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[vc_row el_class=”blog-detail-section”][vc_column][vc_column_text]<\/p>\n

\u5728\u904b\u7b97\u80fd\u529b\u7684\u9818\u57df\u4e2d\uff0c\u9ad8\u6548\u80fd\u904b\u7b97\uff08HPC\uff09\u7368\u5360\u9c32\u982d\u3002\u672c\u6587\u6df1\u5165\u63a2\u8a0e HPC \u7684\u8907\u96dc\u6027\uff0c\u63a2\u7d22\u5176\u6838\u5fc3\u7d44\u4ef6\u3001\u61c9\u7528\u548c\u6240\u91cb\u653e\u7684\u539f\u59cb\u904b\u7b97\u80fd\u529b\u3002\u7121\u8ad6\u60a8\u662f\u7368\u7acb\u4f3a\u670d\u5668<\/a><\/strong>\u7528\u6236\u9084\u662f\u597d\u5947\u7684\u6280\u8853\u611b\u597d\u8005\uff0c\u6e96\u5099\u6df1\u5165\u63a2\u7d22\u4e26\u884c\u8655\u7406\u3001GPU<\/a><\/strong>\u52a0\u901f\u548c\u4ee4\u4eba\u9a5a\u5606\u7684\u904b\u7b97\u58ef\u8209\u7684\u4e16\u754c\u5427\u3002<\/p>\n

[\/vc_column_text][\/vc_column][\/vc_row][vc_row el_class=”blog-detail-section”][vc_column][vc_column_text]<\/p>\n

\u89e3\u78bc HPC\uff1a\u8d85\u8d8a\u666e\u901a\u7684\u6578\u4f4d\u8a08\u7b97\u5668<\/strong><\/h2>\n
HPC \u7684\u6838\u5fc3\u662f\u5229\u7528\u6d77\u91cf\u904b\u7b97\u8cc7\u6e90\u4f86\u89e3\u6c7a\u8907\u96dc\u554f\u984c\u3002\u8207\u6a19\u6e96\u684c\u4e0a\u578b\u96fb\u8166\u751a\u81f3\u5f37\u5927\u7684\u5de5\u4f5c\u7ad9\u4e0d\u540c\uff0c\u5176\u7cfb\u7d71\u8a2d\u8a08\u7528\u65bc\u8655\u7406\u666e\u901a\u96fb\u8166\u96e3\u4ee5\u61c9\u5c0d\u7684\u4efb\u52d9\u3002\u60f3\u50cf\u6a21\u64ec\u661f\u7cfb\u7684\u8a95\u751f\u3001\u9810\u6e2c\u5168\u7403\u5929\u6c23\u6a21\u5f0f\u6216\u63ed\u958b\u86cb\u767d\u8cea\u647a\u758a\u7684\u5967\u79d8 – \u9019\u5c31\u662f HPC \u5927\u986f\u8eab\u624b\u7684\u5730\u65b9\u3002<\/p>\n
[\/vc_column_text][\/vc_column][\/vc_row][vc_row el_class=”blog-detail-section”][vc_column][vc_column_text]<\/p>\n
\u904b\u7b97\u5de8\u7378\u7684\u69cb\u5efa\u6a21\u584a<\/strong><\/h2>\n
\u9ad8\u6548\u80fd\u904b\u7b97\u7cfb\u7d71\u662f\u5c16\u7aef\u786c\u9ad4\u7d44\u4ef6\u5b8c\u7f8e\u548c\u8ae7\u5de5\u4f5c\u7684\u4ea4\u97ff\u6a02\uff1a<\/p>\n
\n
CPU<\/a><\/strong>\uff1a\u591a\u6838\u91ce\u7378\uff0c\u5177\u6709\u9ad8\u6642\u8108\u901f\u5ea6\u548c\u5de8\u5927\u5feb\u53d6<\/li>\n
GPU\uff1a<\/strong>\u4e26\u884c\u8655\u7406\u5f37\u8005\uff0c\u52a0\u901f\u7279\u5b9a\u904b\u7b97<\/li>\n
\u8a18\u61b6\u9ad4\uff1a<\/strong>\u5927\u91cf\u9ad8\u983b\u5bec\u3001\u4f4e\u5ef6\u9072\u7684 RAM<\/li>\n
\u5132\u5b58\uff1a<\/strong>\u9583\u96fb\u822c\u5feb\u901f\u7684 SSD \u548c\u7528\u65bc\u8cc7\u6599\u5bc6\u96c6\u578b\u64cd\u4f5c\u7684\u4e26\u884c\u6a94\u6848\u7cfb\u7d71<\/li>\n
\u4e92\u9023\uff1a<\/strong>\u5982 InfiniBand \u7b49\u9ad8\u983b\u5bec\u7db2\u8def\uff0c\u7528\u65bc\u7bc0\u9ede\u9593\u7121\u7e2b\u901a\u8a0a<\/li>\n<\/ul>\n
[\/vc_column_text][\/vc_column][\/vc_row][vc_row el_class=”blog-detail-section”][vc_column][vc_column_text]<\/p>\n
\u4e26\u884c\u8655\u7406\uff1a\u5206\u800c\u6cbb\u4e4b<\/strong><\/h2>\n
HPC \u7684\u7955\u8a23\u5728\u65bc\u4e26\u884c\u8655\u7406\u3002\u900f\u904e\u5c07\u8907\u96dc\u554f\u984c\u5206\u89e3\u6210\u66f4\u5c0f\u7684\u584a\uff0c\u4e26\u5728\u6578\u767e\u6216\u6578\u5343\u500b\u904b\u7b97\u7bc0\u9ede\u4e0a\u540c\u6642\u8655\u7406\uff0cHPC \u7cfb\u7d71\u5be6\u73fe\u4e86\u4ee4\u4eba\u96e3\u4ee5\u7f6e\u4fe1\u7684\u901f\u5ea6\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528 Python \u7684 multiprocessing \u6a21\u7d44\u9032\u884c\u4e26\u884c\u8655\u7406\u7684\u7c21\u55ae\u793a\u4f8b\uff1a<\/p>\n
\r\nimport multiprocessing as mp\r\nimport math\r\n\r\ndef calculate_pi(n):\r\n h = 1.0 \/ n\r\n s = 0.0\r\n for i in range(n):\r\n x = h * (i + 0.5)\r\n s += 4.0 \/ (1.0 + x**2)\r\n return s * h\r\n\r\nif __name__ == '__main__':\r\n num_processes = 4\r\n num_steps = 1000000000\r\n\r\n pool = mp.Pool(processes=num_processes)\r\n results = pool.map(calculate_pi, [num_steps\/\/num_processes]*num_processes)\r\n pi = sum(results)\r\n\r\n print(f\"Calculated Pi: {pi}\")\r\n print(f\"Difference from math.pi: {abs(pi - math.pi)}\")\r\n<\/code><\/pre>\n\u9019\u6bb5\u7a0b\u5f0f\u78bc\u4f7f\u7528\u6578\u503c\u7a4d\u5206\u8a08\u7b97 \u03c0\uff0c\u5c07\u5de5\u4f5c\u8ca0\u8f09\u5206\u914d\u5230\u591a\u500b CPU \u6838\u5fc3\u3002\u5728 HPC \u74b0\u5883\u4e2d\uff0c\u60a8\u53ef\u4ee5\u5c07\u5176\u64f4\u5c55\u5230\u6578\u767e\u6216\u6578\u5343\u500b\u7bc0\u9ede\uff0c\u4ee5\u7372\u5f97\u66f4\u4ee4\u4eba\u5370\u8c61\u6df1\u523b\u7684\u6548\u80fd\u63d0\u5347\u3002<\/p>\n [\/vc_column_text][\/vc_column][\/vc_row][vc_row el_class=”blog-detail-section”][vc_column][vc_column_text]<\/p>\nGPU \u52a0\u901f\uff1a\u91cb\u653e\u4e26\u884c\u8655\u7406\u80fd\u529b<\/strong><\/h2>\n\u96d6\u7136 CPU \u64c5\u9577\u5faa\u5e8f\u4efb\u52d9\uff0c\u4f46 GPU \u5728\u4e26\u884c\u904b\u7b97\u65b9\u9762\u8868\u73fe\u51fa\u8272\u3002CUDA\uff08\u7528\u65bc NVIDIA GPU\uff09\u548c OpenCL \u63d0\u4f9b\u4e86\u5229\u7528\u9019\u7a2e\u80fd\u529b\u7684\u6846\u67b6\u3002\u4ee5\u4e0b\u662f C++ \u4e2d CUDA \u7a0b\u5f0f\u8a2d\u8a08\u7684\u4e00\u500b\u793a\u4f8b\uff1a<\/p>\n\r\n#include \r\n#include \r\n\r\n__global__ void vectorAdd(float *a, float *b, float *c, int n)\r\n{\r\n int i = blockDim.x * blockIdx.x + threadIdx.x;\r\n if (i < n) {\r\n c[i] = a[i] + b[i];\r\n }\r\n}\r\n\r\nint main()\r\n{\r\n int n = 1000000;\r\n size_t size = n * sizeof(float);\r\n\r\n float *h_a = (float *)malloc(size);\r\n float *h_b = (float *)malloc(size);\r\n float *h_c = (float *)malloc(size);\r\n\r\n for (int i = 0; i < n; i++) {\r\n h_a[i] = rand() \/ (float)RAND_MAX;\r\n h_b[i] = rand() \/ (float)RAND_MAX;\r\n }\r\n\r\n float *d_a, *d_b, *d_c;\r\n cudaMalloc(&d_a, size);\r\n cudaMalloc(&d_b, size);\r\n cudaMalloc(&d_c, size);\r\n\r\n cudaMemcpy(d_a, h_a, size, cudaMemcpyHostToDevice);\r\n cudaMemcpy(d_b, h_b, size, cudaMemcpyHostToDevice);\r\n\r\n int threadsPerBlock = 256;\r\n int blocksPerGrid = (n + threadsPerBlock - 1) \/ threadsPerBlock;\r\n vectorAdd<<<blocksPerGrid, threadsPerBlock>>>(d_a, d_b, d_c, n);\r\n\r\n cudaMemcpy(h_c, d_c, size, cudaMemcpyDeviceToHost);\r\n\r\n \/\/ Verify results...\r\n\r\n free(h_a); free(h_b); free(h_c);\r\n cudaFree(d_a); cudaFree(d_b); cudaFree(d_c);\r\n\r\n return 0;\r\n}\r\n<\/code><\/pre>\n\u9019\u6bb5 CUDA \u7a0b\u5f0f\u78bc\u6f14\u793a\u4e86\u5728 GPU \u4e0a\u9032\u884c\u5411\u91cf\u52a0\u6cd5\uff0c\u5c55\u793a\u4e86 GPU \u904b\u7b97\u7684\u4e26\u884c\u6027\u3002\u5728 HPC \u5834\u666f\u4e2d\uff0c\u9019\u8f49\u5316\u70ba\u6df1\u5ea6\u5b78\u7fd2\u548c\u79d1\u5b78\u6a21\u64ec\u7b49\u4efb\u52d9\u7684\u5de8\u5927\u52a0\u901f\u3002<\/p>\n [\/vc_column_text][\/vc_column][\/vc_row][vc_row el_class=”blog-detail-section”][vc_column][vc_column_text]<\/p>\nHPC \u7684\u5be6\u969b\u61c9\u7528\uff1a\u7576\u904b\u7b97\u808c\u8089\u9047\u4e0a\u79d1\u5b78\u597d\u5947\u5fc3<\/strong><\/h2>\n\u9ad8\u6548\u80fd\u904b\u7b97\u7684\u5f71\u97ff\u8de8\u8d8a\u591a\u500b\u9818\u57df\uff1a<\/p>\n\n\u6c23\u5019\u5efa\u6a21\uff1a<\/strong>\u6a21\u64ec\u8907\u96dc\u7684\u5927\u6c23\u548c\u6d77\u6d0b\u76f8\u4e92\u4f5c\u7528<\/li>\n \u57fa\u56e0\u9ad4\u5b78\uff1a<\/strong>\u5206\u6790\u6d77\u91cf\u57fa\u56e0\u8cc7\u8a0a\u6578\u64da\u96c6<\/li>\n \u4eba\u5de5\u667a\u6167\uff1a<\/strong>\u8a13\u7df4\u9f90\u5927\u7684\u795e\u7d93\u7db2\u8def<\/li>\n \u91d1\u878d\u5efa\u6a21\uff1a<\/strong>\u904b\u884c\u8907\u96dc\u7684\u98a8\u96aa\u5206\u6790\u548c\u6f14\u7b97\u6cd5\u4ea4\u6613\u6a21\u64ec<\/li>\n\u5929\u9ad4\u7269\u7406\u5b78\uff1a<\/strong>\u6a21\u64ec\u661f\u7cfb\u5f62\u6210\u548c\u5b87\u5b99\u6f14\u5316<\/li>\n<\/ul>\n[\/vc_column_text][\/vc_column][\/vc_row][vc_row el_class=”blog-detail-section”][vc_column][vc_column_text]<\/p>\nHPC \u7684\u672a\u4f86\uff1a\u91cf\u5b50\u98db\u8e8d\u548c\u767e\u842c\u5146\u6b21\u7d1a\u5922\u60f3<\/strong><\/h2>\n\u96a8\u8457\u6211\u5011\u63a8\u52d5\u7d93\u5178\u904b\u7b97\u7684\u908a\u754c\uff0c\u9ad8\u6548\u80fd\u904b\u7b97\u7684\u672a\u4f86\u770b\u8d77\u4f86\u66f4\u52a0\u4ee4\u4eba\u8208\u596e\uff1a<\/p>\n \n\u767e\u842c\u5146\u6b21\u7d1a\u904b\u7b97\uff1a<\/strong>\u80fd\u5920\u6bcf\u79d2\u9032\u884c\u4e00\u767e\u842c\u5146\u6b21\uff0810^18\uff09\u904b\u7b97\u7684\u7cfb\u7d71<\/li>\n \u91cf\u5b50 HPC\uff1a<\/strong>\u5229\u7528\u91cf\u5b50\u529b\u5b78\u5be6\u73fe\u4ee4\u4eba\u96e3\u4ee5\u7f6e\u4fe1\u7684\u904b\u7b97\u80fd\u529b<\/li>\n AI-HPC \u878d\u5408\uff1a<\/strong>\u6df1\u5ea6\u5b78\u7fd2\u6f14\u7b97\u6cd5\u6700\u4f73\u5316\u5de5\u4f5c\u6d41\u7a0b\uff0c\u53cd\u4e4b\u4ea6\u7136<\/li>\n<\/ul>\n[\/vc_column_text][\/vc_column][\/vc_row][vc_row el_class=”blog-detail-section”][vc_column][vc_column_text]<\/p>\n \u64c1\u62b1 HPC \u9769\u547d<\/strong><\/h2>\n\u9ad8\u6548\u80fd\u904b\u7b97\u4e0d\u50c5\u50c5\u662f\u95dc\u65bc\u539f\u59cb\u529f\u7387 – \u5b83\u662f\u95dc\u65bc\u63a8\u52d5\u904b\u7b97\u53ef\u80fd\u6027\u7684\u908a\u754c\u3002\u7576\u6211\u5011\u9032\u5165\u767e\u842c\u5146\u6b21\u7d1a\u904b\u7b97\u6642\u4ee3\u53ca\u66f4\u9060\u7684\u672a\u4f86\uff0cHPC \u5c07\u7e7c\u7e8c\u8655\u65bc\u79d1\u5b78\u767c\u73fe\u548c\u6280\u8853\u5275\u65b0\u7684\u524d\u6cbf\u3002\u7121\u8ad6\u60a8\u662f\u5728\u6a21\u64ec\u5b87\u5b99\u9084\u662f\u8a13\u7df4\u4e0b\u4e00\u4ee3 AI 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