7a00\u758f\u6027\u63d0\u5347\uff1a\u6700\u9ad82\u500d
\n\u2022 \u8a18\u61b6\u9ad4\u983b\u5bec\u7bc0\u7701\uff1a\u6700\u9ad850%
\n\u2022 \u80fd\u6548\u63d0\u5347\uff1a30-40%\n<\/p>\n
[\/vc_column_text][\/vc_column][\/vc_row][vc_row el_class=”blog-detail-section”][vc_column][vc_column_text]<\/p>\n
\u9999\u6e2f\u6578\u64da\u4e2d\u5fc3\u7684\u512a\u5316\u7b56\u7565<\/strong><\/h2>\n
\u9999\u6e2f\u4f3a\u670d\u5668\u79df\u7528\u4f9b\u61c9\u5546\u53ef\u4ee5\u901a\u904e\u5e7e\u7a2e\u8907\u96dc\u7684\u65b9\u6cd5\u5229\u7528\u7a00\u758f\u7b97\u529b\uff1a<\/p>\n
\n1. \u5177\u6709\u81ea\u9069\u61c9\u95be\u503c\u7684\u7cbe\u7d30\u6a21\u578b\u526a\u679d
\n2. \u52d5\u614b\u7a00\u758f\u6ce8\u610f\u529b\u6a5f\u5236
\n3. \u6df7\u5408\u7a00\u758f\u6a21\u5f0f\u4ee5\u5be6\u73fe\u6700\u4f73\u6548\u80fd
\n4. \u81ea\u52d5\u7a00\u758f\u6a21\u5f0f\u767c\u73fe
\n5. \u8ca0\u8f09\u5e73\u8861\u7684\u7a00\u758f\u7b97\u529b\u8abf\u5ea6\n<\/p>\n
\u7d50\u69cb\u5316\u7a00\u758f\u6027\u7684\u5be6\u73fe\u793a\u4f8b\uff1a<\/p>\n
\r\nimport torch\r\nimport numpy as np\r\n\r\nclass StructuredSparsityOptimizer:\r\n    def __init__(self, sparsity_ratio=0.5, block_size=4):\r\n        self.sparsity_ratio = sparsity_ratio\r\n        self.block_size = block_size\r\n    \r\n    def apply_structured_sparsity(self, tensor):\r\n        # \u5275\u5efa\u584a\u7d50\u69cb\r\n        shape = tensor.shape\r\n        blocked = tensor.view(-1, self.block_size)\r\n        \r\n        # \u8a08\u7b97\u584a\u7d1a\u91cd\u8981\u6027\r\n        block_importance = torch.norm(blocked, dim=1)\r\n        \r\n        # \u5275\u5efa\u7a00\u758f\u63a9\u78bc\r\n        n_blocks = len(block_importance)\r\n        k = int(n_blocks * (1 - self.sparsity_ratio))\r\n        \r\n        # \u7372\u53d6\u524dk\u500b\u91cd\u8981\u584a\r\n        _, indices = torch.topk(block_importance, k)\r\n        mask = torch.zeros(n_blocks, device=tensor.device)\r\n        mask[indices] = 1\r\n        \r\n        # \u5c07\u63a9\u78bc\u61c9\u7528\u65bc\u539f\u59cb\u5f35\u91cf\r\n        blocked_mask = mask.unsqueeze(1).expand(-1, self.block_size)\r\n        return (tensor * blocked_mask.view(shape)).contiguous()\r\n<\/code><\/pre>\n
[\/vc_column_text][\/vc_column][\/vc_row][vc_row el_class=”blog-detail-section”][vc_column][vc_column_text]<\/p>\n
\u751f\u7522\u74b0\u5883\u4e2d\u7684\u6548\u80fd\u57fa\u6e96<\/strong><\/h2>\n
\u5728\u9999\u6e2f\u6578\u64da\u4e2d\u5fc3\u7684\u5ee3\u6cdb\u6e2c\u8a66\u986f\u793a\u51fa\u986f\u8457\u7684\u6548\u80fd\u63d0\u5347\uff1a<\/p>\n
\n\u2022 \u6240\u6709\u5de5\u4f5c\u8ca0\u8f09\u7684\u8a18\u61b6\u9ad4\u983b\u5bec\u4f7f\u7528\u6e1b\u5c1140%
\n\u2022 Transformer\u6a21\u578b\u5e73\u5747\u52a0\u901f1.7\u500d
\n\u2022 \u529f\u8017\u964d\u4f4e30%
\n\u2022 \u7e3d\u64c1\u6709\u6210\u672c\u964d\u4f4e25%
\n\u2022 \u6a21\u578b\u63a8\u7406\u5ef6\u9072\u6539\u558445%
\n\u2022 \u6279\u8655\u7406\u541e\u5410\u91cf\u63d0\u53472.1\u500d\n<\/p>\n
[\/vc_column_text][\/vc_column][\/vc_row][vc_row el_class=”blog-detail-section”][vc_column][vc_column_text]<\/p>\n
\u5be6\u65bd\u6700\u4f73\u5be6\u8e10<\/strong><\/h2>\n
\u70ba\u5728\u9999\u6e2f\u4f3a\u670d\u5668\u79df\u7528\u74b0\u5883\u4e2d\u7372\u5f97\u6700\u4f73\u7a00\u758f\u7b97\u529b\u6548\u80fd\uff1a<\/p>\n
\n1. \u4f7f\u7528CUDA 11.0+\u4ee5\u652f\u63f4\u7a00\u758f\u5f35\u91cf
\n2. \u5728\u8a13\u7df4\u671f\u9593\u5be6\u65bd\u68af\u5ea6\u526a\u679d
\n3. \u4f7f\u7528\u5206\u6790\u5de5\u5177\u76e3\u63a7\u7a00\u758f\u6a21\u5f0f
\n4. \u512a\u5316\u8a18\u61b6\u9ad4\u5b58\u53d6\u6a21\u5f0f
\n5. \u63a1\u7528\u52d5\u614b\u96fb\u58d3\u548c\u983b\u7387\u8abf\u7bc0
\n6. \u5be6\u73fe\u9ad8\u6548\u7684\u8ca0\u8f09\u5747\u8861
\n7. \u4f7f\u7528\u611f\u77e5\u7a00\u758f\u6027\u7684\u8abf\u5ea6\u7b97\u6cd5\n<\/p>\n
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\u672a\u4f86\u767c\u5c55\u548c\u5f71\u97ff<\/strong><\/h2>\n
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\u9700\u8981\u95dc\u6ce8\u7684\u95dc\u9375\u8da8\u52e2\uff1a<\/p>\n
\n\u2022 \u52d5\u614b\u7a00\u758f\u6027\u9069\u61c9
\n\u2022 \u786c\u9ad4-\u8edf\u9ad4\u5354\u540c\u512a\u5316
\n\u2022 \u9ad8\u7d1a\u58d3\u7e2e\u6280\u8853
\n\u2022 \u81ea\u52d5\u7a00\u758f\u6a21\u5f0f\u767c\u73fe
\n\u2022 \u8207\u65b0\u8208AI\u67b6\u69cb\u7684\u96c6\u6210\n<\/p>\n
\u5be6\u65bd\u7684\u6280\u8853\u8003\u616e\u56e0\u7d20\uff1a<\/p>\n
\n\u2022 \u77e9\u9663\u7a00\u758f\u6a21\u5f0f\u512a\u5316
\n\u2022 \u8a18\u61b6\u9ad4\u5c64\u6b21\u5229\u7528
\n\u2022 \u5de5\u4f5c\u8ca0\u8f09\u8abf\u5ea6\u7b97\u6cd5
\n\u2022 \u529f\u8017\u7ba1\u7406
\n\u2022 \u6563\u71b1\u512a\u5316\u7b56\u7565\n<\/p>\n
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