{"id":478333,"date":"2023-08-09T09:31:18","date_gmt":"2023-08-09T09:31:18","guid":{"rendered":""},"modified":"2023-09-05T11:16:31","modified_gmt":"2023-09-05T11:16:31","slug":"parallel-computing","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/cn\/wiki\/parallel-computing\/","title":{"rendered":"\u5e76\u884c\u8ba1\u7b97"},"content":{"rendered":"

\u5e76\u884c\u8ba1\u7b97\u662f\u4e00\u79cd\u5f3a\u5927\u7684\u8ba1\u7b97\u6280\u672f\uff0c\u5b83\u5c06\u590d\u6742\u7684\u4efb\u52a1\u5206\u89e3\u4e3a\u8f83\u5c0f\u7684\u5b50\u95ee\u9898\uff0c\u5e76\u5728\u591a\u4e2a\u5904\u7406\u5355\u5143\u4e0a\u540c\u65f6\u6267\u884c\u3002\u901a\u8fc7\u5229\u7528\u591a\u4e2a\u5904\u7406\u5668\u7684\u529f\u80fd\uff0c\u5e76\u884c\u8ba1\u7b97\u663e\u8457\u63d0\u9ad8\u4e86\u8ba1\u7b97\u7684\u901f\u5ea6\u548c\u6548\u7387\uff0c\u4f7f\u5176\u6210\u4e3a\u79d1\u5b66\u6a21\u62df\u3001\u6570\u636e\u5206\u6790\u3001\u4eba\u5de5\u667a\u80fd\u7b49\u5404\u4e2a\u9886\u57df\u4e0d\u53ef\u6216\u7f3a\u7684\u5de5\u5177\u3002<\/p>\n

\u5e76\u884c\u8ba1\u7b97\u7684\u8d77\u6e90\u5386\u53f2\u53ca\u5176\u9996\u6b21\u63d0\u53ca<\/h2>\n

\u5e76\u884c\u8ba1\u7b97\u7684\u6982\u5ff5\u53ef\u4ee5\u8ffd\u6eaf\u5230 20 \u4e16\u7eaa 40 \u5e74\u4ee3\u521d\uff0c\u5f53\u65f6 Alan Turing \u548c Konrad Zuse \u63d0\u51fa\u4e86\u8ba1\u7b97\u7cfb\u7edf\u4e2d\u5e76\u884c\u6027\u7684\u601d\u60f3\u3002\u7136\u800c\uff0c\u7531\u4e8e\u786c\u4ef6\u7684\u9650\u5236\u548c\u5e76\u884c\u7f16\u7a0b\u6280\u672f\u7684\u7f3a\u4e4f\uff0c\u5e76\u884c\u8ba1\u7b97\u7684\u5b9e\u9645\u5b9e\u73b0\u51fa\u73b0\u5f97\u665a\u5f97\u591a\u3002<\/p>\n

1958 \u5e74\uff0c\u968f\u7740\u63a7\u5236\u6570\u636e\u516c\u53f8 (CDC) 1604 \u7684\u5f00\u53d1\uff0c\u5e76\u884c\u5904\u7406\u7684\u6982\u5ff5\u5f00\u59cb\u53d7\u5230\u5173\u6ce8\uff0c\u8fd9\u662f\u9996\u6279\u914d\u5907\u591a\u5904\u7406\u5668\u7684\u8ba1\u7b97\u673a\u4e4b\u4e00\u3002\u540e\u6765\uff0c\u5728 20 \u4e16\u7eaa 70 \u5e74\u4ee3\uff0c\u7814\u7a76\u673a\u6784\u548c\u5927\u5b66\u5f00\u59cb\u63a2\u7d22\u5e76\u884c\u5904\u7406\u7cfb\u7edf\uff0c\u4ece\u800c\u8bde\u751f\u4e86\u7b2c\u4e00\u53f0\u5e76\u884c\u8d85\u7ea7\u8ba1\u7b97\u673a\u3002<\/p>\n

\u6709\u5173\u5e76\u884c\u8ba1\u7b97\u7684\u8be6\u7ec6\u4fe1\u606f\u3002\u6269\u5c55\u4e3b\u9898\u5e76\u884c\u8ba1\u7b97<\/h2>\n

\u5e76\u884c\u8ba1\u7b97\u6d89\u53ca\u5c06\u5927\u578b\u8ba1\u7b97\u4efb\u52a1\u5212\u5206\u4e3a\u591a\u4e2a\u53ef\u540c\u65f6\u5728\u591a\u4e2a\u5904\u7406\u5668\u4e0a\u6267\u884c\u7684\u8f83\u5c0f\u3001\u53ef\u7ba1\u7406\u7684\u90e8\u5206\u3002\u4e0e\u4f20\u7edf\u7684\u987a\u5e8f\u5904\u7406\uff08\u4efb\u52a1\u4e00\u4e2a\u63a5\u4e00\u4e2a\u5730\u6267\u884c\uff09\u4e0d\u540c\uff0c\u8fd9\u79cd\u65b9\u6cd5\u53ef\u4ee5\u9ad8\u6548\u89e3\u51b3\u95ee\u9898\u548c\u5229\u7528\u8d44\u6e90\u3002<\/p>\n

\u4e3a\u4e86\u5b9e\u73b0\u5e76\u884c\u8ba1\u7b97\uff0c\u4eba\u4eec\u5f00\u53d1\u4e86\u5404\u79cd\u7f16\u7a0b\u6a21\u578b\u548c\u6280\u672f\u3002\u5171\u4eab\u5185\u5b58\u5e76\u884c\u548c\u5206\u5e03\u5f0f\u5185\u5b58\u5e76\u884c\u662f\u8bbe\u8ba1\u5e76\u884c\u7b97\u6cd5\u7684\u4e24\u79cd\u5e38\u89c1\u8303\u4f8b\u3002\u5171\u4eab\u5185\u5b58\u5e76\u884c\u6d89\u53ca\u591a\u4e2a\u5904\u7406\u5668\u5171\u4eab\u76f8\u540c\u7684\u5185\u5b58\u7a7a\u95f4\uff0c\u800c\u5206\u5e03\u5f0f\u5185\u5b58\u5e76\u884c\u91c7\u7528\u4e92\u8fde\u5904\u7406\u5668\u7f51\u7edc\uff0c\u6bcf\u4e2a\u5904\u7406\u5668\u90fd\u6709\u81ea\u5df1\u7684\u5185\u5b58\u3002<\/p>\n

\u5e76\u884c\u8ba1\u7b97\u7684\u5185\u90e8\u7ed3\u6784\u3002\u5e76\u884c\u8ba1\u7b97\u7684\u5de5\u4f5c\u539f\u7406<\/h2>\n

\u5728\u5e76\u884c\u8ba1\u7b97\u7cfb\u7edf\u4e2d\uff0c\u5185\u90e8\u7ed3\u6784\u4e3b\u8981\u53d6\u51b3\u4e8e\u6240\u9009\u62e9\u7684\u67b6\u6784\uff0c\u53ef\u5206\u4e3a\uff1a<\/p>\n

    \n
  1. \n

    Flynn \u7684\u5206\u7c7b\u6cd5\uff1a<\/strong> \u8fd9\u79cd\u5206\u7c7b\u7531 Michael J. Flynn \u63d0\u51fa\uff0c\u6839\u636e\u8ba1\u7b97\u673a\u67b6\u6784\u53ef\u4ee5\u540c\u65f6\u5904\u7406\u7684\u6307\u4ee4\u6d41\u6570\u91cf\uff08\u5355\u4e2a\u6216\u591a\u4e2a\uff09\u548c\u6570\u636e\u6d41\u6570\u91cf\uff08\u5355\u4e2a\u6216\u591a\u4e2a\uff09\u5bf9\u8ba1\u7b97\u673a\u67b6\u6784\u8fdb\u884c\u5206\u7c7b\u3002\u8fd9\u56db\u4e2a\u7c7b\u522b\u5206\u522b\u662f SISD\uff08\u5355\u6307\u4ee4\u3001\u5355\u6570\u636e\uff09\u3001SIMD\uff08\u5355\u6307\u4ee4\u3001\u591a\u6570\u636e\uff09\u3001MISD\uff08\u591a\u6307\u4ee4\u3001\u5355\u6570\u636e\uff09\u548c MIMD\uff08\u591a\u6307\u4ee4\u3001\u591a\u6570\u636e\uff09\u3002MIMD \u67b6\u6784\u4e0e\u73b0\u4ee3\u5e76\u884c\u8ba1\u7b97\u7cfb\u7edf\u6700\u4e3a\u76f8\u5173\u3002<\/p>\n<\/li>\n

  2. \n

    \u5171\u4eab\u5185\u5b58\u7cfb\u7edf\uff1a<\/strong> \u5728\u5171\u4eab\u5185\u5b58\u7cfb\u7edf\u4e2d\uff0c\u591a\u4e2a\u5904\u7406\u5668\u5171\u4eab\u4e00\u4e2a\u516c\u5171\u5730\u5740\u7a7a\u95f4\uff0c\u4ece\u800c\u4f7f\u5b83\u4eec\u80fd\u591f\u9ad8\u6548\u5730\u901a\u4fe1\u548c\u4ea4\u6362\u6570\u636e\u3002\u4f46\u662f\uff0c\u7ba1\u7406\u5171\u4eab\u5185\u5b58\u9700\u8981\u540c\u6b65\u673a\u5236\u6765\u9632\u6b62\u6570\u636e\u51b2\u7a81\u3002<\/p>\n<\/li>\n

  3. \n

    \u5206\u5e03\u5f0f\u5185\u5b58\u7cfb\u7edf\uff1a<\/strong> \u5728\u5206\u5e03\u5f0f\u5185\u5b58\u7cfb\u7edf\u4e2d\uff0c\u6bcf\u4e2a\u5904\u7406\u5668\u90fd\u6709\u81ea\u5df1\u7684\u5185\u5b58\uff0c\u5e76\u901a\u8fc7\u6d88\u606f\u4f20\u9012\u4e0e\u5176\u4ed6\u5904\u7406\u5668\u8fdb\u884c\u901a\u4fe1\u3002\u8fd9\u79cd\u65b9\u6cd5\u9002\u7528\u4e8e\u5927\u89c4\u6a21\u5e76\u884c\u8ba1\u7b97\uff0c\u4f46\u5728\u6570\u636e\u4ea4\u6362\u65b9\u9762\u9700\u8981\u4ed8\u51fa\u66f4\u591a\u52aa\u529b\u3002<\/p>\n<\/li>\n<\/ol>\n

    \u5e76\u884c\u8ba1\u7b97\u7684\u5173\u952e\u7279\u5f81\u5206\u6790<\/h2>\n

    \u5e76\u884c\u8ba1\u7b97\u63d0\u4f9b\u4e86\u51e0\u4e2a\u6709\u52a9\u4e8e\u5176\u91cd\u8981\u6027\u548c\u5e7f\u6cdb\u5e94\u7528\u7684\u5173\u952e\u7279\u6027\uff1a<\/p>\n

      \n
    1. \n

      \u63d0\u9ad8\u901f\u5ea6\uff1a<\/strong> \u901a\u8fc7\u5c06\u4efb\u52a1\u5212\u5206\u5230\u591a\u4e2a\u5904\u7406\u5668\u4e0a\uff0c\u5e76\u884c\u8ba1\u7b97\u663e\u8457\u52a0\u5feb\u4e86\u6574\u4f53\u8ba1\u7b97\u65f6\u95f4\uff0c\u4ece\u800c\u80fd\u591f\u5feb\u901f\u5904\u7406\u590d\u6742\u95ee\u9898\u3002<\/p>\n<\/li>\n

    2. \n

      \u53ef\u6269\u5c55\u6027\uff1a<\/strong> \u5e76\u884c\u8ba1\u7b97\u7cfb\u7edf\u53ef\u4ee5\u901a\u8fc7\u6dfb\u52a0\u66f4\u591a\u5904\u7406\u5668\u8f7b\u677e\u6269\u5c55\uff0c\u4ece\u800c\u80fd\u591f\u5904\u7406\u66f4\u5927\u3001\u66f4\u82db\u523b\u7684\u4efb\u52a1\u3002<\/p>\n<\/li>\n

    3. \n

      \u9ad8\u6027\u80fd\uff1a<\/strong> \u51ed\u501f\u5229\u7528\u96c6\u4f53\u5904\u7406\u80fd\u529b\u7684\u80fd\u529b\uff0c\u5e76\u884c\u8ba1\u7b97\u7cfb\u7edf\u53ef\u4ee5\u8fbe\u5230\u9ad8\u6027\u80fd\u6c34\u5e73\u5e76\u5728\u8ba1\u7b97\u5bc6\u96c6\u578b\u5e94\u7528\u4e2d\u8868\u73b0\u51fa\u8272\u3002<\/p>\n<\/li>\n

    4. \n

      \u8d44\u6e90\u5229\u7528\u7387\uff1a<\/strong> \u5e76\u884c\u8ba1\u7b97\u901a\u8fc7\u5728\u5904\u7406\u5668\u4e4b\u95f4\u6709\u6548\u5730\u5206\u914d\u4efb\u52a1\u3001\u907f\u514d\u7a7a\u95f2\u65f6\u95f4\u5e76\u786e\u4fdd\u66f4\u597d\u7684\u786c\u4ef6\u5229\u7528\u7387\u6765\u4f18\u5316\u8d44\u6e90\u5229\u7528\u7387\u3002<\/p>\n<\/li>\n

    5. \n

      \u5bb9\u9519\u6027\uff1a<\/strong> \u8bb8\u591a\u5e76\u884c\u8ba1\u7b97\u7cfb\u7edf\u91c7\u7528\u5197\u4f59\u548c\u5bb9\u9519\u673a\u5236\uff0c\u786e\u4fdd\u5373\u4f7f\u67d0\u4e9b\u5904\u7406\u5668\u51fa\u73b0\u6545\u969c\u4e5f\u80fd\u7ee7\u7eed\u8fd0\u884c\u3002<\/p>\n<\/li>\n<\/ol>\n

      \u5e76\u884c\u8ba1\u7b97\u7684\u7c7b\u578b<\/h2>\n

      \u6839\u636e\u4e0d\u540c\u7684\u6807\u51c6\uff0c\u5e76\u884c\u8ba1\u7b97\u53ef\u4ee5\u5206\u4e3a\u591a\u79cd\u7c7b\u578b\u3002\u6982\u8ff0\u5982\u4e0b\uff1a<\/p>\n

      \u6839\u636e\u5efa\u7b51\u5206\u7c7b\uff1a<\/h3>\n\n\n\n\n\n\n
      \u5efa\u7b51\u5b66<\/th>\n\u63cf\u8ff0<\/th>\n<\/tr>\n<\/thead>\n
      \u5171\u4eab\u5185\u5b58<\/td>\n\u591a\u4e2a\u5904\u7406\u5668\u5171\u4eab\u4e00\u4e2a\u516c\u5171\u5185\u5b58\uff0c\u4ece\u800c\u53ef\u4ee5\u66f4\u8f7b\u677e\u5730\u5171\u4eab\u6570\u636e\u548c\u540c\u6b65\u3002<\/td>\n<\/tr>\n
      \u5206\u5e03\u5f0f\u5185\u5b58<\/td>\n\u6bcf\u4e2a\u5904\u7406\u5668\u90fd\u6709\u81ea\u5df1\u7684\u5185\u5b58\uff0c\u56e0\u6b64\u9700\u8981\u4f20\u9012\u6d88\u606f\u6765\u5b9e\u73b0\u5904\u7406\u5668\u4e4b\u95f4\u7684\u901a\u4fe1\u3002<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      \u6839\u636e Flynn \u7684\u5206\u7c7b\u6cd5\uff1a<\/h3>\n
        \n
      1. SISD\uff08\u5355\u6307\u4ee4\uff0c\u5355\u6570\u636e\uff09\uff1a<\/strong> \u4f20\u7edf\u7684\u987a\u5e8f\u8ba1\u7b97\u91c7\u7528\u5355\u4e2a\u5904\u7406\u5668\u6bcf\u6b21\u5bf9\u5355\u4e2a\u6570\u636e\u6267\u884c\u4e00\u6761\u6307\u4ee4\u3002<\/li>\n
      2. SIMD\uff08\u5355\u6307\u4ee4\uff0c\u591a\u6570\u636e\uff09\uff1a<\/strong> \u5355\u4e2a\u6307\u4ee4\u53ef\u540c\u65f6\u5e94\u7528\u4e8e\u591a\u4e2a\u6570\u636e\u5143\u7d20\u3002\u5e38\u7528\u4e8e\u56fe\u5f62\u5904\u7406\u5355\u5143 (GPU) \u548c\u77e2\u91cf\u5904\u7406\u5668\u3002<\/li>\n
      3. MISD\uff08\u591a\u6307\u4ee4\uff0c\u5355\u6570\u636e\uff09\uff1a<\/strong> \u7531\u4e8e\u5b83\u6d89\u53ca\u5bf9\u540c\u4e00\u6570\u636e\u8d77\u4f5c\u7528\u7684\u591a\u6761\u6307\u4ee4\uff0c\u56e0\u6b64\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u5f88\u5c11\u4f7f\u7528\u3002<\/li>\n
      4. MIMD\uff08\u591a\u6307\u4ee4\uff0c\u591a\u6570\u636e\uff09\uff1a<\/strong> \u6700\u666e\u904d\u7684\u7c7b\u578b\uff0c\u5176\u4e2d\u591a\u4e2a\u5904\u7406\u5668\u72ec\u7acb\u5730\u5bf9\u4e0d\u540c\u7684\u6570\u636e\u6267\u884c\u4e0d\u540c\u7684\u6307\u4ee4\u3002<\/li>\n<\/ol>\n

        \u6839\u636e\u4efb\u52a1\u7c92\u5ea6\uff1a<\/h3>\n
          \n
        1. \u7ec6\u7c92\u5ea6\u5e76\u884c\uff1a<\/strong> \u6d89\u53ca\u5c06\u4efb\u52a1\u5206\u89e3\u4e3a\u5c0f\u7684\u5b50\u4efb\u52a1\uff0c\u975e\u5e38\u9002\u5408\u89e3\u51b3\u5177\u6709\u5927\u91cf\u72ec\u7acb\u8ba1\u7b97\u7684\u95ee\u9898\u3002<\/li>\n
        2. \u7c97\u7c92\u5ea6\u5e76\u884c\uff1a<\/strong> \u6d89\u53ca\u5c06\u4efb\u52a1\u5212\u5206\u4e3a\u66f4\u5927\u7684\u5757\uff0c\u975e\u5e38\u9002\u5408\u89e3\u51b3\u5177\u6709\u9ad8\u5ea6\u76f8\u4e92\u4f9d\u8d56\u6027\u7684\u95ee\u9898\u3002<\/li>\n<\/ol>\n

          \u5e76\u884c\u8ba1\u7b97\u7684\u4f7f\u7528\u65b9\u6cd5\u3001\u95ee\u9898\u53ca\u5176\u89e3\u51b3\u65b9\u6cd5<\/h2>\n

          \u5e76\u884c\u8ba1\u7b97\u53ef\u5e94\u7528\u4e8e\u5404\u4e2a\u9886\u57df\uff0c\u5305\u62ec\uff1a<\/p>\n

            \n
          1. \n

            \u79d1\u5b66\u4eff\u771f\uff1a<\/strong> \u5e76\u884c\u8ba1\u7b97\u901a\u8fc7\u5728\u5904\u7406\u5668\u4e4b\u95f4\u5212\u5206\u590d\u6742\u7684\u8ba1\u7b97\u6765\u52a0\u901f\u7269\u7406\u3001\u5316\u5b66\u3001\u5929\u6c14\u9884\u62a5\u548c\u5176\u4ed6\u79d1\u5b66\u9886\u57df\u7684\u6a21\u62df\u3002<\/p>\n<\/li>\n

          2. \n

            \u6570\u636e\u5206\u6790\uff1a<\/strong> \u5927\u6570\u636e\u5206\u6790\u548c\u673a\u5668\u5b66\u4e60\u7b49\u5927\u89c4\u6a21\u6570\u636e\u5904\u7406\u53d7\u76ca\u4e8e\u5e76\u884c\u5904\u7406\uff0c\u4ece\u800c\u80fd\u591f\u66f4\u5feb\u5730\u83b7\u5f97\u6d1e\u5bdf\u548c\u9884\u6d4b\u3002<\/p>\n<\/li>\n

          3. \n

            \u5b9e\u65f6\u56fe\u5f62\u548c\u6e32\u67d3\uff1a<\/strong> \u56fe\u5f62\u5904\u7406\u5355\u5143 (GPU) \u91c7\u7528\u5e76\u884c\u6027\u6765\u5b9e\u65f6\u6e32\u67d3\u590d\u6742\u7684\u56fe\u50cf\u548c\u89c6\u9891\u3002<\/p>\n<\/li>\n

          4. \n

            \u9ad8\u6027\u80fd\u8ba1\u7b97 (HPC)\uff1a<\/strong> \u5e76\u884c\u8ba1\u7b97\u662f\u9ad8\u6027\u80fd\u8ba1\u7b97\u7684\u57fa\u77f3\uff0c\u4f7f\u7814\u7a76\u4eba\u5458\u548c\u5de5\u7a0b\u5e08\u80fd\u591f\u89e3\u51b3\u5177\u6709\u5927\u91cf\u8ba1\u7b97\u9700\u6c42\u7684\u590d\u6742\u95ee\u9898\u3002<\/p>\n<\/li>\n<\/ol>\n

            \u5c3d\u7ba1\u5177\u6709\u4f18\u52bf\uff0c\u4f46\u5e76\u884c\u8ba1\u7b97\u4ecd\u9762\u4e34\u6311\u6218\uff0c\u5305\u62ec\uff1a<\/p>\n

              \n
            1. \n

              \u8d1f\u8f7d\u5747\u8861\uff1a<\/strong> \u786e\u4fdd\u5904\u7406\u5668\u4e4b\u95f4\u5747\u5300\u5206\u914d\u4efb\u52a1\u53ef\u80fd\u5177\u6709\u6311\u6218\u6027\uff0c\u56e0\u4e3a\u67d0\u4e9b\u4efb\u52a1\u53ef\u80fd\u6bd4\u5176\u4ed6\u4efb\u52a1\u9700\u8981\u66f4\u957f\u7684\u65f6\u95f4\u624d\u80fd\u5b8c\u6210\u3002<\/p>\n<\/li>\n

            2. \n

              \u6570\u636e\u4f9d\u8d56\u6027\uff1a<\/strong> \u5728\u67d0\u4e9b\u5e94\u7528\u4e2d\uff0c\u4efb\u52a1\u53ef\u80fd\u4f1a\u4f9d\u8d56\u4e8e\u5f7c\u6b64\u7684\u7ed3\u679c\uff0c\u4ece\u800c\u5bfc\u81f4\u6f5c\u5728\u7684\u74f6\u9888\u5e76\u964d\u4f4e\u5e76\u884c\u6548\u7387\u3002<\/p>\n<\/li>\n

            3. \n

              \u901a\u4fe1\u5f00\u9500\uff1a<\/strong> \u5728\u5206\u5e03\u5f0f\u5185\u5b58\u7cfb\u7edf\u4e2d\uff0c\u5904\u7406\u5668\u4e4b\u95f4\u7684\u6570\u636e\u901a\u4fe1\u4f1a\u4ea7\u751f\u5f00\u9500\u5e76\u5f71\u54cd\u6027\u80fd\u3002<\/p>\n<\/li>\n<\/ol>\n

              \u4e3a\u4e86\u89e3\u51b3\u8fd9\u4e9b\u95ee\u9898\uff0c\u5df2\u7ecf\u5f00\u53d1\u4e86\u52a8\u6001\u8d1f\u8f7d\u5e73\u8861\u3001\u9ad8\u6548\u6570\u636e\u5206\u533a\u548c\u6700\u5c0f\u5316\u901a\u4fe1\u5f00\u9500\u7b49\u6280\u672f\u3002<\/p>\n

              \u4e3b\u8981\u7279\u70b9\u53ca\u4e0e\u540c\u7c7b\u672f\u8bed\u7684\u5176\u4ed6\u6bd4\u8f83<\/h2>\n

              \u5e76\u884c\u8ba1\u7b97\u901a\u5e38\u4e0e\u5176\u4ed6\u4e24\u79cd\u8ba1\u7b97\u8303\u5f0f\u8fdb\u884c\u6bd4\u8f83\uff1a\u4e32\u884c\u8ba1\u7b97\uff08\u987a\u5e8f\u5904\u7406\uff09\u548c\u5e76\u53d1\u8ba1\u7b97\u3002<\/p>\n\n\n\n\n\n\n\n\n\n
              \u7279\u5f81<\/th>\n\u5e76\u884c\u8ba1\u7b97<\/th>\n\u4e32\u884c\u8ba1\u7b97<\/th>\n\u5e76\u53d1\u8ba1\u7b97<\/th>\n<\/tr>\n<\/thead>\n
              \u4efb\u52a1\u6267\u884c<\/td>\n\u540c\u65f6\u6267\u884c\u4efb\u52a1<\/td>\n\u987a\u5e8f\u6267\u884c\u4efb\u52a1<\/td>\n\u4efb\u52a1\u91cd\u53e0\u6267\u884c<\/td>\n<\/tr>\n
              \u6548\u7387<\/td>\n\u9ad8\u6548\u5b8c\u6210\u590d\u6742\u4efb\u52a1<\/td>\n\u5927\u578b\u4efb\u52a1\u6548\u7387\u6709\u9650<\/td>\n\u9ad8\u6548\u5904\u7406\u591a\u4efb\u52a1\uff0c\u4e0d\u590d\u6742<\/td>\n<\/tr>\n
              \u590d\u6742\u6027\u5904\u7406<\/td>\n\u5904\u7406\u590d\u6742\u95ee\u9898<\/td>\n\u9002\u5408\u8f83\u7b80\u5355\u7684\u95ee\u9898<\/td>\n\u540c\u65f6\u5904\u7406\u591a\u4e2a\u4efb\u52a1<\/td>\n<\/tr>\n
              \u8d44\u6e90\u5229\u7528\u7387<\/td>\n\u6709\u6548\u5229\u7528\u8d44\u6e90<\/td>\n\u53ef\u80fd\u5bfc\u81f4\u8d44\u6e90\u5229\u7528\u4e0d\u8db3<\/td>\n\u9ad8\u6548\u5229\u7528\u8d44\u6e90<\/td>\n<\/tr>\n
              \u4f9d\u8d56\u5173\u7cfb<\/td>\n\u53ef\u4ee5\u5904\u7406\u4efb\u52a1\u4f9d\u8d56\u6027<\/td>\n\u4f9d\u8d56\u4e8e\u987a\u5e8f\u6d41<\/td>\n\u9700\u8981\u7ba1\u7406\u4f9d\u8d56\u9879<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

              \u4e0e\u5e76\u884c\u8ba1\u7b97\u76f8\u5173\u7684\u672a\u6765\u89c2\u70b9\u548c\u6280\u672f<\/h2>\n

              \u968f\u7740\u6280\u672f\u7684\u8fdb\u6b65\uff0c\u5e76\u884c\u8ba1\u7b97\u4e0d\u65ad\u53d1\u5c55\uff0c\u672a\u6765\u524d\u666f\u5149\u660e\u3002\u4e00\u4e9b\u5173\u952e\u8d8b\u52bf\u548c\u6280\u672f\u5305\u62ec\uff1a<\/p>\n

                \n
              1. \n

                \u5f02\u6784\u67b6\u6784\uff1a<\/strong> \u5c06\u4e0d\u540c\u7c7b\u578b\u7684\u5904\u7406\u5668\uff08CPU\u3001GPU\u3001FPGA\uff09\u7ec4\u5408\u8d77\u6765\u6267\u884c\u4e13\u95e8\u7684\u4efb\u52a1\uff0c\u4ece\u800c\u63d0\u9ad8\u6027\u80fd\u548c\u80fd\u6e90\u6548\u7387\u3002<\/p>\n<\/li>\n

              2. \n

                \u91cf\u5b50\u5e76\u884c\u6027\uff1a<\/strong> \u91cf\u5b50\u8ba1\u7b97\u5229\u7528\u91cf\u5b50\u529b\u5b66\u539f\u7406\u5bf9\u91cf\u5b50\u6bd4\u7279\u8fdb\u884c\u5e76\u884c\u8ba1\u7b97\uff0c\u5f7b\u5e95\u6539\u53d8\u4e86\u7279\u5b9a\u95ee\u9898\u96c6\u7684\u8ba1\u7b97\u3002<\/p>\n<\/li>\n

              3. \n

                \u5206\u5e03\u5f0f\u8ba1\u7b97\u548c\u4e91\u670d\u52a1\uff1a<\/strong> \u53ef\u6269\u5c55\u7684\u5206\u5e03\u5f0f\u8ba1\u7b97\u5e73\u53f0\u548c\u4e91\u670d\u52a1\u4e3a\u66f4\u5e7f\u6cdb\u7684\u53d7\u4f17\u63d0\u4f9b\u5e76\u884c\u5904\u7406\u529f\u80fd\uff0c\u4f7f\u9ad8\u6027\u80fd\u8ba1\u7b97\u8d44\u6e90\u7684\u8bbf\u95ee\u53d8\u5f97\u6c11\u4e3b\u5316\u3002<\/p>\n<\/li>\n

              4. \n

                \u9ad8\u7ea7\u5e76\u884c\u7b97\u6cd5\uff1a<\/strong> \u6b63\u5728\u8fdb\u884c\u7684\u7814\u7a76\u548c\u5f00\u53d1\u91cd\u70b9\u662f\u8bbe\u8ba1\u66f4\u597d\u7684\u5e76\u884c\u7b97\u6cd5\uff0c\u4ee5\u51cf\u5c11\u901a\u4fe1\u5f00\u9500\u5e76\u63d0\u9ad8\u53ef\u6269\u5c55\u6027\u3002<\/p>\n<\/li>\n<\/ol>\n

                \u5982\u4f55\u4f7f\u7528\u4ee3\u7406\u670d\u52a1\u5668\u6216\u5c06\u5176\u4e0e\u5e76\u884c\u8ba1\u7b97\u5173\u8054<\/h2>\n

                \u4ee3\u7406\u670d\u52a1\u5668\u5728\u589e\u5f3a\u5e76\u884c\u8ba1\u7b97\u80fd\u529b\u65b9\u9762\u8d77\u7740\u81f3\u5173\u91cd\u8981\u7684\u4f5c\u7528\uff0c\u5c24\u5176\u662f\u5728\u5927\u578b\u5206\u5e03\u5f0f\u7cfb\u7edf\u4e2d\u3002\u901a\u8fc7\u5145\u5f53\u5ba2\u6237\u7aef\u548c\u670d\u52a1\u5668\u4e4b\u95f4\u7684\u4e2d\u4ecb\uff0c\u4ee3\u7406\u670d\u52a1\u5668\u53ef\u4ee5\u6709\u6548\u5730\u5c06\u4f20\u5165\u8bf7\u6c42\u5206\u914d\u5230\u591a\u4e2a\u8ba1\u7b97\u8282\u70b9\uff0c\u4ece\u800c\u4fc3\u8fdb\u8d1f\u8f7d\u5e73\u8861\u5e76\u6700\u5927\u9650\u5ea6\u5730\u63d0\u9ad8\u8d44\u6e90\u5229\u7528\u7387\u3002<\/p>\n

                \u5728\u5206\u5e03\u5f0f\u7cfb\u7edf\u4e2d\uff0c\u4ee3\u7406\u670d\u52a1\u5668\u53ef\u4ee5\u5c06\u6570\u636e\u548c\u8bf7\u6c42\u8def\u7531\u5230\u6700\u8fd1\u6216\u8d1f\u8f7d\u6700\u5c0f\u7684\u8ba1\u7b97\u8282\u70b9\uff0c\u4ece\u800c\u6700\u5927\u9650\u5ea6\u5730\u51cf\u5c11\u5ef6\u8fdf\u5e76\u4f18\u5316\u5e76\u884c\u5904\u7406\u3002\u6b64\u5916\uff0c\u4ee3\u7406\u670d\u52a1\u5668\u53ef\u4ee5\u7f13\u5b58\u7ecf\u5e38\u8bbf\u95ee\u7684\u6570\u636e\uff0c\u4ece\u800c\u51cf\u5c11\u5bf9\u5197\u4f59\u8ba1\u7b97\u7684\u9700\u6c42\u5e76\u8fdb\u4e00\u6b65\u63d0\u9ad8\u6574\u4f53\u7cfb\u7edf\u6548\u7387\u3002<\/p>\n

                \u76f8\u5173\u94fe\u63a5<\/h2>\n

                \u6709\u5173\u5e76\u884c\u8ba1\u7b97\u7684\u66f4\u591a\u4fe1\u606f\uff0c\u8bf7\u968f\u610f\u6d4f\u89c8\u4ee5\u4e0b\u8d44\u6e90\uff1a<\/p>\n

                  \n
                1. \u5e76\u884c\u8ba1\u7b97\u7b80\u4ecb\u2014\u2014\u963f\u8d21\u56fd\u5bb6\u5b9e\u9a8c\u5ba4<\/a><\/li>\n
                2. \u5e76\u884c\u8ba1\u7b97 \u2013 MIT \u5f00\u653e\u5f0f\u8bfe\u7a0b<\/a><\/li>\n
                3. IEEE \u8ba1\u7b97\u673a\u5b66\u4f1a \u2013 \u5e76\u884c\u5904\u7406\u6280\u672f\u59d4\u5458\u4f1a<\/a><\/li>\n<\/ol>\n

                  \u603b\u4e4b\uff0c\u5e76\u884c\u8ba1\u7b97\u662f\u4e00\u79cd\u53d8\u9769\u6027\u6280\u672f\uff0c\u5b83\u4e3a\u73b0\u4ee3\u8ba1\u7b97\u4efb\u52a1\u63d0\u4f9b\u4e86\u652f\u6301\uff0c\u63a8\u52a8\u4e86\u5404\u4e2a\u9886\u57df\u7684\u7a81\u7834\u3002\u5b83\u80fd\u591f\u5229\u7528\u591a\u4e2a\u5904\u7406\u5668\u7684\u96c6\u4f53\u529b\u91cf\uff0c\u518d\u52a0\u4e0a\u67b6\u6784\u548c\u7b97\u6cd5\u7684\u8fdb\u6b65\uff0c\u4e3a\u8ba1\u7b97\u7684\u672a\u6765\u5e26\u6765\u4e86\u5149\u660e\u7684\u524d\u666f\u3002\u5bf9\u4e8e\u5206\u5e03\u5f0f\u7cfb\u7edf\u7684\u7528\u6237\u6765\u8bf4\uff0c\u4ee3\u7406\u670d\u52a1\u5668\u662f\u4f18\u5316\u5e76\u884c\u5904\u7406\u548c\u63d0\u9ad8\u6574\u4f53\u7cfb\u7edf\u6027\u80fd\u7684\u5b9d\u8d35\u5de5\u5177\u3002<\/p>","protected":false},"featured_media":469111,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-478333","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about Parallel Computing: A Comprehensive Overview<\/mark>","faq_items":[{"question":"What is Parallel computing?","answer":"

                  Answer:<\/strong> Parallel computing is a computational technique that involves breaking down complex tasks into smaller subproblems and executing them simultaneously on multiple processors. By doing so, it significantly accelerates computation, leading to faster and more efficient problem-solving across various fields.<\/p>"},{"question":"How did Parallel computing originate?","answer":"

                  Answer:<\/strong> The concept of Parallel computing dates back to the 1940s when Alan Turing and Konrad Zuse proposed the idea of parallelism in computing systems. Practical implementation, however, emerged later, with the development of the Control Data Corporation (CDC) 1604 in 1958, one of the first computers with multiple processors.<\/p>"},{"question":"What are the key features of Parallel computing?","answer":"

                  Answer:<\/strong> Parallel computing offers several key features, including increased speed, scalability, high performance, efficient resource utilization, and fault tolerance. These attributes make it invaluable for computationally intensive tasks and real-time processing.<\/p>"},{"question":"What are the types of Parallel computing?","answer":"

                  Answer:<\/strong> Parallel computing can be classified based on architectural structures and Flynn's Taxonomy. The architectural classification includes shared memory systems and distributed memory systems. Based on Flynn's Taxonomy, it can be categorized as SISD, SIMD, MISD, and MIMD.<\/p>"},{"question":"How is Parallel computing used?","answer":"

                  Answer:<\/strong> Parallel computing finds applications in diverse fields such as scientific simulations, data analysis, real-time graphics, and high-performance computing (HPC). It accelerates complex calculations and data processing, enabling faster insights and predictions.<\/p>"},{"question":"What are the challenges in Parallel computing?","answer":"

                  Answer:<\/strong> Parallel computing faces challenges such as load balancing, handling data dependencies, and communication overhead in distributed memory systems. These issues are addressed using techniques like dynamic load balancing and efficient data partitioning.<\/p>"},{"question":"What are the future perspectives of Parallel computing?","answer":"

                  Answer:<\/strong> The future of Parallel computing involves advancements in heterogeneous architectures, quantum parallelism, distributed computing, and cloud services. Research is also focused on developing advanced parallel algorithms to enhance scalability and reduce communication overhead.<\/p>"},{"question":"How can proxy servers enhance Parallel computing?","answer":"

                  Answer:<\/strong> Proxy servers play a crucial role in optimizing Parallel computing in distributed systems. By distributing incoming requests across multiple computing nodes and caching frequently accessed data, proxy servers facilitate load balancing and maximize resource utilization, leading to improved system performance.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/cn\/wp-json\/wp\/v2\/wiki\/478333","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/cn\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/cn\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/cn\/wp-json\/wp\/v2\/wiki\/478333\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/cn\/wp-json\/wp\/v2\/media\/469111"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/cn\/wp-json\/wp\/v2\/media?parent=478333"}],"curies":[{"name":"\u53ef\u6e7f\u6027\u7c89\u5242","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}