{"id":1598,"date":"2018-11-28T02:37:07","date_gmt":"2018-11-28T02:37:07","guid":{"rendered":""},"modified":"2018-11-28T10:37:53","modified_gmt":"2018-11-28T02:37:53","slug":"%e6%b7%b1%e5%ba%a6%e5%89%96%e6%9e%90%e4%ba%ba%e5%b7%a5%e6%99%ba%e8%83%bd%e8%8a%af%e7%89%87%e7%9a%84%e5%8f%91%e5%b1%95%e7%8e%b0%e7%8a%b6%e5%8f%8a%e8%b6%8b%e5%8a%bf","status":"publish","type":"post","link":"http:\/\/www.szryc.com\/?p=1598","title":{"rendered":"\u6df1\u5ea6\u5256\u6790\u4eba\u5de5\u667a\u80fd\u82af\u7247\u7684\u53d1\u5c55\u73b0\u72b6\u53ca\u8d8b\u52bf"},"content":{"rendered":"

\n\t\u4e00\u3001\u57fa\u672c\u77e5\u8bc6\u53ca\u73b0\u72b6<\/span><\/p>\n

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\n\t <\/div>\n

\n\t<\/p>\n

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\n\t\u4f5c\u4e3a\u4eba\u5de5\u667a\u80fd\u6838\u5fc3\u7684\u5e95\u5c42\u786c\u4ef6 AI \u82af\u7247\uff0c\u4e5f\u540c\u6837\u7ecf\u5386\u4e86\u591a\u6b21\u7684\u8d77\u4f0f\u548c\u6ce2\u6298\uff0c\u603b\u4f53\u770b\u6765\uff0cAI \u82af\u7247\u7684\u53d1\u5c55\u524d\u540e\u7ecf\u5386\u4e86\u56db\u6b21\u5927\u7684\u53d8\u5316\uff0c\u5176\u53d1\u5c55\u5386\u7a0b\u5982\u56fe\u6240\u793a\u3002<\/p>\n

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\n\t2\u3001\u6211\u56fd AI \u82af\u7247\u53d1\u5c55\u60c5\u51b5<\/p>\n

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\n\t\u5c3d\u7ba1\u5982\u6b64\uff0c \u56fd\u5185\u516c\u53f8\u5374\u5e76\u672a\u5982\u56fd\u5916\u5927\u516c\u53f8\u4e00\u6837\u5f62\u6210\u5e02\u573a\u89c4\u6a21\uff0c \u53cd\u800c\u51fa\u73b0\u5404\u81ea\u4e3a\u653f\u7684\u6563\u88c2\u53d1\u5c55\u73b0\u72b6\u3002\u9664\u4e86\u65b0\u5174\u521b\u4e1a\u516c\u53f8\uff0c\u56fd\u5185\u7814\u7a76\u673a\u6784\u5982\u5317\u4eac\u5927\u5b66\u3001\u6e05\u534e\u5927\u5b66\u3001\u4e2d\u56fd\u79d1\u5b66\u9662\u7b49\u5728AI \u82af\u7247\u9886\u57df\u90fd\u6709\u6df1\u5165\u7814\u7a76\uff1b\u800c\u5176\u4ed6\u516c\u53f8\u5982\u767e\u5ea6\u548c\u6bd4\u7279\u5927\u9646\u7b49\uff0c 2017 \u5e74\u4e5f\u6709\u4e00\u4e9b\u6210\u679c\u53d1\u5e03\u3002\u53ef\u4ee5\u9884\u89c1\uff0c\u672a\u6765\u8c01\u5148\u5728\u4eba\u5de5\u667a\u80fd\u9886\u57df\u638c\u63e1\u4e86\u751f\u6001\u7cfb\u7edf\uff0c\u8c01\u5c31\u638c\u63e1\u4f4f\u4e86\u8fd9\u4e2a\u4ea7\u4e1a\u7684\u4e3b\u52a8\u6743\u3002<\/p>\n

\n\t3\u3001AI\u5b66\u8005\u6982\u51b5<\/p>\n

\n\t\u57fa\u4e8e\u6765\u81ea\u6e05\u534e\u5927\u5b66AMiner \u4eba\u624d\u5e93\u6570\u636e\uff0c\u5168\u7403\u4eba\u5de5\u667a\u80fd\u82af\u7247\u9886\u57df\u5b66\u8005\u5206\u5e03\u5982\u56fe\u6240\u793a\uff0c \u4ece\u56fe\u4e2d\u53ef\u4ee5\u770b\u5230\uff0c \u4eba\u5de5\u667a\u80fd\u82af\u7247\u9886\u57df\u7684\u5b66\u8005\u4e3b\u8981\u5206\u5e03\u5728\u5317\u7f8e\u6d32\uff0c\u5176\u6b21\u662f\u6b27\u6d32\u3002 \u4e2d\u56fd\u5bf9\u4eba\u5de5\u667a\u80fd\u82af\u7247\u7684\u7814\u7a76\u7d27\u8ddf\u5176\u540e\uff0c\u5357\u7f8e\u6d32\u3001\u975e\u6d32\u548c\u5927\u6d0b\u6d32\u4eba\u624d\u76f8\u5bf9\u6bd4\u8f83\u532e\u4e4f\u3002<\/p>\n

\n\t\u6309\u56fd\u5bb6\u8fdb\u884c\u7edf\u8ba1\u6765\u770b\u7f8e\u56fd\u662f\u4eba\u5de5\u667a\u80fd\u82af\u7247\u9886\u57df\u79d1\u6280\u53d1\u5c55\u7684\u6838\u5fc3\u3002 \u82f1\u56fd\u7684\u4eba\u6570\u7d27\u6392\u5728\u7f8e\u56fd\u4e4b\u540e\u3002\u5176\u4ed6\u7684\u4e13\u5bb6\u4e3b\u8981\u5206\u5e03\u5728\u4e2d\u56fd\u3001 \u5fb7\u56fd\u3001 \u52a0\u62ff\u5927\u3001\u610f\u5927\u5229\u548c\u65e5\u672c \u3002<\/p>\n

\n\t\u5bf9\u5168\u7403\u4eba\u5de5\u667a\u80fd\u82af\u7247\u9886\u57df\u6700\u5177\u5f71\u54cd\u529b\u7684 1000 \u4eba\u7684\u8fc1\u5f99\u8def\u5f84\u8fdb\u884c\u4e86\u7edf\u8ba1\u5206\u6790\uff0c\u5f97\u51fa\u4e0b\u56fe\u6240\u793a\u7684\u5404\u56fd\u4eba\u624d\u9006\u987a\u5dee\u5bf9\u6bd4\u3002<\/p>\n

\n\t<\/p>\n

\n\t\u53ef\u4ee5\u770b\u51fa\uff0c\u5404\u56fd\u4eba\u624d\u7684\u6d41\u5931\u548c\u5f15\u8fdb\u662f\u76f8\u5bf9\u6bd4\u8f83\u5747\u8861\u7684\uff0c\u5176\u4e2d\u7f8e\u56fd\u4e3a\u4eba\u624d\u6d41\u52a8\u5927\u56fd\uff0c\u4eba\u624d\u8f93\u5165\u548c\u8f93\u51fa\u5e45\u5ea6\u90fd\u5927\u5e45\u5ea6\u9886\u5148\u3002\u82f1\u56fd\u3001 \u4e2d\u56fd\u3001 \u5fb7\u56fd\u548c\u745e\u58eb\u7b49\u56fd\u6b21\u4e8e\u7f8e\u56fd\uff0c\u4f46\u5404\u56fd\u4e4b\u95f4\u4eba\u624d\u6d41\u52a8\u76f8\u5dee\u5e76\u4e0d\u660e\u663e\u3002<\/p>\n

\n\t\u4e8c\u3001AI \u82af\u7247\u7684\u5206\u7c7b\u53ca\u6280\u672f<\/p>\n

\n\t\u4eba\u5de5\u667a\u80fd\u82af\u7247\u76ee\u524d\u6709\u4e24\u79cd\u53d1\u5c55\u8def\u5f84\uff1a\u4e00\u79cd\u662f\u5ef6\u7eed\u4f20\u7edf\u8ba1\u7b97\u67b6\u6784\uff0c\u52a0\u901f\u786c\u4ef6\u8ba1\u7b97\u80fd\u529b\uff0c\u4e3b\u8981\u4ee5 3 \u79cd\u7c7b\u578b\u7684\u82af\u7247\u4e3a\u4ee3\u8868\uff0c\u5373 GPU\u3001 FPGA<\/u>\u3001 ASIC<\/u>\uff0c\u4f46 CPU\u4f9d\u65e7\u53d1\u6325\u7740\u4e0d\u53ef\u66ff\u4ee3\u7684\u4f5c\u7528\uff1b\u53e6\u4e00\u79cd\u662f\u98a0\u8986\u7ecf\u5178\u7684\u51af·\u8bfa\u4f9d\u66fc\u8ba1\u7b97\u67b6\u6784\uff0c\u91c7\u7528\u7c7b\u8111\u795e\u7ecf\u7ed3\u6784\u6765\u63d0\u5347\u8ba1\u7b97\u80fd\u529b\uff0c \u4ee5 IBM TrueNorth \u82af\u7247\u4e3a\u4ee3\u8868\u3002<\/p>\n

\n\t1\u3001\u4f20\u7edf\u7684 CPU<\/p>\n

\n\t\u8ba1\u7b97\u673a\u5de5\u4e1a\u4ece 1960 \u5e74\u4ee3\u65e9\u671f\u5f00\u59cb\u4f7f\u7528 CPU \u8fd9\u4e2a\u672f\u8bed\u3002\u8fc4\u4eca\u4e3a\u6b62\uff0c CPU \u4ece\u5f62\u6001\u3001\u8bbe\u8ba1\u5230\u5b9e\u73b0\u90fd\u5df2\u53d1\u751f\u4e86\u5de8\u5927\u7684\u53d8\u5316\uff0c\u4f46\u662f\u5176\u57fa\u672c\u5de5\u4f5c\u539f\u7406\u5374\u4e00\u76f4\u6ca1\u6709\u5927\u7684\u6539\u53d8\u3002 \u901a\u5e38 CPU \u7531\u63a7\u5236\u5668\u548c\u8fd0\u7b97\u5668\u8fd9\u4e24\u4e2a\u4e3b\u8981\u90e8\u4ef6\u7ec4\u6210\u3002 \u4f20\u7edf\u7684 CPU \u5185\u90e8\u7ed3\u6784\u56fe\u5982\u56fe 3 \u6240\u793a\uff0c \u4ece\u56fe\u4e2d\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff1a\u5b9e\u8d28\u4e0a\u4ec5\u5355\u72ec\u7684 ALU \u6a21\u5757\uff08\u903b\u8f91\u8fd0\u7b97\u5355\u5143\uff09\u662f\u7528\u6765\u5b8c\u6210\u6570\u636e\u8ba1\u7b97\u7684\uff0c\u5176\u4ed6\u5404\u4e2a\u6a21\u5757\u7684\u5b58\u5728\u90fd\u662f\u4e3a\u4e86\u4fdd\u8bc1\u6307\u4ee4\u80fd\u591f\u4e00\u6761\u63a5\u4e00\u6761\u7684\u6709\u5e8f\u6267\u884c\u3002\u8fd9\u79cd\u901a\u7528\u6027\u7ed3\u6784\u5bf9\u4e8e\u4f20\u7edf\u7684\u7f16\u7a0b\u8ba1\u7b97\u6a21\u5f0f\u975e\u5e38\u9002\u5408\uff0c\u540c\u65f6\u53ef\u4ee5\u901a\u8fc7\u63d0\u5347 CPU \u4e3b\u9891\uff08\u63d0\u5347\u5355\u4f4d\u65f6\u95f4\u5185\u6267\u884c\u6307\u4ee4\u7684\u6761\u6570\uff09\u6765\u63d0\u5347\u8ba1\u7b97\u901f\u5ea6\u3002<\/p>\n

\n\t\u4f46\u5bf9\u4e8e\u6df1\u5ea6\u5b66\u4e60\u4e2d\u7684\u5e76\u4e0d\u9700\u8981\u592a\u591a\u7684\u7a0b\u5e8f\u6307\u4ee4\u3001 \u5374\u9700\u8981\u6d77\u91cf\u6570\u636e\u8fd0\u7b97\u7684\u8ba1\u7b97\u9700\u6c42\uff0c \u8fd9\u79cd\u7ed3\u6784\u5c31\u663e\u5f97\u6709\u4e9b\u529b\u4e0d\u4ece\u5fc3\u3002\u5c24\u5176\u662f\u5728\u529f\u8017\u9650\u5236\u4e0b\uff0c \u65e0\u6cd5\u901a\u8fc7\u65e0\u9650\u5236\u7684\u63d0\u5347 CPU \u548c\u5185\u5b58\u7684\u5de5\u4f5c\u9891\u7387\u6765\u52a0\u5feb\u6307\u4ee4\u6267\u884c\u901f\u5ea6\uff0c \u8fd9\u79cd\u60c5\u51b5\u5bfc\u81f4 CPU \u7cfb\u7edf\u7684\u53d1\u5c55\u9047\u5230\u4e0d\u53ef\u903e\u8d8a\u7684\u74f6\u9888\u3002<\/p>\n

\n\t2\u3001\u5e76\u884c\u52a0\u901f\u8ba1<\/u>\u7b97\u7684 GPU<\/p>\n

\n\tGPU \u4f5c\u4e3a\u6700\u65e9\u4ece\u4e8b\u5e76\u884c\u52a0\u901f\u8ba1\u7b97\u7684\u5904\u7406\u5668\uff0c\u76f8\u6bd4 CPU \u901f\u5ea6\u5feb\uff0c \u540c\u65f6\u6bd4\u5176\u4ed6\u52a0\u901f\u5668\u82af\u7247\u7f16\u7a0b\u7075\u6d3b\u7b80\u5355\u3002<\/p>\n

\n\t\u4f20\u7edf\u7684 CPU \u4e4b\u6240\u4ee5\u4e0d\u9002\u5408\u4eba\u5de5\u667a\u80fd\u7b97\u6cd5\u7684\u6267\u884c\uff0c\u4e3b\u8981\u539f\u56e0\u5728\u4e8e\u5176\u8ba1\u7b97\u6307\u4ee4\u9075\u5faa\u4e32\u884c\u6267\u884c\u7684\u65b9\u5f0f\uff0c\u6ca1\u80fd\u53d1\u6325\u51fa\u82af\u7247\u7684\u5168\u90e8\u6f5c\u529b\u3002\u4e0e\u4e4b\u4e0d\u540c\u7684\u662f\uff0c GPU \u5177\u6709\u9ad8\u5e76\u884c\u7ed3\u6784\uff0c\u5728\u5904\u7406\u56fe\u5f62\u6570\u636e\u548c\u590d\u6742\u7b97\u6cd5\u65b9\u9762\u62e5\u6709\u6bd4 CPU \u66f4\u9ad8\u7684\u6548\u7387\u3002\u5bf9\u6bd4 GPU \u548c CPU \u5728\u7ed3\u6784\u4e0a\u7684\u5dee\u5f02\uff0c CPU\u5927\u90e8\u5206\u9762\u79ef\u4e3a\u63a7\u5236\u5668\u548c\u5bc4\u5b58\u5668<\/u>\uff0c\u800c GPU \u62e5\u6709\u66f4ALU(ARITHMETIC LOGIC UNIT\uff0c\u903b\u8f91\u8fd0\u7b97\u5355\u5143)\u7528\u4e8e\u6570\u636e\u5904\u7406\uff0c\u8fd9\u6837\u7684\u7ed3\u6784\u9002\u5408\u5bf9\u5bc6\u96c6\u578b\u6570\u636e\u8fdb\u884c\u5e76\u884c\u5904\u7406\uff0c CPU \u4e0e GPU \u7684\u7ed3\u6784\u5bf9\u6bd4\u5982\u56fe \u6240\u793a\u3002\u7a0b\u5e8f\u5728 GPU\u7cfb\u7edf\u4e0a\u7684\u8fd0\u884c\u901f\u5ea6\u76f8\u8f83\u4e8e\u5355\u6838 CPU\u5f80\u5f80\u63d0\u5347\u51e0\u5341\u500d\u4e43\u81f3\u4e0a\u5343\u500d\u3002\u968f\u7740\u82f1\u4f1f\u8fbe<\/u>\u3001 AMD<\/u> \u7b49\u516c\u53f8\u4e0d\u65ad\u63a8\u8fdb\u5176\u5bf9 GPU \u5927\u89c4\u6a21\u5e76\u884c\u67b6\u6784\u7684\u652f\u6301\uff0c\u9762\u5411\u901a\u7528\u8ba1\u7b97\u7684 GPU(\u5373GPGPU\uff0c GENERAL PURPOSE GPU\uff0c\u901a\u7528\u8ba1\u7b97\u56fe\u5f62\u5904\u7406\u5668)\u5df2\u6210\u4e3a\u52a0\u901f\u53ef\u5e76\u884c\u5e94\u7528\u7a0b\u5e8f\u7684\u91cd\u8981\u624b\u6bb5\u3002<\/p>\n

\n\tGPU \u7684\u53d1\u5c55\u5386\u7a0b\u53ef\u5206\u4e3a 3 \u4e2a\u9636\u6bb5\uff0c \u53d1\u5c55\u5386\u7a0b\u5982\u56fe\u6240\u793a\uff1a<\/p>\n

\n\t\u7b2c \u4e00 \u4ee3 GPU(1999 \u5e74 \u4ee5 \u524d ) \uff0c \u90e8 \u5206 \u529f \u80fd \u4ece CPU \u5206 \u79bb \uff0c \u5b9e \u73b0 \u786c \u4ef6 \u52a0 \u901f \uff0c \u4ee5GE(GEOMETRY ENGINE)\u4e3a\u4ee3\u8868\uff0c\u53ea\u80fd\u8d77\u5230 3D \u56fe\u50cf\u5904\u7406\u7684\u52a0\u901f\u4f5c\u7528\uff0c\u4e0d\u5177\u6709\u8f6f\u4ef6\u7f16\u7a0b\u7279\u6027\u3002<\/p>\n

\n\t\u7b2c\u4e8c\u4ee3 GPU(1999-2005 \u5e74)\uff0c \u5b9e\u73b0\u8fdb\u4e00\u6b65\u7684\u786c\u4ef6\u52a0\u901f\u548c\u6709\u9650\u7684\u7f16\u7a0b\u6027\u3002 1999 \u5e74\uff0c\u82f1\u4f1f\u8fbe\u53d1\u5e03\u4e86“\u4e13\u4e3a\u6267\u884c\u590d\u6742\u7684\u6570\u5b66\u548c\u51e0\u4f55\u8ba1\u7b97\u7684” GeForce256 \u56fe\u50cf\u5904\u7406\u82af\u7247\uff0c\u5c06\u66f4\u591a\u7684\u6676\u4f53\u7ba1<\/u>\u7528\u4f5c\u6267\u884c\u5355\u5143\uff0c \u800c\u4e0d\u662f\u50cf CPU \u90a3\u6837\u7528\u4f5c\u590d\u6742\u7684\u63a7\u5236\u5355\u5143\u548c\u7f13\u5b58\uff0c\u5c06 T&L(TRANSFORM AND LIGHTING)\u7b49\u529f\u80fd\u4ece CPU \u5206\u79bb\u51fa\u6765\uff0c\u5b9e\u73b0\u4e86\u5feb\u901f\u53d8\u6362\uff0c\u8fd9\u6210\u4e3a GPU \u771f\u6b63\u51fa\u73b0\u7684\u6807\u5fd7\u3002\u4e4b\u540e\u51e0\u5e74\uff0c GPU \u6280\u672f\u5feb\u901f\u53d1\u5c55\uff0c\u8fd0\u7b97\u901f\u5ea6\u8fc5\u901f\u8d85\u8fc7 CPU\u3002 2001 \u5e74\u82f1\u4f1f\u8fbe\u548c ATI \u5206\u522b\u63a8\u51fa\u7684GEFORCE3 \u548c RADEON 8500\uff0c\u56fe\u5f62\u786c\u4ef6\u7684\u6d41\u6c34\u7ebf\u88ab\u5b9a\u4e49\u4e3a\u6d41\u5904\u7406\u5668\uff0c\u51fa\u73b0\u4e86\u9876\u70b9\u7ea7\u53ef\u7f16\u7a0b\u6027\uff0c\u540c\u65f6\u50cf\u7d20\u7ea7\u4e5f\u5177\u6709\u6709\u9650\u7684\u7f16\u7a0b\u6027\uff0c\u4f46 GPU \u7684\u6574\u4f53\u7f16\u7a0b\u6027\u4ecd\u7136\u6bd4\u8f83\u6709\u9650\u3002<\/p>\n

\n\t\u7b2c\u4e09\u4ee3 GPU(2006\u5e74\u4ee5\u540e)\uff0c GPU\u5b9e\u73b0\u65b9\u4fbf\u7684\u7f16\u7a0b\u73af\u5883\u521b\u5efa\uff0c \u53ef\u4ee5\u76f4\u63a5\u7f16\u5199\u7a0b\u5e8f\u3002 2006\u5e74\u82f1\u4f1f\u8fbe\u4e0e ATI\u5206\u522b\u63a8\u51fa\u4e86 CUDA(Compute<\/u> United Device Architecture\uff0c\u8ba1\u7b97\u7edf\u4e00\u8bbe\u5907\u67b6\u6784)\u7f16\u7a0b\u73af\u5883\u548c CTM(CLOSE TO THE METAL)\u7f16\u7a0b\u73af\u5883\uff0c \u4f7f\u5f97 GPU \u6253\u7834\u56fe\u5f62\u8bed\u8a00\u7684\u5c40\u9650\u6210\u4e3a\u771f\u6b63\u7684\u5e76\u884c\u6570\u636e\u5904\u7406\u8d85\u7ea7\u52a0\u901f\u5668\u3002<\/p>\n

\n\t2008 \u5e74\uff0c\u82f9\u679c\u516c\u53f8\u63d0\u51fa\u4e00\u4e2a\u901a\u7528\u7684\u5e76\u884c\u8ba1\u7b97\u7f16\u7a0b\u5e73\u53f0 OPENCL\uff08OPEN COMPUTING LANGUAGE\uff0c\u5f00\u653e\u8fd0\u7b97\u8bed\u8a00\uff09\uff0c\u4e0e CUDA \u7ed1\u5b9a\u5728\u82f1\u4f1f\u8fbe\u7684\u663e\u5361\u4e0a\u4e0d\u540c\uff0cOPENCL \u548c\u5177\u4f53\u7684\u8ba1\u7b97\u8bbe\u5907\u65e0\u5173\u3002<\/p>\n

\n\t\u76ee\u524d\uff0c GPU \u5df2\u7ecf\u53d1\u5c55\u5230\u8f83\u4e3a\u6210\u719f\u7684\u9636\u6bb5\u3002\u8c37\u6b4c\u3001 FACEBOOK\u3001\u5fae\u8f6f\u3001 TWITTER \u548c\u767e\u5ea6\u7b49\u516c\u53f8\u90fd\u5728\u4f7f\u7528 GPU \u5206\u6790\u56fe\u7247\u3001\u89c6\u9891\u548c\u97f3\u9891\u6587\u4ef6\uff0c\u4ee5\u6539\u8fdb\u641c\u7d22\u548c\u56fe\u50cf\u6807\u7b7e\u7b49\u5e94\u7528\u529f\u80fd\u3002\u6b64\u5916\uff0c\u5f88\u591a\u6c7d\u8f66\u751f\u4ea7\u5546\u4e5f\u5728\u4f7f\u7528 GPU \u82af\u7247\u53d1\u5c55\u65e0\u4eba\u9a7e\u9a76\u3002 \u4e0d\u4ec5\u5982\u6b64\uff0c GPU \u4e5f\u88ab\u5e94\u7528\u4e8eVR\/AR \u76f8\u5173\u7684\u4ea7\u4e1a\u3002<\/p>\n

\n\t\u4f46\u662f GPU\u4e5f\u6709\u4e00\u5b9a\u7684\u5c40\u9650\u6027\u3002 \u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\u5206\u4e3a\u8bad\u7ec3\u548c\u63a8\u65ad\u4e24\u90e8\u5206\uff0c GPU \u5e73\u53f0\u5728\u7b97\u6cd5\u8bad\u7ec3\u4e0a\u975e\u5e38\u9ad8\u6548\u3002\u4f46\u5728\u63a8\u65ad\u4e2d\u5bf9\u4e8e\u5355\u9879\u8f93\u5165\u8fdb\u884c\u5904\u7406\u7684\u65f6\u5019\uff0c\u5e76\u884c\u8ba1\u7b97\u7684\u4f18\u52bf\u4e0d\u80fd\u5b8c\u5168\u53d1\u6325\u51fa\u6765\u3002<\/p>\n

\n\t3\u3001\u534a\u5b9a\u5236\u5316\u7684 FPGA<\/p>\n

\n\tFPGA \u662f\u5728 PAL\u3001 GAL\u3001 CPLD<\/u> \u7b49\u53ef\u7f16\u7a0b\u5668\u4ef6\u57fa\u7840\u4e0a\u8fdb\u4e00\u6b65\u53d1\u5c55\u7684\u4ea7\u7269\u3002\u7528\u6237\u53ef\u4ee5\u901a\u8fc7\u70e7\u5165 FPGA \u914d\u7f6e\u6587\u4ef6\u6765\u5b9a\u4e49\u8fd9\u4e9b\u95e8\u7535\u8def\u4ee5\u53ca\u5b58\u50a8\u5668\u4e4b\u95f4\u7684\u8fde\u7ebf\u3002\u8fd9\u79cd\u70e7\u5165\u4e0d\u662f\u4e00\u6b21\u6027\u7684\uff0c\u6bd4\u5982\u7528\u6237\u53ef\u4ee5\u628a FPGA \u914d\u7f6e\u6210\u4e00\u4e2a\u5fae\u63a7\u5236\u5668 MCU<\/u>\uff0c\u4f7f\u7528\u5b8c\u6bd5\u540e\u53ef\u4ee5\u7f16\u8f91\u914d\u7f6e\u6587\u4ef6\u628a\u540c\u4e00\u4e2aFPGA \u914d\u7f6e\u6210\u4e00\u4e2a\u97f3\u9891\u7f16\u89e3\u7801\u5668<\/u>\u3002\u56e0\u6b64\uff0c \u5b83\u65e2\u89e3\u51b3\u4e86\u5b9a\u5236\u7535\u8def\u7075\u6d3b\u6027\u7684\u4e0d\u8db3\uff0c\u53c8\u514b\u670d\u4e86\u539f\u6709\u53ef\u7f16\u7a0b\u5668\u4ef6\u95e8\u7535\u8def\u6570\u6709\u9650\u7684\u7f3a\u70b9\u3002<\/p>\n

\n\tFPGA \u53ef\u540c\u65f6\u8fdb\u884c\u6570\u636e\u5e76\u884c\u548c\u4efb\u52a1\u5e76\u884c\u8ba1\u7b97\uff0c\u5728\u5904\u7406\u7279\u5b9a\u5e94\u7528\u65f6\u6709\u66f4\u52a0\u660e\u663e\u7684\u6548\u7387\u63d0\u5347\u3002\u5bf9\u4e8e\u67d0\u4e2a\u7279\u5b9a\u8fd0\u7b97\uff0c\u901a\u7528 CPU \u53ef\u80fd\u9700\u8981\u591a\u4e2a\u65f6\u949f<\/u>\u5468\u671f\uff1b \u800c FPGA \u53ef\u4ee5\u901a\u8fc7\u7f16\u7a0b\u91cd\u7ec4\u7535\u8def\uff0c\u76f4\u63a5\u751f\u6210\u4e13\u7528\u7535\u8def\uff0c\u4ec5\u6d88\u8017\u5c11\u91cf\u751a\u81f3\u4e00\u6b21\u65f6\u949f\u5468\u671f\u5c31\u53ef\u5b8c\u6210\u8fd0\u7b97\u3002<\/p>\n

\n\t\u6b64\u5916\uff0c\u7531\u4e8e FPGA\u7684\u7075\u6d3b\u6027\uff0c\u5f88\u591a\u4f7f\u7528\u901a\u7528\u5904\u7406\u5668\u6216 ASIC\u96be\u4ee5\u5b9e\u73b0\u7684\u5e95\u5c42\u786c\u4ef6\u63a7\u5236\u64cd\u4f5c\u6280\u672f\uff0c \u5229\u7528 FPGA \u53ef\u4ee5\u5f88\u65b9\u4fbf\u7684\u5b9e\u73b0\u3002\u8fd9\u4e2a\u7279\u6027\u4e3a\u7b97\u6cd5\u7684\u529f\u80fd\u5b9e\u73b0\u548c\u4f18\u5316\u7559\u51fa\u4e86\u66f4\u5927\u7a7a\u95f4\u3002\u540c\u65f6 FPGA \u4e00\u6b21\u6027\u6210\u672c(\u5149\u523b\u63a9\u6a21\u5236\u4f5c\u6210\u672c)\u8fdc\u4f4e\u4e8e ASIC\uff0c\u5728\u82af\u7247\u9700\u6c42\u8fd8\u672a\u6210\u89c4\u6a21\u3001\u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\u6682\u672a\u7a33\u5b9a\uff0c \u9700\u8981\u4e0d\u65ad\u8fed\u4ee3\u6539\u8fdb\u7684\u60c5\u51b5\u4e0b\uff0c\u5229\u7528 FPGA \u82af\u7247\u5177\u5907\u53ef\u91cd\u6784\u7684\u7279\u6027\u6765\u5b9e\u73b0\u534a\u5b9a\u5236\u7684\u4eba\u5de5\u667a\u80fd\u82af\u7247\u662f\u6700\u4f73\u9009\u62e9\u4e4b\u4e00\u3002<\/p>\n

\n\t\u529f\u8017\u65b9\u9762\uff0c\u4ece\u4f53\u7cfb\u7ed3\u6784\u800c\u8a00\uff0c FPGA \u4e5f\u5177\u6709\u5929\u751f\u7684\u4f18\u52bf\u3002\u4f20\u7edf\u7684\u51af\u6c0f\u7ed3\u6784\u4e2d\uff0c\u6267\u884c\u5355\u5143\uff08\u5982 CPU \u6838\uff09\u6267\u884c\u4efb\u610f\u6307\u4ee4\uff0c\u90fd\u9700\u8981\u6709\u6307\u4ee4\u5b58\u50a8\u5668\u3001\u8bd1\u7801\u5668\u3001\u5404\u79cd\u6307\u4ee4\u7684\u8fd0\u7b97\u5668\u53ca\u5206\u652f\u8df3\u8f6c\u5904\u7406\u903b\u8f91\u53c2\u4e0e\u8fd0\u884c\uff0c \u800c FPGA \u6bcf\u4e2a\u903b\u8f91\u5355\u5143\u7684\u529f\u80fd\u5728\u91cd\u7f16\u7a0b\uff08\u5373\u70e7\u5165\uff09\u65f6\u5c31\u5df2\u7ecf\u786e\u5b9a\uff0c\u4e0d\u9700\u8981\u6307\u4ee4\uff0c\u65e0\u9700\u5171\u4eab\u5185\u5b58\uff0c\u4ece\u800c\u53ef\u4ee5\u6781\u5927\u7684\u964d\u4f4e\u5355\u4f4d\u6267\u884c\u7684\u529f\u8017\uff0c\u63d0\u9ad8\u6574\u4f53\u7684\u80fd\u8017\u6bd4\u3002<\/p>\n

\n\t\u7531\u4e8e FPGA \u5177\u5907\u7075\u6d3b\u5feb\u901f\u7684\u7279\u70b9\uff0c \u56e0\u6b64\u5728\u4f17\u591a\u9886\u57df\u90fd\u6709\u66ff\u4ee3 ASIC \u7684\u8d8b\u52bf\u3002 FPGA \u5728\u4eba\u5de5\u667a\u80fd\u9886\u57df\u7684\u5e94\u7528\u5982\u56fe\u6240\u793a\u3002<\/p>\n

\n\t4\u3001\u5168\u5b9a\u5236\u5316\u7684 ASIC<\/p>\n

\n\t\u76ee\u524d\u4ee5\u6df1\u5ea6\u5b66\u4e60\u4e3a\u4ee3\u8868\u7684\u4eba\u5de5\u667a\u80fd\u8ba1\u7b97\u9700\u6c42\uff0c\u4e3b\u8981\u91c7\u7528 GPU\u3001 FPGA \u7b49\u5df2\u6709\u7684\u9002\u5408\u5e76\u884c\u8ba1\u7b97\u7684\u901a\u7528\u82af\u7247\u6765\u5b9e\u73b0\u52a0\u901f\u3002\u5728\u4ea7\u4e1a\u5e94\u7528\u6ca1\u6709\u5927\u89c4\u6a21\u5174\u8d77\u4e4b\u65f6\uff0c\u4f7f\u7528\u8fd9\u7c7b\u5df2\u6709\u7684\u901a\u7528\u82af\u7247\u53ef\u4ee5\u907f\u514d\u4e13\u95e8\u7814\u53d1\u5b9a\u5236\u82af\u7247\uff08ASIC\uff09 \u7684\u9ad8\u6295\u5165\u548c\u9ad8\u98ce\u9669\u3002\u4f46\u662f\uff0c\u7531\u4e8e\u8fd9\u7c7b\u901a\u7528\u82af\u7247\u8bbe\u8ba1\u521d\u8877\u5e76\u975e\u4e13\u95e8\u9488\u5bf9\u6df1\u5ea6\u5b66\u4e60\uff0c\u56e0\u800c\u5929\u7136\u5b58\u5728\u6027\u80fd\u3001 \u529f\u8017\u7b49\u65b9\u9762\u7684\u5c40\u9650\u6027\u3002\u968f\u7740\u4eba\u5de5\u667a\u80fd\u5e94\u7528\u89c4\u6a21\u7684\u6269\u5927\uff0c\u8fd9\u7c7b\u95ee\u9898\u65e5\u76ca\u7a81\u663e\u3002<\/p>\n

\n\tGPU \u4f5c\u4e3a\u56fe\u50cf\u5904\u7406\u5668\uff0c \u8bbe\u8ba1\u521d\u8877\u662f\u4e3a\u4e86\u5e94\u5bf9\u56fe\u50cf\u5904\u7406\u4e2d\u7684\u5927\u89c4\u6a21\u5e76\u884c\u8ba1\u7b97\u3002\u56e0\u6b64\uff0c\u5728\u5e94\u7528\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\u65f6\uff0c\u6709\u4e09\u4e2a\u65b9\u9762\u7684\u5c40\u9650\u6027\uff1a<\/p>\n

\n\t\u7b2c\u4e00\uff0c\u5e94\u7528\u8fc7\u7a0b\u4e2d\u65e0\u6cd5\u5145\u5206\u53d1\u6325\u5e76\u884c\u8ba1\u7b97\u4f18\u52bf\u3002 \u6df1\u5ea6\u5b66\u4e60\u5305\u542b\u8bad\u7ec3\u548c\u63a8\u65ad\u4e24\u4e2a\u8ba1\u7b97\u73af\u8282\uff0c GPU \u5728\u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\u8bad\u7ec3\u4e0a\u975e\u5e38\u9ad8\u6548\uff0c \u4f46\u5bf9\u4e8e\u5355\u4e00\u8f93\u5165\u8fdb\u884c\u63a8\u65ad\u7684\u573a\u5408\uff0c \u5e76\u884c\u5ea6\u7684\u4f18\u52bf\u4e0d\u80fd\u5b8c\u5168\u53d1\u6325\u3002<\/p>\n

\n\t\u7b2c\u4e8c\uff0c \u65e0\u6cd5\u7075\u6d3b\u914d\u7f6e\u786c\u4ef6\u7ed3\u6784\u3002 GPU \u91c7\u7528 SIMT \u8ba1\u7b97\u6a21\u5f0f\uff0c \u786c\u4ef6\u7ed3\u6784\u76f8\u5bf9\u56fa\u5b9a\u3002 <\/p>\n

\n\t\u76ee\u524d\u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\u8fd8\u672a\u5b8c\u5168\u7a33\u5b9a\uff0c\u82e5\u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\u53d1\u751f\u5927\u7684\u53d8\u5316\uff0c GPU \u65e0\u6cd5\u50cf FPGA \u4e00\u6837\u53ef\u4ee5\u7075\u6d3b\u7684\u914d\u5236\u786c\u4ef6\u7ed3\u6784\u3002 \u7b2c\u4e09\uff0c\u8fd0\u884c\u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\u80fd\u6548\u4f4e\u4e8e FPGA\u3002<\/p>\n

\n\t\u5c3d\u7ba1 FPGA \u500d\u53d7\u770b\u597d\uff0c\u751a\u81f3\u65b0\u4e00\u4ee3\u767e\u5ea6\u5927\u8111\u4e5f\u662f\u57fa\u4e8e FPGA \u5e73\u53f0\u7814\u53d1\uff0c\u4f46\u5176\u6bd5\u7adf\u4e0d\u662f\u4e13\u95e8\u4e3a\u4e86\u9002\u7528\u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\u800c\u7814\u53d1\uff0c\u5b9e\u9645\u5e94\u7528\u4e2d\u4e5f\u5b58\u5728\u8bf8\u591a\u5c40\u9650\uff1a<\/p>\n

\n\t\u7b2c\u4e00\uff0c\u57fa\u672c\u5355\u5143\u7684\u8ba1\u7b97\u80fd\u529b\u6709\u9650\u3002\u4e3a\u4e86\u5b9e\u73b0\u53ef\u91cd\u6784\u7279\u6027\uff0c FPGA \u5185\u90e8\u6709\u5927\u91cf\u6781\u7ec6\u7c92\u5ea6\u7684\u57fa\u672c\u5355\u5143\uff0c\u4f46\u662f\u6bcf\u4e2a\u5355\u5143\u7684\u8ba1\u7b97\u80fd\u529b(\u4e3b\u8981\u4f9d\u9760 LUT \u67e5\u627e\u8868)\u90fd\u8fdc\u8fdc\u4f4e\u4e8e CPU \u548c GPU \u4e2d\u7684 ALU \u6a21\u5757\uff1b <\/p>\n

\n\t\u7b2c\u4e8c\u3001 \u8ba1\u7b97\u8d44\u6e90\u5360\u6bd4\u76f8\u5bf9\u8f83\u4f4e\u3002 \u4e3a\u5b9e\u73b0\u53ef\u91cd\u6784\u7279\u6027\uff0c FPGA \u5185\u90e8\u5927\u91cf\u8d44\u6e90\u88ab\u7528\u4e8e\u53ef\u914d\u7f6e\u7684\u7247\u4e0a\u8def\u7531\u4e0e\u8fde\u7ebf\uff1b<\/p>\n

\n\t\u7b2c\u4e09\uff0c\u901f\u5ea6\u548c\u529f\u8017\u76f8\u5bf9\u4e13\u7528\u5b9a\u5236\u82af\u7247(ASIC)\u4ecd\u7136\u5b58\u5728\u4e0d\u5c0f\u5dee\u8ddd\uff1b<\/p>\n

\n\t\u7b2c\u56db\uff0c FPGA \u4ef7\u683c\u8f83\u4e3a\u6602\u8d35\uff0c\u5728\u89c4\u6a21\u653e\u91cf\u7684\u60c5\u51b5\u4e0b\u5355\u5757 FPGA \u7684\u6210\u672c\u8981\u8fdc\u9ad8\u4e8e\u4e13\u7528\u5b9a\u5236\u82af\u7247\u3002<\/p>\n

\n\t\u56e0\u6b64\uff0c\u968f\u7740\u4eba\u5de5\u667a\u80fd\u7b97\u6cd5\u548c\u5e94\u7528\u6280\u672f\u7684\u65e5\u76ca\u53d1\u5c55\uff0c\u4ee5\u53ca\u4eba\u5de5\u667a\u80fd\u4e13\u7528\u82af\u7247 ASIC\u4ea7\u4e1a\u73af\u5883\u7684\u9010\u6e10\u6210\u719f\uff0c \u5168\u5b9a\u5236\u5316\u4eba\u5de5\u667a\u80fd ASIC\u4e5f\u9010\u6b65\u4f53\u73b0\u51fa\u81ea\u8eab\u7684\u4f18\u52bf\uff0c\u4ece\u4e8b\u6b64\u7c7b\u82af\u7247\u7814\u53d1\u4e0e\u5e94\u7528\u7684\u56fd\u5185\u5916\u6bd4\u8f83\u6709\u4ee3\u8868\u6027\u7684\u516c\u53f8\u5982\u56fe\u6240\u793a\u3002<\/p>\n

\n\t\u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\u7a33\u5b9a\u540e\uff0c AI \u82af\u7247\u53ef\u91c7\u7528 ASIC \u8bbe\u8ba1\u65b9\u6cd5\u8fdb\u884c\u5168\u5b9a\u5236\uff0c \u4f7f\u6027\u80fd\u3001\u529f\u8017\u548c\u9762\u79ef\u7b49\u6307\u6807\u9762\u5411\u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\u505a\u5230\u6700\u4f18\u3002<\/p>\n

\n\t5\u3001\u7c7b\u8111\u82af\u7247<\/p>\n

\n\t\u7c7b\u8111\u82af\u7247\u4e0d\u91c7\u7528\u7ecf\u5178\u7684\u51af·\u8bfa\u4f9d\u66fc\u67b6\u6784\uff0c \u800c\u662f\u57fa\u4e8e\u795e\u7ecf\u5f62\u6001\u67b6\u6784\u8bbe\u8ba1\uff0c\u4ee5 IBM Truenorth\u4e3a\u4ee3\u8868\u3002 IBM \u7814\u7a76\u4eba\u5458\u5c06\u5b58\u50a8\u5355\u5143\u4f5c\u4e3a\u7a81\u89e6\u3001\u8ba1\u7b97\u5355\u5143\u4f5c\u4e3a\u795e\u7ecf\u5143\u3001\u4f20\u8f93\u5355\u5143\u4f5c\u4e3a\u8f74\u7a81\u642d\u5efa\u4e86\u795e\u7ecf\u82af\u7247\u7684\u539f\u578b\u3002<\/p>\n

\n\t\u76ee\u524d\uff0c Truenorth \u7528\u4e09\u661f<\/u> 28nm \u529f\u8017\u5de5\u827a\u6280\u672f\uff0c\u7531 54 \u4ebf\u4e2a\u6676\u4f53\u7ba1\u7ec4\u6210\u7684\u82af\u7247\u6784\u6210\u7684\u7247\u4e0a\u7f51\u7edc\u6709 4096 \u4e2a\u795e\u7ecf\u7a81\u89e6\u6838\u5fc3\uff0c\u5b9e\u65f6\u4f5c\u4e1a\u529f\u8017\u4ec5\u4e3a 70mW\u3002\u7531\u4e8e\u795e\u7ecf\u7a81\u89e6\u8981\u6c42\u6743\u91cd\u53ef\u53d8\u4e14\u8981\u6709\u8bb0\u5fc6\u529f\u80fd\uff0c IBM \u91c7\u7528\u4e0e CMOS \u5de5\u827a\u517c\u5bb9\u7684\u76f8\u53d8\u975e\u6325\u53d1\u5b58\u50a8\u5668\uff08PCM\uff09\u7684\u6280\u672f\u5b9e\u9a8c\u6027\u7684\u5b9e\u73b0\u4e86\u65b0\u578b\u7a81\u89e6\uff0c\u52a0\u5feb\u4e86\u5546\u4e1a\u5316\u8fdb\u7a0b\u3002<\/p>\n

\n\t\u4e09\u3001AI\u82af\u7247\u4ea7\u4e1a\u53ca\u8d8b\u52bf<\/p>\n

\n\t<\/p>\n

\n\t1\u3001AI\u82af\u7247\u5e94\u7528\u9886\u57df<\/p>\n

\n\t\u968f\u7740\u4eba\u5de5\u667a\u80fd\u82af\u7247\u7684\u6301\u7eed\u53d1\u5c55\uff0c\u5e94\u7528\u9886\u57df\u4f1a\u968f\u65f6\u95f4\u63a8\u79fb\u800c\u4e0d\u65ad\u5411\u591a\u7ef4\u65b9\u5411\u53d1\u5c55\uff0c\u8fd9\u91cc\u6211\u4eec\u9009\u62e9\u76ee\u524d\u53d1\u5c55\u6bd4\u8f83\u96c6\u4e2d\u7684\u51e0\u4e2a\u884c\u4e1a\u505a\u76f8\u5173\u7684\u4ecb\u7ecd\u3002<\/p>\n

\n\tAI\u82af\u7247\u76ee\u524d\u6bd4\u8f83\u96c6\u4e2d\u7684\u5e94\u7528\u9886\u57df<\/p>\n

\n\t\uff081\uff09\u667a\u80fd\u624b\u673a<\/p>\n

\n\t2017 \u5e74 9 \u6708\uff0c\u534e\u4e3a<\/u>\u5728\u5fb7\u56fd\u67cf\u6797\u6d88\u8d39\u7535\u5b50\u5c55\u53d1\u5e03\u4e86\u9e92\u9e9f 970 \u82af\u7247\uff0c\u8be5\u82af\u7247\u642d\u8f7d\u4e86\u5bd2\u6b66\u7eaa\u7684 NPU\uff0c\u6210\u4e3a“\u5168\u7403\u9996\u6b3e\u667a\u80fd\u624b\u673a\u79fb\u52a8\u7aef AI \u82af\u7247” \uff1b 2017 \u5e74 10 \u6708\u4e2d\u65ec Mate10 \u7cfb\u5217\u65b0\u54c1\uff08\u8be5\u7cfb\u5217\u624b\u673a\u7684\u5904\u7406\u5668\u4e3a\u9e92\u9e9f 970\uff09\u4e0a\u5e02\u3002\u642d\u8f7d\u4e86 NPU \u7684\u534e\u4e3a Mate10 \u7cfb\u5217\u667a\u80fd\u624b\u673a\u5177\u5907\u4e86\u8f83\u5f3a\u7684\u6df1\u5ea6\u5b66\u4e60\u3001\u672c\u5730\u7aef\u63a8\u65ad\u80fd\u529b\uff0c\u8ba9\u5404\u7c7b\u57fa\u4e8e\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u7684\u6444\u5f71\u3001\u56fe\u50cf\u5904\u7406\u5e94\u7528\u80fd\u591f\u4e3a\u7528\u6237\u63d0\u4f9b\u66f4\u52a0\u5b8c\u7f8e\u7684\u4f53\u9a8c\u3002<\/p>\n

\n\t\u800c\u82f9\u679c\u53d1\u5e03\u4ee5 iPhone X \u4e3a\u4ee3\u8868\u7684\u624b\u673a\u53ca\u5b83\u4eec\u5185\u7f6e\u7684 A11 Bionic \u82af\u7247\u3002A11 Bionic \u4e2d\u81ea\u4e3b\u7814\u53d1\u7684\u53cc\u6838\u67b6\u6784 Neural Engine\uff08\u795e\u7ecf\u7f51\u7edc\u5904\u7406\u5f15\u64ce\uff09\uff0c\u5b83\u6bcf\u79d2\u5904\u7406\u76f8\u5e94\u795e\u7ecf\u7f51\u7edc\u8ba1\u7b97\u9700\u6c42\u7684\u6b21\u6570\u53ef\u8fbe 6000 \u4ebf\u6b21\u3002\u8fd9\u4e2a Neural Engine \u7684\u51fa\u73b0\uff0c\u8ba9 A11 Bionic \u6210\u4e3a\u4e00\u5757\u771f\u6b63\u7684 AI \u82af\u7247\u3002 A11 Bionic \u5927\u5927\u63d0\u5347\u4e86 iPhone X \u5728\u62cd\u7167\u65b9\u9762\u7684\u4f7f\u7528\u4f53\u9a8c\uff0c\u5e76\u63d0\u4f9b\u4e86\u4e00\u4e9b\u5bcc\u6709\u521b\u610f\u7684\u65b0\u7528\u6cd5\u3002<\/p>\n

\n\t\uff082\uff09ADAS\uff08\u9ad8\u7ea7\u8f85\u52a9\u9a7e\u9a76\u7cfb\u7edf\uff09<\/p>\n

\n\tADAS \u662f\u6700\u5438\u5f15\u5927\u4f17\u773c\u7403\u7684\u4eba\u5de5\u667a\u80fd\u5e94\u7528\u4e4b\u4e00\uff0c \u5b83\u9700\u8981\u5904\u7406\u6d77\u91cf\u7684\u7531\u6fc0\u5149\u96f7\u8fbe\u3001\u6beb\u7c73\u6ce2\u96f7\u8fbe\u3001\u6444\u50cf\u5934\u7b49\u4f20\u611f\u5668<\/u>\u91c7\u96c6\u7684\u5b9e\u65f6\u6570\u636e\u3002\u76f8\u5bf9\u4e8e\u4f20\u7edf\u7684\u8f66\u8f86\u63a7\u5236\u65b9\u6cd5\uff0c\u667a\u80fd\u63a7\u5236\u65b9\u6cd5\u4e3b\u8981\u4f53\u73b0\u5728\u5bf9\u63a7\u5236\u5bf9\u8c61\u6a21\u578b\u7684\u8fd0\u7528\u548c\u7efc\u5408\u4fe1\u606f\u5b66\u4e60\u8fd0\u7528\u4e0a\uff0c\u5305\u62ec\u795e\u7ecf\u7f51\u7edc\u63a7\u5236\u548c\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\u7b49\uff0c\u5f97\u76ca\u4e8e AI \u82af\u7247\u7684\u98de\u901f\u53d1\u5c55\uff0c \u8fd9\u4e9b\u7b97\u6cd5\u5df2\u9010\u6b65\u5728\u8f66\u8f86\u63a7\u5236\u4e2d\u5f97\u5230\u5e94\u7528\u3002<\/p>\n

\n\t\uff083\uff09CV\uff08\u8ba1\u7b97\u673a\u89c6\u89c9\uff08Computer Vision\uff09 \u8bbe\u5907<\/p>\n

\n\t\u9700\u8981\u4f7f\u7528\u8ba1\u7b97\u673a\u89c6\u89c9\u6280\u672f\u7684\u8bbe\u5907\uff0c\u5982\u667a\u80fd\u6444\u50cf\u5934\u3001\u65e0\u4eba\u673a<\/u>\u3001 \u884c\u8f66\u8bb0\u5f55\u4eea\u3001\u4eba\u8138\u8bc6\u522b\u8fce\u5bbe\u673a\u5668\u4eba\u4ee5\u53ca\u667a\u80fd\u624b\u5199\u677f\u7b49\u8bbe\u5907\uff0c \u5f80\u5f80\u90fd\u5177\u6709\u672c\u5730\u7aef\u63a8\u65ad\u7684\u9700\u8981\uff0c\u5982\u679c\u4ec5\u80fd\u5728\u8054\u7f51\u4e0b\u5de5\u4f5c\uff0c\u65e0\u7591\u5c06\u5e26\u6765\u7cdf\u7cd5\u7684\u4f53\u9a8c\u3002\u800c\u8ba1\u7b97\u673a\u89c6\u89c9\u6280\u672f\u76ee\u524d\u770b\u6765\u5c06\u4f1a\u6210\u4e3a\u4eba\u5de5\u667a\u80fd\u5e94\u7528\u7684\u6c83\u571f\u4e4b\u4e00\uff0c\u8ba1\u7b97\u673a\u89c6\u89c9\u82af\u7247\u5c06\u62e5\u6709\u5e7f\u9614\u7684\u5e02\u573a\u524d\u666f\u3002<\/p>\n

\n\t\uff084\uff09 VR \u8bbe\u5907<\/p>\n

\n\tVR \u8bbe\u5907\u82af\u7247\u7684\u4ee3\u8868\u4e3a HPU \u82af\u7247\uff0c \u662f\u5fae\u8f6f\u4e3a\u81ea\u8eab VR \u8bbe\u5907 Hololens \u7814\u53d1\u5b9a\u5236\u7684\u3002 \u8fd9\u9897\u7531\u53f0\u79ef\u7535\u4ee3\u5de5\u7684\u82af\u7247\u80fd\u540c\u65f6\u5904\u7406\u6765\u81ea 5\u4e2a\u6444\u50cf\u5934\u3001 1\u4e2a\u6df1\u5ea6\u4f20\u611f\u5668\u4ee5\u53ca\u8fd0\u52a8\u4f20\u611f\u5668\u7684\u6570\u636e\uff0c\u5e76\u5177\u5907\u8ba1\u7b97\u673a\u89c6\u89c9\u7684\u77e9\u9635\u8fd0\u7b97\u548c CNN \u8fd0\u7b97\u7684\u52a0\u901f\u529f\u80fd\u3002\u8fd9\u4f7f\u5f97 VR \u8bbe\u5907\u53ef\u91cd\u5efa\u9ad8\u8d28\u91cf\u7684\u4eba\u50cf 3D \u5f71\u50cf\uff0c\u5e76\u5b9e\u65f6\u4f20\u9001\u5230\u4efb\u4f55\u5730\u65b9\u3002<\/p>\n

\n\t\uff085\uff09\u8bed\u97f3\u4ea4\u4e92\u8bbe\u5907<\/p>\n

\n\t\u8bed\u97f3\u4ea4\u4e92\u8bbe\u5907\u82af\u7247\u65b9\u9762\uff0c\u56fd\u5185\u6709\u542f\u82f1\u6cf0\u4f26\u4ee5\u53ca\u4e91\u77e5\u58f0\u4e24\u5bb6\u516c\u53f8\uff0c\u5176\u63d0\u4f9b\u7684\u82af\u7247\u65b9\u6848\u5747\u5185\u7f6e\u4e86\u4e3a\u8bed\u97f3\u8bc6\u522b<\/u>\u800c\u4f18\u5316\u7684\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u52a0\u901f\u65b9\u6848\uff0c\u5b9e\u73b0\u8bbe\u5907\u7684\u8bed\u97f3\u79bb\u7ebf\u8bc6\u522b\u3002\u7a33\u5b9a\u7684\u8bc6\u522b\u80fd\u529b\u4e3a\u8bed\u97f3\u6280\u672f\u7684\u843d\u5730\u63d0\u4f9b\u4e86\u53ef\u80fd\uff1b \u4e0e\u6b64\u540c\u65f6\uff0c\u8bed\u97f3\u4ea4\u4e92\u7684\u6838\u5fc3\u73af\u8282\u4e5f\u53d6\u5f97\u91cd\u5927\u7a81\u7834\u3002\u8bed\u97f3\u8bc6\u522b\u73af\u8282\u7a81\u7834\u4e86\u5355\u70b9\u80fd\u529b\uff0c\u4ece\u8fdc\u573a\u8bc6\u522b\uff0c\u5230\u8bed\u97f3\u5206\u6790\u548c\u8bed\u4e49\u7406\u89e3\u6709\u4e86\u91cd\u5927\u7a81\u7834\uff0c\u5448\u73b0\u51fa\u4e00\u79cd\u6574\u4f53\u7684\u4ea4\u4e92\u65b9\u6848\u3002<\/p>\n

\n\t\uff086\uff09\u673a\u5668\u4eba<\/p>\n

\n\t\u65e0\u8bba\u662f\u5bb6\u5c45\u673a\u5668\u4eba\u8fd8\u662f\u5546\u7528\u670d\u52a1\u673a\u5668\u4eba\u5747\u9700\u8981\u4e13\u7528\u8f6f\u4ef6+\u82af\u7247\u7684\u4eba\u5de5\u667a\u80fd\u89e3\u51b3\u65b9\u6848\uff0c\u8fd9\u65b9\u9762\u5178\u578b\u516c\u53f8\u6709\u7531\u524d\u767e\u5ea6\u6df1\u5ea6\u5b66\u4e60\u5b9e\u9a8c\u5ba4\u8d1f\u8d23\u4eba\u4f59\u51ef\u521b\u529e\u7684\u5730\u5e73\u7ebf\u673a\u5668\u4eba\uff0c\u5f53\u7136\u5730\u5e73\u7ebf\u673a\u5668\u4eba\u9664\u6b64\u4e4b\u5916\uff0c\u8fd8\u63d0\u4f9b ADAS\u3001\u667a\u80fd\u5bb6\u5c45\u7b49\u5176\u4ed6\u5d4c\u5165\u5f0f\u4eba\u5de5\u667a\u80fd\u89e3\u51b3\u65b9\u6848\u3002<\/p>\n

\n\t2\u3001AI\u82af\u7247\u56fd\u5185\u5916\u4ee3\u8868\u6027\u4f01\u4e1a<\/p>\n

\n\t<\/p>\n

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\n\t\u4e2d\u79d1\u5bd2\u6b66\u7eaa<\/p>\n

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\n\t\u5bd2\u6b66\u7eaa\u662f\u5168\u7403\u7b2c\u4e00\u4e2a\u6210\u529f\u6d41\u7247\u5e76\u62e5\u6709\u6210\u719f\u4ea7\u54c1\u7684 AI \u82af\u7247\u516c\u53f8\uff0c\u62e5\u6709\u7ec8\u7aef AI \u5904\u7406\u5668 IP\u548c\u4e91\u7aef\u9ad8\u6027\u80fd AI \u82af\u7247\u4e24\u6761\u4ea7\u54c1\u7ebf\u3002 2016 \u5e74\u53d1\u5e03\u7684\u5bd2\u6b66\u7eaa 1A \u5904\u7406\u5668\uff08Cambricon-1A\uff09 \u662f\u4e16\u754c\u9996\u6b3e\u5546\u7528\u6df1\u5ea6\u5b66\u4e60\u4e13\u7528\u5904\u7406\u5668\uff0c\u9762\u5411\u667a\u80fd\u624b\u673a\u3001\u5b89\u9632\u76d1\u63a7\u3001\u65e0\u4eba\u673a\u3001\u53ef\u7a7f\u6234\u8bbe\u5907\u4ee5\u53ca\u667a\u80fd\u9a7e\u9a76\u7b49\u5404\u7c7b\u7ec8\u7aef\u8bbe\u5907\uff0c\u5728\u8fd0\u884c\u4e3b\u6d41\u667a\u80fd\u7b97\u6cd5\u65f6\u6027\u80fd\u529f\u8017\u6bd4\u5168\u9762\u8d85\u8d8a\u4f20\u7edf\u5904\u7406\u5668\u3002<\/p>\n

\n\t\u4e2d\u661f\u5fae<\/p>\n

\n\t1999 \u5e74\uff0c \u7531\u591a\u4f4d\u6765\u81ea\u7845\u8c37\u7684\u535a\u58eb\u4f01\u4e1a\u5bb6\u5728\u5317\u4eac\u4e2d\u5173\u6751\u79d1\u6280\u56ed\u533a\u521b\u5efa\u4e86\u4e2d\u661f\u5fae\u7535\u5b50\u6709\u9650\u516c\u53f8\uff0c \u542f\u52a8\u5e76\u627f\u62c5\u4e86\u56fd\u5bb6\u6218\u7565\u9879\u76ee——“\u661f\u5149\u4e2d\u56fd\u82af\u5de5\u7a0b”,\u81f4\u529b\u4e8e\u6570\u5b57\u591a\u5a92\u4f53\u82af\u7247\u7684\u5f00\u53d1\u3001\u8bbe\u8ba1\u548c\u4ea7\u4e1a\u5316\u3002<\/p>\n

\n\t2016 \u5e74\u521d\uff0c\u4e2d\u661f\u5fae\u63a8\u51fa\u4e86\u5168\u7403\u9996\u6b3e\u96c6\u6210\u4e86\u795e\u7ecf\u7f51\u7edc\u5904\u7406\u5668\uff08NPU\uff09\u7684 SVAC \u89c6\u9891\u7f16\u89e3\u7801 SoC\uff0c\u4f7f\u5f97\u667a\u80fd\u5206\u6790\u7ed3\u679c\u53ef\u4ee5\u4e0e\u89c6\u9891\u6570\u636e\u540c\u65f6\u7f16\u7801\uff0c\u5f62\u6210\u7ed3\u6784\u5316\u7684\u89c6\u9891\u7801\u6d41\u3002\u8be5\u6280\u672f\u88ab\u5e7f\u6cdb\u5e94\u7528\u4e8e\u89c6\u9891\u76d1\u63a7\u6444\u50cf\u5934\uff0c\u5f00\u542f\u4e86\u5b89\u9632\u76d1\u63a7\u667a\u80fd\u5316\u7684\u65b0\u65f6\u4ee3\u3002\u81ea\u4e3b\u8bbe\u8ba1\u7684\u5d4c\u5165\u5f0f\u795e\u7ecf\u7f51\u7edc\u5904\u7406\u5668\uff08NPU\uff09\u91c7\u7528\u4e86“\u6570\u636e\u9a71\u52a8\u5e76\u884c\u8ba1\u7b97” \u67b6\u6784\uff0c\u4e13\u95e8\u9488\u5bf9\u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\u8fdb\u884c\u4e86\u4f18\u5316\uff0c\u5177\u5907\u9ad8\u6027\u80fd\u3001\u4f4e\u529f\u8017\u3001\u9ad8\u96c6\u6210\u5ea6\u3001\u5c0f\u5c3a\u5bf8\u7b49\u7279\u70b9\uff0c\u7279\u522b\u9002\u5408\u7269\u8054\u7f51\u524d\u7aef\u667a\u80fd\u7684\u9700\u6c42\u3002<\/p>\n

\n\t\u5730\u5e73\u7ebf\u673a\u5668\u4eba\uff08Horizon Robotics\uff09<\/p>\n

\n\t\u5730\u5e73\u7ebf\u673a\u5668\u4eba\u6210\u7acb\u4e8e 2015 \u5e74\uff0c\u603b\u90e8\u5728\u5317\u4eac\uff0c\u521b\u59cb\u4eba\u662f\u524d\u767e\u5ea6\u6df1\u5ea6\u5b66\u4e60\u7814\u7a76\u9662\u8d1f\u8d23\u4eba\u4f59\u51ef\u3002BPU\uff08BrainProcessing Unit\uff09 \u662f\u5730\u5e73\u7ebf\u673a\u5668\u4eba\u81ea\u4e3b\u8bbe\u8ba1\u7814\u53d1\u7684\u9ad8\u6548\u4eba\u5de5\u667a\u80fd\u5904\u7406\u5668\u67b6\u6784IP\uff0c\u652f\u6301 ARM\/GPU\/FPGA\/ASIC \u5b9e\u73b0\uff0c\u4e13\u6ce8\u4e8e\u81ea\u52a8\u9a7e\u9a76<\/u>\u3001\u4eba\u8138\u56fe\u50cf\u8fa8\u8bc6\u7b49\u4e13\u7528\u9886\u57df\u3002<\/p>\n

\n\t2017\u5e74\uff0c\u5730\u5e73\u7ebf\u53d1\u5e03\u57fa\u4e8e\u9ad8\u65af\u67b6\u6784\u7684\u5d4c\u5165\u5f0f\u4eba\u5de5\u667a\u80fd\u89e3\u51b3\u65b9\u6848\uff0c\u5c06\u5728\u667a\u80fd\u9a7e\u9a76\u3001\u667a\u80fd\u751f\u6d3b\u3001\u516c\u5171\u5b89\u9632\u4e09\u4e2a\u9886\u57df\u8fdb\u884c\u5e94\u7528\uff0c\u7b2c\u4e00\u4ee3 BPU\u82af\u7247“\u76d8\u53e4” \u76ee\u524d\u5df2\u8fdb\u5165\u6d41\u7247\u9636\u6bb5\uff0c\u9884\u8ba1\u5728 2018\u5e74\u4e0b\u534a\u5e74\u63a8\u51fa\uff0c\u80fd\u652f\u6301 1080P \u7684\u9ad8\u6e05\u56fe\u50cf\u8f93\u5165\uff0c\u6bcf\u79d2\u949f\u5904\u7406 30 \u5e27\uff0c\u68c0\u6d4b\u8ddf\u8e2a\u6570\u767e\u4e2a\u76ee\u6807\u3002\u5730\u5e73\u7ebf\u7684\u7b2c\u4e00\u4ee3 BPU \u91c7\u7528 TSMC \u7684 40nm\u5de5\u827a\uff0c\u76f8\u5bf9\u4e8e\u4f20\u7edf CPU\/GPU\uff0c \u80fd\u6548\u53ef\u4ee5\u63d0\u5347 2~3 \u4e2a\u6570\u91cf\u7ea7\uff08100~1,000 \u500d\u5de6\u53f3\uff09\u3002<\/p>\n

\n\t\u6df1\u9274\u79d1\u6280<\/p>\n

\n\t\u6df1\u9274\u79d1\u6280\u6210\u7acb\u4e8e 2016 \u5e74\uff0c\u603b\u90e8\u5728\u5317\u4eac\u3002\u7531\u6e05\u534e\u5927\u5b66\u4e0e\u65af\u5766\u798f\u5927\u5b66\u7684\u4e16\u754c\u9876\u5c16\u6df1\u5ea6\u5b66\u4e60\u786c\u4ef6\u7814\u7a76\u8005\u521b\u7acb\u3002\u6df1\u9274\u79d1\u6280\u4e8e 2018 \u5e74 7 \u6708\u88ab\u8d5b\u7075\u601d<\/u>\u6536\u8d2d\u3002\u6df1\u9274\u79d1\u6280\u5c06\u5176\u5f00\u53d1\u7684\u57fa\u4e8e FPGA \u7684\u795e\u7ecf\u7f51\u7edc\u5904\u7406\u5668\u79f0\u4e3a DPU\u3002<\/p>\n

\n\t\u5230\u76ee\u524d\u4e3a\u6b62\uff0c\u6df1\u9274\u516c\u5f00\u53d1\u5e03\u4e86\u4e24\u6b3e DPU\uff1a\u4e9a\u91cc\u58eb\u591a\u5fb7\u67b6\u6784\u548c\u7b1b\u5361\u5c14\u67b6\u6784\uff0c\u5176\u4e2d\uff0c\u4e9a\u91cc\u58eb\u591a\u5fb7\u67b6\u6784\u662f\u9488\u5bf9\u5377\u79ef\u795e\u7ecf\u7f51\u7edc CNN \u800c\u8bbe\u8ba1\uff1b\u7b1b\u5361\u5c14\u67b6\u6784\u4e13\u4e3a\u5904\u7406 DNN\/RNN \u7f51\u7edc\u800c\u8bbe\u8ba1\uff0c\u53ef\u5bf9\u7ecf\u8fc7\u7ed3\u6784\u538b\u7f29\u540e\u7684\u7a00\u758f\u795e\u7ecf\u7f51\u7edc\u8fdb\u884c\u6781\u81f4\u9ad8\u6548\u7684\u786c\u4ef6\u52a0\u901f\u3002\u76f8\u5bf9\u4e8e Intel XeonCPU \u4e0e Nvidia TitanX GPU\uff0c\u5e94\u7528\u7b1b\u5361\u5c14\u67b6\u6784\u7684\u5904\u7406\u5668\u5728\u8ba1\u7b97\u901f\u5ea6\u4e0a\u5206\u522b\u63d0\u9ad8 189 \u500d\u4e0e 13 \u500d\uff0c\u5177\u6709 24,000 \u500d\u4e0e 3,000 \u500d\u7684\u66f4\u9ad8\u80fd\u6548\u3002<\/p>\n

\n\t\u7075\u6c50\u79d1\u6280<\/p>\n

\n\t\u7075\u6c50\u79d1\u6280\u4e8e 2018 \u5e74 1 \u6708\u5728\u5317\u4eac\u6210\u7acb\uff0c\u8054\u5408\u521b\u59cb\u4eba\u5305\u62ec\u6e05\u534e\u5927\u5b66\u7684\u4e16\u754c\u9876\u5c16\u7c7b\u8111\u8ba1\u7b97\u7814\u7a76\u8005\u3002<\/p>\n

\n\t\u516c\u53f8\u81f4\u529b\u4e8e\u65b0\u4e00\u4ee3\u795e\u7ecf\u7f51\u7edc\u5904\u7406\u5668\uff08Tianjic\uff09 \u5f00\u53d1\uff0c \u7279\u70b9\u5728\u4e8e\u65e2\u80fd\u591f\u9ad8\u6548\u652f\u6491\u73b0\u6709\u6d41\u884c\u7684\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\uff08\u5305\u62ec CNN\uff0c MLP\uff0c LSTM \u7b49\u7f51\u7edc\u67b6\u6784\uff09\uff0c\u4e5f\u80fd\u591f\u652f\u6491\u66f4\u4eff\u8111\u7684\u3001\u66f4\u5177\u6210\u957f\u6f5c\u529b\u7684\u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u7b97\u6cd5\uff1b \u4f7f\u82af\u7247\u5177\u6709\u9ad8\u8ba1\u7b97\u529b\u3001\u9ad8\u591a\u4efb\u52a1\u5e76\u884c\u5ea6\u548c\u8f83\u4f4e\u529f\u8017\u7b49\u4f18\u70b9\u3002 \u8f6f\u4ef6\u5de5\u5177\u94fe\u65b9\u9762\u652f\u6301\u7531 Caffe\u3001 TensorFlow<\/u> \u7b49\u7b97\u6cd5\u5e73\u53f0\u76f4\u63a5\u8fdb\u884c\u795e\u7ecf\u7f51\u7edc\u7684\u6620\u5c04\u7f16\u8bd1\uff0c\u5f00\u53d1\u53cb\u5584\u7684\u7528\u6237\u4ea4\u4e92\u754c\u9762\u3002 Tianjic \u53ef\u7528\u4e8e\u4e91\u7aef\u8ba1\u7b97\u548c\u7ec8\u7aef\u5e94\u7528\u573a\u666f\uff0c\u52a9\u529b\u4eba\u5de5\u667a\u80fd\u7684\u843d\u5730\u548c\u63a8\u5e7f\u3002<\/p>\n

\n\t\u542f\u82f1\u6cf0\u4f26<\/p>\n

\n\t\u542f\u82f1\u6cf0\u4f26\u4e8e2015\u5e74 11\u6708\u5728\u6210\u90fd\u6210\u7acb\uff0c\u662f\u4e00\u5bb6\u8bed\u97f3\u8bc6\u522b\u82af\u7247\u7814\u53d1\u5546\u3002\u542f\u82f1\u6cf0\u4f26\u7684 CI1006\u662f\u57fa\u4e8e ASIC \u67b6\u6784\u7684\u4eba\u5de5\u667a\u80fd\u8bed\u97f3\u8bc6\u522b\u82af\u7247\uff0c\u5305\u542b\u4e86\u8111\u795e\u7ecf\u7f51\u7edc\u5904\u7406\u786c\u4ef6\u5355\u5143\uff0c\u80fd\u591f\u5b8c\u7f8e\u652f\u6301 DNN \u8fd0\u7b97\u67b6\u6784\uff0c\u8fdb\u884c\u9ad8\u6027\u80fd\u7684\u6570\u636e\u5e76\u884c\u8ba1\u7b97\uff0c\u53ef\u6781\u5927\u7684\u63d0\u9ad8\u4eba\u5de5\u667a\u80fd\u6df1\u5ea6\u5b66\u4e60\u8bed\u97f3\u6280\u672f\u5bf9\u5927\u91cf\u6570\u636e\u7684\u5904\u7406\u6548\u7387\u3002<\/p>\n

\n\t\u767e\u5ea6<\/p>\n

\n\t\u767e\u5ea6 2017 \u5e74 8 \u6708 Hot Chips \u5927\u4f1a\u4e0a\u53d1\u5e03\u4e86 XPU\uff0c\u8fd9\u662f\u4e00\u6b3e 256 \u6838\u3001\u57fa\u4e8e FPGA \u7684\u4e91\u8ba1\u7b97\u52a0\u901f\u82af\u7247\u3002\u5408\u4f5c\u4f19\u4f34\u662f\u8d5b\u601d\u7075\uff08Xilinx\uff09\u3002 XPU \u91c7\u7528\u65b0\u4e00\u4ee3 AI \u5904\u7406\u67b6\u6784\uff0c\u62e5\u6709 GPU \u7684\u901a\u7528\u6027\u548c FPGA \u7684\u9ad8\u6548\u7387\u548c\u4f4e\u80fd\u8017\uff0c\u5bf9\u767e\u5ea6\u7684\u6df1\u5ea6\u5b66\u4e60\u5e73\u53f0 PaddlePaddle \u505a\u4e86\u9ad8\u5ea6\u7684\u4f18\u5316\u548c\u52a0\u901f\u3002\u636e\u4ecb\u7ecd\uff0c XPU \u5173\u6ce8\u8ba1\u7b97\u5bc6\u96c6\u578b\u3001\u57fa\u4e8e\u89c4\u5219\u7684\u591a\u6837\u5316\u8ba1\u7b97\u4efb\u52a1\uff0c\u5e0c\u671b\u63d0\u9ad8\u6548\u7387\u548c\u6027\u80fd\uff0c\u5e76\u5e26\u6765\u7c7b\u4f3c CPU \u7684\u7075\u6d3b\u6027\u3002<\/p>\n

\n\t\u534e\u4e3a<\/p>\n

\n\t<\/p>\n

\n\t\u9e92\u9e9f 970 \u642d\u8f7d\u7684\u795e\u7ecf\u7f51\u7edc\u5904\u7406\u5668 NPU \u91c7\u7528\u4e86\u5bd2\u6b66\u7eaa IP\uff0c\u5982\u56fe 12 \u6240\u793a\u3002\u9e92\u9e9f 970 \u91c7\u7528\u4e86 TSMC 10nm \u5de5\u827a\u5236\u7a0b\uff0c\u62e5\u6709 55 \u4ebf\u4e2a\u6676\u4f53\u7ba1\uff0c\u529f\u8017\u76f8\u6bd4\u4e0a\u4e00\u4ee3\u82af\u7247\u964d\u4f4e 20%\u3002 CPU \u67b6\u6784\u65b9\u9762\u4e3a 4 \u6838 A73+4 \u6838 A53 \u7ec4\u6210 8 \u6838\u5fc3\uff0c\u80fd\u8017\u540c\u6bd4\u4e0a\u4e00\u4ee3\u82af\u7247\u5f97\u5230 20%\u7684\u63d0\u5347\uff1b GPU \u65b9\u9762\u91c7\u7528\u4e86 12 \u6838 Mali G72 MP12GPU\uff0c\u5728\u56fe\u5f62\u5904\u7406\u4ee5\u53ca\u80fd\u6548\u4e24\u9879\u5173\u952e\u6307\u6807\u65b9\u9762\u5206\u522b\u63d0\u5347 20%\u548c50%\uff1b NPU \u91c7\u7528 HiAI\u79fb\u52a8\u8ba1\u7b97\u67b6\u6784\uff0c\u5728 FP16 \u4e0b\u63d0\u4f9b\u7684\u8fd0\u7b97\u6027\u80fd\u53ef\u4ee5\u8fbe\u5230 1.92 TFLOPs\uff0c\u76f8\u6bd4\u56db\u4e2a Cortex-A73 \u6838\u5fc3\uff0c\u5904\u7406\u540c\u6837\u7684 AI \u4efb\u52a1\uff0c\u6709\u5927\u7ea6\u5177\u5907 50 \u500d\u80fd\u6548\u548c 25 \u500d\u6027\u80fd\u4f18\u52bf\u3002<\/p>\n

\n\t\u82f1\u4f1f\u8fbe\uff08Nvidia\uff09<\/p>\n

\n\t\u82f1\u4f1f\u8fbe\u521b\u7acb\u4e8e 1993 \u5e74\uff0c\u603b\u90e8\u4f4d\u4e8e\u7f8e\u56fd\u52a0\u5229\u798f\u5c3c\u4e9a\u5dde\u5723\u514b\u62c9\u62c9\u5e02\u3002 \u65e9\u5728 1999 \u5e74\uff0c \u82f1\u4f1f\u8fbe\u53d1\u660e\u4e86 GPU\uff0c\u91cd\u65b0\u5b9a\u4e49\u4e86\u73b0\u4ee3\u8ba1\u7b97\u673a\u56fe\u5f62\u6280\u672f\uff0c\u5f7b\u5e95\u6539\u53d8\u4e86\u5e76\u884c\u8ba1\u7b97\u3002\u6df1\u5ea6\u5b66\u4e60\u5bf9\u8ba1\u7b97\u901f\u5ea6\u6709\u975e\u5e38\u82db\u523b\u7684\u8981\u6c42\uff0c \u800c\u82f1\u4f1f\u8fbe\u7684 GPU \u82af\u7247\u53ef\u4ee5\u8ba9\u5927\u91cf\u5904\u7406\u5668\u5e76\u884c\u8fd0\u7b97\uff0c\u901f\u5ea6\u6bd4 CPU \u5feb\u5341\u500d\u751a\u81f3\u51e0\u5341\u500d\uff0c\u56e0\u800c\u6210\u4e3a\u7edd\u5927\u90e8\u5206\u4eba\u5de5\u667a\u80fd\u7814\u7a76\u8005\u548c\u5f00\u53d1\u8005\u7684\u9996\u9009\u3002\u81ea\u4ece Google Brain \u91c7\u7528 1.6 \u4e07\u4e2a GPU \u6838\u8bad\u7ec3 DNN \u6a21\u578b\uff0c \u5e76\u5728\u8bed\u97f3\u548c\u56fe\u50cf\u8bc6\u522b\u7b49\u9886\u57df\u83b7\u5f97\u5de8\u5927\u6210\u529f\u4ee5\u6765\uff0c \u82f1\u4f1f\u8fbe\u5df2\u6210\u4e3a AI \u82af\u7247\u5e02\u573a\u4e2d\u65e0\u53ef\u4e89\u8bae\u7684\u9886\u5bfc\u8005\u3002<\/p>\n

\n\tAMD<\/p>\n

\n\t\u7f8e\u56fd AMD \u534a\u5bfc\u4f53\u516c\u53f8\u4e13\u95e8\u4e3a\u8ba1\u7b97\u673a\u3001 \u901a\u4fe1\u548c\u6d88\u8d39\u7535\u5b50\u884c\u4e1a\u8bbe\u8ba1\u548c\u5236\u9020\u5404\u79cd\u521b\u65b0\u7684\u5fae\u5904\u7406\u5668\uff08CPU\u3001 GPU\u3001 APU\u3001 \u4e3b\u677f\u82af\u7247\u7ec4\u3001 \u7535\u89c6\u5361\u82af\u7247\u7b49\uff09\uff0c\u4ee5\u53ca\u63d0\u4f9b\u95ea\u5b58\u548c\u4f4e\u529f\u7387\u5904\u7406\u5668\u89e3\u51b3\u65b9\u6848\uff0c \u516c\u53f8\u6210\u7acb\u4e8e 1969 \u5e74\u3002 AMD \u81f4\u529b\u4e3a\u6280\u672f\u7528\u6237——\u4ece\u4f01\u4e1a\u3001 \u653f\u5e9c\u673a\u6784\u5230\u4e2a\u4eba\u6d88\u8d39\u8005——\u63d0\u4f9b\u57fa\u4e8e\u6807\u51c6\u7684\u3001 \u4ee5\u5ba2\u6237\u4e3a\u4e2d\u5fc3\u7684\u89e3\u51b3\u65b9\u6848\u3002<\/p>\n

\n\t2017 \u5e74 12 \u6708 Intel \u548c AMD \u5ba3\u5e03\u5c06\u8054\u624b\u63a8\u51fa\u4e00\u6b3e\u7ed3\u5408\u82f1\u7279\u5c14<\/u>\u5904\u7406\u5668\u548c AMD \u56fe\u5f62\u5355\u5143\u7684\u7b14\u8bb0\u672c\u7535\u8111\u82af\u7247\u3002 \u76ee\u524d AMD \u62e5\u6709\u9488\u5bf9 AI \u548c\u673a\u5668\u5b66\u4e60\u7684\u9ad8\u6027\u80fd Radeon Instinc \u52a0\u901f\u5361\uff0c\u5f00\u653e\u5f0f\u8f6f\u4ef6\u5e73\u53f0 ROCm \u7b49\u3002<\/p>\n

\n\tGoogle <\/p>\n

\n\tGoogle \u5728 2016 \u5e74\u5ba3\u5e03\u72ec\u7acb\u5f00\u53d1\u4e00\u79cd\u540d\u4e3a TPU \u7684\u5168\u65b0\u7684\u5904\u7406\u7cfb\u7edf\u3002 TPU \u662f\u4e13\u95e8\u4e3a\u673a\u5668\u5b66\u4e60\u5e94\u7528\u800c\u8bbe\u8ba1\u7684\u4e13\u7528\u82af\u7247\u3002\u901a\u8fc7\u964d\u4f4e\u82af\u7247\u7684\u8ba1\u7b97\u7cbe\u5ea6\uff0c\u51cf\u5c11\u5b9e\u73b0\u6bcf\u4e2a\u8ba1\u7b97\u64cd\u4f5c\u6240\u9700\u6676\u4f53\u7ba1\u6570\u91cf\u7684\u65b9\u5f0f\uff0c\u8ba9\u82af\u7247\u7684\u6bcf\u79d2\u8fd0\u884c\u7684\u64cd\u4f5c\u4e2a\u6570\u66f4\u9ad8\uff0c\u8fd9\u6837\u7ecf\u8fc7\u7cbe\u7ec6\u8c03\u4f18\u7684\u673a\u5668\u5b66\u4e60\u6a21\u578b\u5c31\u80fd\u5728\u82af\u7247\u4e0a\u8fd0\u884c\u5f97\u66f4\u5feb\uff0c\u8fdb\u800c\u66f4\u5feb\u5730\u8ba9\u7528\u6237\u5f97\u5230\u66f4\u667a\u80fd\u7684\u7ed3\u679c\u3002 <\/p>\n

\n\t\u5728 2016 \u5e74 3 \u6708\u6253\u8d25\u4e86\u674e\u4e16\u77f3\u548c 2017 \u5e74 5 \u6708\u6253\u8d25\u4e86\u67ef\u6770\u7684\u963f\u5c14\u6cd5\u72d7\uff0c\u5c31\u662f\u91c7\u7528\u4e86\u8c37\u6b4c\u7684 TPU \u7cfb\u5217\u82af\u7247\u3002<\/p>\n

\n\tGoogle I\/O-2018 \u5f00\u53d1\u8005\u5927\u4f1a\u671f\u95f4\uff0c\u6b63\u5f0f\u53d1\u5e03\u4e86\u7b2c\u4e09\u4ee3\u4eba\u5de5\u667a\u80fd\u5b66\u4e60\u4e13\u7528\u5904\u7406\u5668 TPU 3.0\u3002TPU3.0 \u91c7\u7528 8 \u4f4d\u4f4e\u7cbe\u5ea6\u8ba1\u7b97\u4ee5\u8282\u7701\u6676\u4f53\u7ba1\u6570\u91cf\uff0c \u5bf9\u7cbe\u5ea6\u5f71\u54cd\u5f88\u5c0f\u4f46\u53ef\u4ee5\u5927\u5e45\u8282\u7ea6\u529f\u8017\u3001\u52a0\u5feb\u901f\u5ea6\uff0c\u540c\u65f6\u8fd8\u6709\u8109\u52a8\u9635\u5217\u8bbe\u8ba1\uff0c\u4f18\u5316\u77e9\u9635\u4e58\u6cd5\u4e0e\u5377\u79ef\u8fd0\u7b97\uff0c \u5e76\u4f7f\u7528\u66f4\u5927\u7684\u7247\u4e0a\u5185\u5b58\uff0c\u51cf\u5c11\u5bf9\u7cfb\u7edf\u5185\u5b58\u7684\u4f9d\u8d56\u3002 \u901f\u5ea6\u80fd\u52a0\u5feb\u5230\u6700\u9ad8 100PFlops\uff08\u6bcf\u79d2 1000 \u4e07\u4ebf\u6b21\u6d6e\u70b9\u8ba1\u7b97\uff09\u3002<\/p>\n

\n\t\u9ad8\u901a<\/p>\n

\n\t\u5728\u667a\u80fd\u624b\u673a\u82af\u7247\u5e02\u573a\u5360\u636e\u7edd\u5bf9\u4f18\u52bf\u7684\u9ad8\u901a\u516c\u53f8\uff0c\u4e5f\u5728\u4eba\u5de5\u667a\u80fd\u82af\u7247\u65b9\u9762\u79ef\u6781\u5e03\u5c40\u3002\u636e\u9ad8\u901a\u63d0\u4f9b\u7684\u8d44\u6599\u663e\u793a\uff0c\u5176\u5728\u4eba\u5de5\u667a\u80fd\u65b9\u9762\u5df2\u6295\u8d44\u4e86 Clarifai \u516c\u53f8\u548c\u4e2d\u56fd“\u4e13\u6ce8\u4e8e\u7269\u8054\u7f51\u4eba\u5de5\u667a\u80fd\u670d\u52a1” \u7684\u4e91\u77e5\u58f0\u3002\u800c\u65e9\u5728 2015 \u5e74 CES \u4e0a\uff0c\u9ad8\u901a\u5c31\u5df2\u63a8\u51fa\u4e86\u4e00\u6b3e\u642d\u8f7d\u9a81\u9f99 SoC \u7684\u98de\u884c\u673a\u5668\u4eba——Snapdragon Cargo\u3002<\/p>\n

\n\t\u9ad8\u901a\u8ba4\u4e3a\u5728\u5de5\u4e1a\u3001\u519c\u4e1a\u7684\u76d1\u6d4b\u4ee5\u53ca\u822a\u62cd\u5bf9\u62cd\u7167\u3001\u6444\u50cf\u4ee5\u53ca\u89c6\u9891\u65b0\u9700\u6c42\u4e0a\uff0c\u516c\u53f8\u6070\u597d\u53ef\u4ee5\u53d1\u6325\u5176\u5728\u8ba1\u7b97\u673a\u89c6\u89c9\u9886\u57df\u7684\u80fd\u529b\u3002\u6b64\u5916\uff0c\u9ad8\u901a\u7684\u9a81\u9f99 820 \u82af\u7247\u4e5f\u88ab\u5e94\u7528\u4e8e VR\u5934\u76d4\u4e2d\u3002\u4e8b\u5b9e\u4e0a\uff0c\u9ad8\u901a\u5df2\u7ecf\u5728\u7814\u53d1\u53ef\u4ee5\u5728\u672c\u5730\u5b8c\u6210\u6df1\u5ea6\u5b66\u4e60\u7684\u79fb\u52a8\u7aef\u8bbe\u5907\u82af\u7247\u3002<\/p>\n

\n\tNervana Systems<\/p>\n

\n\tNervana \u521b\u7acb\u4e8e 2014 \u5e74\uff0c \u516c\u53f8\u63a8\u51fa\u7684 The Nervana Engine \u662f\u4e00\u4e2a\u4e3a\u6df1\u5ea6\u5b66\u4e60\u4e13\u95e8\u5b9a\u5236\u548c\u4f18\u5316\u7684 ASIC \u82af\u7247\u3002\u8fd9\u4e2a\u65b9\u6848\u7684\u5b9e\u73b0\u5f97\u76ca\u4e8e\u4e00\u9879\u53eb\u505a High Bandwidt<\/u>h Memory \u7684\u65b0\u578b\u5185\u5b58\u6280\u672f\uff0c \u8fd9\u9879\u6280\u672f\u540c\u65f6\u62e5\u6709\u9ad8\u5bb9\u91cf\u548c\u9ad8\u901f\u5ea6\uff0c\u63d0\u4f9b 32GB \u7684\u7247\u4e0a\u50a8\u5b58\u548c 8TB \u6bcf\u79d2\u7684\u5185\u5b58\u8bbf\u95ee\u901f\u5ea6\u3002\u8be5\u516c\u53f8\u76ee\u524d\u63d0\u4f9b\u4e00\u4e2a\u4eba\u5de5\u667a\u80fd\u670d\u52a1“in the cloud” \uff0c\u4ed6\u4eec\u58f0\u79f0\u8fd9\u662f\u4e16\u754c\u4e0a\u6700\u5feb\u7684\u4e14\u76ee\u524d\u5df2\u88ab\u91d1\u878d\u670d\u52a1\u673a\u6784\u3001\u533b\u7597\u4fdd\u5065\u63d0\u4f9b\u8005\u548c\u653f\u5e9c\u673a\u6784\u6240\u4f7f\u7528\u7684\u670d\u52a1\u3002 \u4ed6\u4eec\u7684\u65b0\u578b\u82af\u7247\u5c06\u4f1a\u4fdd\u8bc1 Nervana \u4e91\u5e73\u53f0\u5728\u672a\u6765\u7684\u51e0\u5e74\u5185\u4ecd\u4fdd\u6301\u6700\u5feb\u7684\u901f\u5ea6\u3002<\/p>\n

\n\tMovidius\uff08\u88ab Intel \u6536\u8d2d\uff09<\/p>\n

\n\t2016 \u5e74 9 \u6708\uff0c Intel \u53d1\u8868\u58f0\u660e\u6536\u8d2d\u4e86 Movidius\u3002 Movidius \u4e13\u6ce8\u4e8e\u7814\u53d1\u9ad8\u6027\u80fd\u89c6\u89c9\u5904\u7406\u82af\u7247\u3002\u5176\u6700\u65b0\u4e00\u4ee3\u7684 Myriad2 \u89c6\u89c9\u5904\u7406\u5668\u4e3b\u8981\u7531 SPARC \u5904\u7406\u5668\u4f5c\u4e3a\u4e3b\u63a7\u5236\u5668\uff0c\u52a0\u4e0a\u4e13\u95e8\u7684DSP \u5904\u7406\u5668\u548c\u786c\u4ef6\u52a0\u901f\u7535\u8def\u6765\u5904\u7406\u4e13\u95e8\u7684\u89c6\u89c9\u548c\u56fe\u50cf\u4fe1\u53f7\u3002\u8fd9\u662f\u4e00\u6b3e\u4ee5 DSP \u67b6\u6784\u4e3a\u57fa\u7840\u7684\u89c6\u89c9\u5904\u7406\u5668\uff0c\u5728\u89c6\u89c9\u76f8\u5173\u7684\u5e94\u7528\u9886\u57df\u6709\u6781\u9ad8\u7684\u80fd\u8017\u6bd4\uff0c\u53ef\u4ee5\u5c06\u89c6\u89c9\u8ba1\u7b97\u666e\u53ca\u5230\u51e0\u4e4e\u6240\u6709\u7684\u5d4c\u5165\u5f0f\u7cfb\u7edf\u4e2d\u3002<\/p>\n

\n\t\u8be5\u82af\u7247\u5df2\u88ab\u5927\u91cf\u5e94\u7528\u5728 Google 3D \u9879\u76ee\u7684 Tango \u624b\u673a\u3001\u5927\u7586<\/u>\u65e0\u4eba\u673a\u3001 FLIR<\/u> \u667a\u80fd\u7ea2\u5916<\/u>\u6444\u50cf\u673a\u3001\u6d77\u5eb7\u6df1\u7738\u7cfb\u5217\u6444\u50cf\u673a\u3001\u534e\u777f\u667a\u80fd\u5de5\u4e1a\u76f8\u673a\u7b49\u4ea7\u54c1\u4e2d\u3002<\/p>\n

\n\tIBM<\/p>\n

\n\tIBM \u5f88\u65e9\u4ee5\u524d\u5c31\u53d1\u5e03\u8fc7 watson\uff0c\u6295\u5165\u4e86\u5f88\u591a\u7684\u5b9e\u9645\u5e94\u7528\u3002\u9664\u6b64\u4e4b\u5916\uff0c\u8fd8\u542f\u52a8\u4e86\u7c7b\u8111\u82af\u7247\u7684\u7814\u53d1\uff0c \u5373 TrueNorth\u3002TrueNorth \u662f IBM \u53c2\u4e0e DARPA \u7684\u7814\u7a76\u9879\u76ee SyNapse \u7684\u6700\u65b0\u6210\u679c\u3002<\/p>\n

\n\tSyNapse \u5168\u79f0\u662fSystems of Neurom<\/u>orphic Adaptive Plastic Scalable Electronics\uff08\u81ea\u9002\u5e94\u53ef\u5851\u53ef\u4f38\u7f29\u7535\u5b50\u795e\u7ecf\u7cfb\u7edf\uff0c\u800c SyNapse \u6b63\u597d\u662f\u7a81\u89e6\u7684\u610f\u601d\uff09\uff0c\u5176\u7ec8\u6781\u76ee\u6807\u662f\u5f00\u53d1\u51fa\u6253\u7834\u51af·\u8bfa\u4f9d\u66fc\u4f53\u7cfb\u7ed3\u6784\u7684\u8ba1\u7b97\u673a\u4f53\u7cfb\u7ed3\u6784\u3002<\/p>\n

\n\tARM<\/p>\n

\n\tARM \u63a8\u51fa\u5168\u65b0\u82af\u7247\u67b6\u6784 DynamIQ\uff0c\u901a\u8fc7\u8fd9\u9879\u6280\u672f\uff0c AI \u82af\u7247\u7684\u6027\u80fd\u6709\u671b\u5728\u672a\u6765\u4e09\u5230\u4e94\u5e74\u5185\u63d0\u5347 50 \u500d\u3002<\/p>\n

\n\tARM\u7684\u65b0CPU\u67b6\u6784\u5c06\u4f1a\u901a\u8fc7\u4e3a\u4e0d\u540c\u90e8\u5206\u914d\u7f6e\u8f6f\u4ef6\u7684\u65b9\u5f0f\u5c06\u591a\u4e2a\u5904\u7406\u6838\u5fc3\u96c6\u805a\u5728\u4e00\u8d77\uff0c\u8fd9\u5176\u4e2d\u5305\u62ec\u4e00\u4e2a\u4e13\u95e8\u4e3a AI \u7b97\u6cd5\u8bbe\u8ba1\u7684\u5904\u7406\u5668\u3002\u82af\u7247\u5382\u5546\u5c06\u53ef\u4ee5\u4e3a\u65b0\u5904\u7406\u5668\u914d\u7f6e\u6700\u591a 8 \u4e2a\u6838\u5fc3\u3002\u540c\u65f6\u4e3a\u4e86\u80fd\u8ba9\u4e3b\u6d41 AI \u5728\u81ea\u5df1\u7684\u5904\u7406\u5668\u4e0a\u66f4\u597d\u5730\u8fd0\u884c\uff0c ARM \u8fd8\u5c06\u63a8\u51fa\u4e00\u7cfb\u5217\u8f6f\u4ef6\u5e93\u3002<\/p>\n

\n\tCEVA<\/p>\n

\n\tCEVA \u662f\u4e13\u6ce8\u4e8e DSP \u7684 IP \u4f9b\u5e94\u5546\uff0c\u62e5\u6709\u4f17\u591a\u7684\u4ea7\u54c1\u7ebf\u3002\u5176\u4e2d\uff0c\u56fe\u50cf\u548c\u8ba1\u7b97\u673a\u89c6\u89c9 DSP\u4ea7\u54c1 CEVA-XM4\u662f\u7b2c\u4e00\u4e2a\u652f\u6301\u6df1\u5ea6\u5b66\u4e60\u7684\u53ef\u7f16\u7a0b DSP\uff0c\u800c\u5176\u53d1\u5e03\u7684\u65b0\u4e00\u4ee3\u578b\u53f7 CEVA-XM6\uff0c\u5177\u6709\u66f4\u4f18\u7684\u6027\u80fd\u3001\u66f4\u5f3a\u5927\u7684\u8ba1\u7b97\u80fd\u529b\u4ee5\u53ca\u66f4\u4f4e\u7684\u80fd\u8017\u3002CEVA \u6307\u51fa\uff0c\u667a\u80fd\u624b\u673a\u3001\u6c7d\u8f66\u3001\u5b89\u5168\u548c\u5546\u4e1a\u5e94\u7528\uff0c\u5982\u65e0\u4eba\u673a\u3001\u81ea\u52a8\u5316\u5c06\u662f\u5176\u4e1a\u52a1\u5f00\u5c55\u7684\u4e3b\u8981\u76ee\u6807\u3002<\/p>\n

\n\tMIT\/Eyeriss<\/p>\n

\n\tEyeriss \u4e8b\u5b9e\u4e0a\u662f MIT \u7684\u4e00\u4e2a\u9879\u76ee\uff0c\u8fd8\u4e0d\u662f\u4e00\u4e2a\u516c\u53f8\uff0c \u4ece\u957f\u8fdc\u6765\u770b\uff0c\u5982\u679c\u8fdb\u5c55\u987a\u5229\uff0c\u5f88\u53ef\u80fd\u5b75\u5316\u51fa\u4e00\u4e2a\u65b0\u7684\u516c\u53f8\u3002Eyeriss \u662f\u4e00\u4e2a\u9ad8\u6548\u80fd\u7684\u6df1\u5ea6\u5377\u79ef\u795e\u7ecf\u7f51\u7edc\uff08CNN\uff09\u52a0\u901f\u5668\u786c\u4ef6\uff0c\u8be5\u82af\u7247\u5185\u5efa 168 \u4e2a\u6838\u5fc3\uff0c\u4e13\u95e8\u7528\u6765\u90e8\u7f72\u795e\u7ecf\u7f51\u8def\uff08neural network\uff09\uff0c\u6548\u80fd\u4e3a\u4e00\u822c GPU \u7684 10 \u500d\u3002\u5176\u6280\u672f\u5173\u952e\u5728\u4e8e\u6700\u5c0f\u5316 GPU \u6838\u5fc3\u548c\u8bb0\u5fc6\u4f53\u4e4b\u95f4\u4ea4\u6362\u6570\u636e\u7684\u9891\u7387\uff08\u6b64\u8fd0\u4f5c\u8fc7\u7a0b\u901a\u5e38\u4f1a\u6d88\u8017\u5927\u91cf\u7684\u65f6\u95f4\u4e0e\u80fd\u91cf\uff09\uff1a\u4e00\u822c GPU \u5185\u7684\u6838\u5fc3\u901a\u5e38\u5171\u4eab\u5355\u4e00\u8bb0\u5fc6\u4f53\uff0c\u4f46 Eyeriss \u7684\u6bcf\u4e2a\u6838\u5fc3\u62e5\u6709\u5c5e\u4e8e\u81ea\u5df1\u7684\u8bb0\u5fc6\u4f53\u3002<\/p>\n

\n\t\u76ee\u524d\uff0c Eyeriss \u4e3b\u8981\u5b9a\u4f4d\u5728\u4eba\u8138\u8bc6\u522b\u548c\u8bed\u97f3\u8bc6\u522b\uff0c\u53ef\u5e94\u7528\u5728\u667a\u80fd\u624b\u673a\u3001\u7a7f\u6234\u5f0f\u8bbe\u5907\u3001\u673a\u5668\u4eba\u3001\u81ea\u52a8\u9a7e\u9a76\u8f66\u4e0e\u5176\u4ed6\u7269\u8054\u7f51\u5e94\u7528\u88c5\u7f6e\u4e0a\u3002<\/p>\n

\n\t\u82f9\u679c<\/p>\n

\n\t\u5728 iPhone 8 \u548c iPhone X \u7684\u53d1\u5e03\u4f1a\u4e0a\uff0c\u82f9\u679c\u660e\u786e\u8868\u793a\u5176\u4e2d\u6240\u4f7f\u7528\u7684 A11 \u5904\u7406\u5668\u96c6\u6210\u4e86\u4e00\u4e2a\u4e13\u7528\u4e8e\u673a\u5668\u5b66\u4e60\u7684\u786c\u4ef6——“\u795e\u7ecf\u7f51\u7edc\u5f15\u64ce\uff08Neural Engine\uff09 ”\uff0c \u6bcf\u79d2\u8fd0\u7b97\u6b21\u6570\u6700\u9ad8\u53ef\u8fbe6000 \u4ebf\u6b21\u3002\u8fd9\u5757\u82af\u7247\u5c06\u80fd\u591f\u6539\u8fdb\u82f9\u679c\u8bbe\u5907\u5728\u5904\u7406\u9700\u8981\u4eba\u5de5\u667a\u80fd\u7684\u4efb\u52a1\u65f6\u7684\u8868\u73b0\uff0c\u6bd4\u5982\u9762\u90e8\u8bc6\u522b\u548c\u8bed\u97f3\u8bc6\u522b\u7b49\u3002<\/p>\n

\n\t\u4e09\u661f<\/p>\n

\n\t2017 \u5e74\uff0c\u534e\u4e3a\u6d77\u601d<\/u>\u63a8\u51fa\u4e86\u9e92\u9e9f 970 \u82af\u7247\uff0c\u636e\u77e5\u60c5\u4eba\u58eb\u900f\u9732\uff0c\u4e3a\u4e86\u5bf9\u6807\u534e\u4e3a\uff0c\u4e09\u661f\u5df2\u7ecf\u7814\u53d1\u4e86\u8bb8\u591a\u79cd\u7c7b\u7684\u4eba\u5de5\u667a\u80fd\u82af\u7247\u3002 \u4e09\u661f\u8ba1\u5212\u5728\u672a\u6765\u4e09\u5e74\u5185\u65b0\u4e0a\u5e02\u7684\u667a\u80fd\u624b\u673a\u4e2d\u90fd\u91c7\u7528\u4eba\u5de5\u667a\u80fd\u82af\u7247\uff0c\u5e76\u4e14\u4ed6\u4eec\u8fd8\u5c06\u4e3a\u4eba\u5de5\u667a\u80fd\u8bbe\u5907\u5efa\u7acb\u65b0\u7684\u7ec4\u4ef6\u4e1a\u52a1\u3002\u4e09\u661f\u8fd8\u6295\u8d44\u4e86 Graphcore\u3001\u6df1\u9274\u79d1\u6280\u7b49\u4eba\u5de5\u667a\u80fd\u82af\u7247\u4f01\u4e1a\u3002<\/p>\n

\n\t3\u3001\u6280\u672f\u8d8b\u52bf<\/p>\n

\n\t<\/p>\n

\n\t\u76ee\u524d\u4e3b\u6d41 AI \u82af\u7247\u7684\u6838\u5fc3\u4e3b\u8981\u662f\u5229\u7528 MAC\uff08Multiplier and Accumulation\uff0c \u4e58\u52a0\u8ba1\u7b97\uff09 \u52a0\u901f\u9635\u5217\u6765\u5b9e\u73b0\u5bf9 CNN\uff08\u5377\u79ef\u795e\u7ecf\u7f51\u7edc\uff09\u4e2d\u6700\u4e3b\u8981\u7684\u5377\u79ef\u8fd0\u7b97\u7684\u52a0\u901f\u3002\u8fd9\u4e00\u4ee3 AI \u82af\u7247\u4e3b\u8981\u6709\u5982\u4e0b 3 \u4e2a\u65b9\u9762\u7684\u95ee\u9898\u3002<\/p>\n

\n\t\uff081\uff09\u6df1\u5ea6\u5b66\u4e60\u8ba1\u7b97\u6240\u9700\u6570\u636e\u91cf\u5de8\u5927\uff0c\u9020\u6210\u5185\u5b58\u5e26\u5bbd\u6210\u4e3a\u6574\u4e2a\u7cfb\u7edf\u7684\u74f6\u9888\uff0c\u5373\u6240\u8c13“memory wall” \u95ee\u9898\u3002<\/p>\n

\n\t\uff082\uff09\u4e0e\u7b2c\u4e00\u4e2a\u95ee\u9898\u76f8\u5173\uff0c \u5185\u5b58\u5927\u91cf\u8bbf\u95ee\u548c MAC\u9635\u5217\u7684\u5927\u91cf\u8fd0\u7b97\uff0c\u9020\u6210 AI\u82af\u7247\u6574\u4f53\u529f\u8017\u7684\u589e\u52a0\u3002<\/p>\n

\n\t\uff083\uff09\u6df1\u5ea6\u5b66\u4e60\u5bf9\u7b97\u529b\u8981\u6c42\u5f88\u9ad8\uff0c\u8981\u63d0\u5347\u7b97\u529b\uff0c\u6700\u597d\u7684\u65b9\u6cd5\u662f\u505a\u786c\u4ef6\u52a0\u901f\uff0c\u4f46\u662f\u540c\u65f6\u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\u7684\u53d1\u5c55\u4e5f\u662f\u65e5\u65b0\u6708\u5f02\uff0c\u65b0\u7684\u7b97\u6cd5\u53ef\u80fd\u5728\u5df2\u7ecf\u56fa\u5316\u7684\u786c\u4ef6\u52a0\u901f\u5668\u4e0a\u65e0\u6cd5\u5f97\u5230\u5f88\u597d\u7684\u652f\u6301\uff0c\u5373\u6027\u80fd\u548c\u7075\u6d3b\u5ea6\u4e4b\u95f4\u7684\u5e73\u8861\u95ee\u9898\u3002<\/p>\n

\n\t\u56e0\u6b64\uff0c\u53ef\u4ee5\u9884\u89c1\u4e0b\u4e00\u4ee3 AI \u82af\u7247\u5c06\u6709\u5982\u4e0b\u7684\u4e94\u4e2a\u53d1\u5c55\u8d8b\u52bf\u3002<\/p>\n

\n\t\uff081\uff09\u66f4\u9ad8\u6548\u7684\u5927\u5377\u79ef\u89e3\u6784\/\u590d\u7528<\/p>\n

\n\t\u5728\u6807\u51c6 SIMD \u7684\u57fa\u7840\u4e0a\uff0c CNN \u7531\u4e8e\u5176\u7279\u6b8a\u7684\u590d\u7528\u673a\u5236\uff0c\u53ef\u4ee5\u8fdb\u4e00\u6b65\u51cf\u5c11\u603b\u7ebf\u4e0a\u7684\u6570\u636e\u901a\u4fe1\u3002\u800c\u590d\u7528\u8fd9\u4e00\u6982\u5ff5\uff0c\u5728\u8d85\u5927\u578b\u795e\u7ecf\u7f51\u7edc\u4e2d\u5c31\u663e\u5f97\u683c\u5916\u91cd\u8981\u3002 \u5982\u4f55\u5408\u7406\u5730\u5206\u89e3\u3001 \u6620\u5c04\u8fd9\u4e9b\u8d85\u5927\u5377\u79ef\u5230\u6709\u6548\u7684\u786c\u4ef6\u4e0a\u6210\u4e3a\u4e86\u4e00\u4e2a\u503c\u5f97\u7814\u7a76\u7684\u65b9\u5411\uff0c<\/p>\n

\n\t\uff082\uff09\u66f4\u4f4e\u7684 Inference \u8ba1\u7b97\/\u5b58\u50a8\u4f4d\u5bbd<\/p>\n

\n\tAI \u82af\u7247\u6700\u5927\u7684\u6f14\u8fdb\u65b9\u5411\u4e4b\u4e00\u53ef\u80fd\u5c31\u662f\u795e\u7ecf\u7f51\u7edc\u53c2\u6570\/\u8ba1\u7b97\u4f4d\u5bbd\u7684\u8fc5\u901f\u51cf\u5c11——\u4ece 32 \u4f4d\u6d6e\u70b9\u5230 16 \u4f4d\u6d6e\u70b9\/\u5b9a\u70b9\u3001 8 \u4f4d\u5b9a\u70b9\uff0c\u751a\u81f3\u662f 4 \u4f4d\u5b9a\u70b9\u3002\u5728\u7406\u8bba\u8ba1\u7b97\u9886\u57df\uff0c 2 \u4f4d\u751a\u81f3 1 \u4f4d\u53c2\u6570\u4f4d\u5bbd\uff0c\u90fd\u5df2\u7ecf\u9010\u6e10\u8fdb\u5165\u5b9e\u8df5\u9886\u57df\u3002<\/p>\n

\n\t\uff083\uff09\u66f4\u591a\u6837\u7684\u5b58\u50a8\u5668\u5b9a\u5236\u8bbe\u8ba1<\/p>\n

\n\t\u5f53\u8ba1\u7b97\u90e8\u4ef6\u4e0d\u518d\u6210\u4e3a\u795e\u7ecf\u7f51\u7edc\u52a0\u901f\u5668\u7684\u8bbe\u8ba1\u74f6\u9888\u65f6\uff0c\u5982\u4f55\u51cf\u5c11\u5b58\u50a8\u5668\u7684\u8bbf\u95ee\u5ef6\u65f6\u5c06\u4f1a\u6210\u4e3a\u4e0b\u4e00\u4e2a\u7814\u7a76\u65b9\u5411\u3002\u901a\u5e38\uff0c\u79bb\u8ba1\u7b97\u8d8a\u8fd1\u7684\u5b58\u50a8\u5668\u901f\u5ea6\u8d8a\u5feb\uff0c\u6bcf\u5b57\u8282\u7684\u6210\u672c\u4e5f\u8d8a\u9ad8\uff0c\u540c\u65f6\u5bb9\u91cf\u4e5f\u8d8a\u53d7\u9650\uff0c\u56e0\u6b64\u65b0\u578b\u7684\u5b58\u50a8\u7ed3\u6784\u4e5f\u5c06\u5e94\u8fd0\u800c\u751f\u3002<\/p>\n

\n\t\uff084\uff09\u66f4\u7a00\u758f\u7684\u5927\u89c4\u6a21\u5411\u91cf\u5b9e\u73b0<\/p>\n

\n\t\u795e\u7ecf\u7f51\u7edc\u867d\u7136\u5927\uff0c\u4f46\u662f\uff0c\u5b9e\u9645\u4e0a\u6709\u5f88\u591a\u4ee5\u96f6\u4e3a\u8f93\u5165\u7684\u60c5\u51b5\uff0c \u6b64\u65f6\u7a00\u758f\u8ba1\u7b97\u53ef\u4ee5\u9ad8\u6548\u7684\u51cf\u5c11\u65e0\u7528\u80fd\u6548\u3002\u6765\u81ea\u54c8\u4f5b\u5927\u5b66\u7684\u56e2\u961f\u5c31\u8be5\u95ee\u9898\u63d0\u51fa\u4e86\u4f18\u5316\u7684\u4e94\u7ea7\u6d41\u6c34\u7ebf\u7ed3\uff0c\u5728\u6700\u540e\u4e00\u7ea7\u8f93\u51fa\u4e86\u89e6\u53d1\u4fe1\u53f7\u3002\u5728 Activation\u5c42\u540e\u5bf9\u4e0b\u4e00\u6b21\u8ba1\u7b97\u7684\u5fc5\u8981\u6027\u8fdb\u884c\u9884\u5148\u5224\u65ad\uff0c\u5982\u679c\u53d1\u73b0\u8fd9\u662f\u4e00\u4e2a\u7a00\u758f\u8282\u70b9\uff0c\u5219\u89e6\u53d1 SKIP \u4fe1\u53f7\uff0c\u907f\u514d\u4e58\u6cd5\u8fd0\u7b97\u7684\u529f\u8017\uff0c\u4ee5\u8fbe\u5230\u51cf\u5c11\u65e0\u7528\u529f\u8017\u7684\u76ee\u7684\u3002<\/p>\n

\n\t\uff085\uff09\u8ba1\u7b97\u548c\u5b58\u50a8\u4e00\u4f53\u5316<\/p>\n

\n\t\u8ba1\u7b97\u548c\u5b58\u50a8\u4e00\u4f53\u5316\uff08process-in-memory\uff09\u6280\u672f\uff0c\u5176\u8981\u70b9\u662f\u901a\u8fc7\u4f7f\u7528\u65b0\u578b\u975e\u6613\u5931\u6027\u5b58\u50a8\uff08\u5982 ReRAM<\/u>\uff09\u5668\u4ef6\uff0c\u5728\u5b58\u50a8\u9635\u5217\u91cc\u9762\u52a0\u4e0a\u795e\u7ecf\u7f51\u7edc\u8ba1\u7b97\u529f\u80fd\uff0c\u4ece\u800c\u7701\u53bb\u6570\u636e\u642c\u79fb\u64cd\u4f5c\uff0c\u5373\u5b9e\u73b0\u4e86\u8ba1\u7b97\u5b58\u50a8\u4e00\u4f53\u5316\u7684\u795e\u7ecf\u7f51\u7edc\u5904\u7406\uff0c\u5728\u529f\u8017\u6027\u80fd\u65b9\u9762\u53ef\u4ee5\u83b7\u5f97\u663e\u8457\u63d0\u5347\u3002<\/p>\n

\n\t\u7ed3\u5c3e\uff1a<\/p>\n

\n\t<\/p>\n

\n\t\u8fd1\u51e0\u5e74\uff0cAI\u6280\u672f\u4e0d\u65ad\u53d6\u5f97\u7a81\u7834\u6027\u8fdb\u5c55\u3002\u4f5c\u4e3aAI\u6280\u672f\u7684\u91cd\u8981\u7269\u7406\u57fa\u7840\uff0cAI\u82af\u7247\u62e5\u6709\u5de8\u5927\u7684\u4ea7\u4e1a\u4ef7\u503c\u548c\u6218\u7565\u5730\u4f4d\u3002<\/p>\n

\n\t\u4f46\u4ece\u5927\u8d8b\u52bf\u6765\u770b\uff0c\u76ee\u524d\u5c1a\u5904\u4e8eAI\u82af\u7247\u53d1\u5c55\u7684\u521d\u7ea7\u9636\u6bb5\uff0c\u65e0\u8bba\u662f\u79d1\u7814\u8fd8\u662f\u4ea7\u4e1a\u5e94\u7528\u90fd\u6709\u5de8\u5927\u7684\u521b\u65b0\u7a7a\u95f4\u3002<\/p>\n

\n\t\u73b0\u5728\u4e0d\u4ec5\u82f1\u4f1f\u8fbe\u3001\u8c37\u6b4c\u7b49\u56fd\u9645\u5de8\u5934\u76f8\u7ee7\u63a8\u51fa\u65b0\u4ea7\u54c1\uff0c\u56fd\u5185\u767e\u5ea6\u3001\u963f\u91cc\u7b49\u7eb7\u7eb7\u5e03\u5c40\u8fd9\u4e00\u9886\u57df\uff0c\u4e5f\u8bde\u751f\u4e86\u5bd2\u6b66\u7eaa\u7b49AI\u82af\u7247\u521b\u4e1a\u516c\u53f8\u3002<\/p>\n

\n\t\u5728CPU\u3001GPU\u7b49\u4f20\u7edf\u82af\u7247\u9886\u57df\u4e0e\u56fd\u9645\u76f8\u5dee\u8f83\u591a\u7684\u60c5\u51b5\u4e0b\uff0c\u4e2d\u56fdAI\u82af\u7247\u88ab\u5bc4\u671b\u80fd\u5b9e\u73b0\u5f2f\u9053\u8d85\u8f66\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

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