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\u6587\u7ae0\u6765\u6e90\u4e8e\u4e92\u8054\u7f51:\u8bba\u6587\u8363\u767b\u8ba1\u7b97\u673a\u4f53\u7cfb\u7ed3\u6784\u9876\u4f1aISCA\uff0c\u82af\u7247\u67b6\u6784\u6210\u4e3a\u8fb9\u7f18AI\u6700\u4f73\u5e76\u884c\u8ba1\u7b97\u9009\u62e9<\/a><\/p>\n

AI \u5927\u6a21\u578b\u7684\u7206\u53d1\u5e26\u52a8\u4e86 GPU \u7684\u5f3a\u52b2\u9700\u6c42\uff0c\u4ece\u4e91\u7aef\u5230\u8fb9\u7f18\u6e17\u900f\u7684 AI \u5e94\u7528\u4e5f\u5c06\u5e26\u52a8\u8fb9\u7f18 AI \u670d\u52a1\u5668\u53ca\u52a0\u901f\u5904\u7406\u5668\u7684\u9700\u6c42\u3002\u901a\u8fc7\u5bf9\u6bd4 GPGPU\u3001FPGA\u3001NPU \u548c ASIC\uff0c\u53ef\u91cd\u6784\u8ba1\u7b97\u67b6\u6784<\/mark> CGRA \u6210\u4e3a\u6700\u9002\u5408\u8fb9\u7f18 AI \u7684\u5e76\u884c\u8ba1\u7b97\u67b6\u6784\u3002\u7531\u82af\u52a8\u529b\u63d0\u51fa\u7684\u53ef\u91cd\u6784\u5e76\u884c\u5904\u7406\u5668\uff08RPP\uff09\u662f\u6bd4\u4f20\u7edf CGRA \u66f4\u9002\u5408\u5927\u89c4\u6a21\u5e76\u884c\u5904\u7406\u7684\u8ba1\u7b97\u67b6\u6784\uff0c\u8fd9\u4e0d\u4f46\u901a\u8fc7\u8bd5\u9a8c\u8bc4\u6d4b\u5f97\u5230\u8bc1\u5b9e\uff0c\u800c\u4e14\u4e5f\u901a\u8fc7 ISCA \u4f1a\u8bae\u5f97\u5230\u56fd\u9645\u5b66\u672f\u6743\u5a01\u7684\u8ba4\u53ef\u3002\u57fa\u4e8e RPP \u67b6\u6784\u7684 R8 \u82af\u7247\u53ca\u540e\u7eed\u66f4\u9ad8\u6027\u80fd\u7684\u8fed\u4ee3\u82af\u7247\u5c06\u662f\u8fb9\u7f18 AI \u670d\u52a1\u5668\u548c AI PC \u7684\u7406\u60f3 AI \u52a0\u901f\u5904\u7406\u5668\u9009\u62e9\u3002<\/p>\n

\u76ee\u5f55<\/strong><\/p>\n

\u4e00\u3001\u4ec0\u4e48\u662f\u8fb9\u7f18 AI\uff1f<\/p>\n

\u4e8c\u3001\u8fb9\u7f18 AI \u670d\u52a1\u5668\u5e02\u573a\u8d8b\u52bf<\/p>\n

\u4e09\u3001\u9002\u5408\u8fb9\u7f18 AI \u7684\u7406\u60f3\u8ba1\u7b97\u67b6\u6784<\/p>\n

\u56db\u3001RPP \u67b6\u6784\u8be6\u89e3<\/p>\n

\u4e94\u3001RPP \u5904\u7406\u5668 R8 \u80fd\u6548\u5bf9\u6bd4<\/p>\n

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\u4e03\u3001\u7ed3\u8bed<\/p>\n

\u4e00\u3001\u4ec0\u4e48\u662f\u8fb9\u7f18 AI\uff1f<\/strong><\/p>\n

\u8fb9\u7f18 AI\uff08AI Edge\uff09\u662f\u4eba\u5de5\u667a\u80fd<\/mark> (AI) \u4e0e\u8fb9\u7f18\u8ba1\u7b97<\/mark>\u4ea4\u53c9\u7684\u5148\u8fdb\u6280\u672f\uff0c\u8fd9\u4e00\u6982\u5ff5\u6e90\u4e8e AI \u4ece\u4e91\u7aef\u5411\u8fb9\u7f18\u4e0b\u6c89\u7684\u5206\u5e03\u5f0f\u8ba1\u7b97\u8303\u5f0f\u8f6c\u53d8\u3002\u8fb9\u7f18 AI \u7684\u6838\u5fc3\u662f\u5c06 AI \u7b97\u6cd5\u76f4\u63a5\u5d4c\u5165\u5230\u4ea7\u751f\u5927\u91cf\u6570\u636e\u7684\u672c\u5730\u73af\u5883\u4e2d\uff0c\u4f8b\u5982\u667a\u80fd\u624b\u673a\u3001\u7269\u8054\u7f51\u8bbe\u5907\u6216\u672c\u5730\u670d\u52a1\u5668\uff0c\u901a\u8fc7\u4f4d\u4e8e\u7f51\u7edc \u201c\u8fb9\u7f18\u201d\uff08\u5373\u66f4\u9760\u8fd1\u6570\u636e\u6e90\uff09\u7684\u8bbe\u5907\u548c\u7cfb\u7edf\u8fdb\u884c\u5b9e\u65f6\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u3002<\/p>\n

\u76f8\u5bf9\u4e8e\u4f20\u7edf\u7684\u6570\u636e\u4e2d\u5fc3\u6216\u4e91\u8ba1\u7b97<\/mark>\u5e73\u53f0\u7684 AI \u8bad\u7ec3\u6216\u63a8\u7406\uff0c\u8fb9\u7f18 AI \u7684\u4e3b\u8981\u4f18\u52bf\u5728\u4e8e \u201c\u5c31\u5730\u5904\u7406\u201d\uff0c\u5927\u5927\u51cf\u5c11\u4e86\u6570\u636e\u4f20\u8f93\u548c\u5904\u7406\u7684\u5ef6\u8fdf\uff0c\u8fd9\u5728\u667a\u80fd\u76d1\u63a7\u3001\u81ea\u52a8\u9a7e\u9a76\u3001\u5b9e\u65f6\u533b\u7597\u8bca\u65ad\u6216\u5de5\u4e1a\u81ea\u52a8\u5316\u63a7\u5236\u7b49\u5e94\u7528\u573a\u666f\u4e2d\u5c24\u5176\u91cd\u8981\u3002<\/p>\n

\u5b9e\u73b0\u8fb9\u7f18 AI \u8ba1\u7b97\u7684\u8bbe\u5907\u548c\u7cfb\u7edf\u4e3b\u8981\u5305\u62ec\uff1a<\/p>\n

    \n
  1. \n

    \u667a\u80fd\u7ec8\u7aef\uff1a\u4e3b\u8981\u7528\u4e8e\u4ea7\u751f\u6216\u6536\u96c6\u6570\u636e\u7684\u8bbe\u5907\uff0c\u5982\u667a\u80fd\u4f20\u611f\u5668\u3001\u667a\u80fd\u624b\u673a\u3001AI PC \u6216\u7269\u8054\u7f51\u8bbe\u5907\u7b49\uff1b<\/p>\n<\/li>\n

  2. \n

    \u8fb9\u7f18 AI \u670d\u52a1\u5668\uff1a\u76f4\u63a5\u5bf9\u6240\u6536\u96c6\u6570\u636e\u8fdb\u884c\u5904\u7406\u548c\u5206\u6790\u7684\u8fb9\u7f18\u8bbe\u5907\u53ca\u8f6f\u786c\u4ef6\u7cfb\u7edf\uff0c\u6bd4\u5982\u4e13\u7528\u7684\u5927\u8bed\u8a00\u6a21\u578b<\/mark>\uff08LLM\uff09AI \u63a8\u7406\u670d\u52a1\u5668\u3001\u667a\u80fd\u9a7e\u9a76\u533a\u57df\u8ba1\u7b97\u4e2d\u5fc3\u670d\u52a1\u5668\u7b49\uff1b<\/p>\n<\/li>\n

  3. \n

    \u901a\u4fe1\u7f51\u7edc\u8bbe\u5907\uff1a\u5c3d\u7ba1\u8fb9\u7f18 AI \u5e94\u7528\u5bf9\u901a\u4fe1\u7f51\u7edc\u7684\u5e26\u5bbd\u548c\u901f\u7387\u8981\u6c42\u6ca1\u6709\u4e91\u7aef\u90a3\u4e48\u9ad8\uff0c\u4f46\u4e5f\u5fc5\u987b\u63d0\u4f9b\u53ef\u9760\u7684\u9ad8\u901f\u8fde\u63a5\u624d\u80fd\u8fbe\u5230\u8fb9\u7f18 AI \u6240\u9700\u7684\u4f4e\u5ef6\u8fdf\u548c\u5b9e\u65f6\u6027\u8981\u6c42\u3002<\/p>\n<\/li>\n<\/ol>\n

    \u672c\u6587\u4e3b\u8981\u8ba8\u8bba\u8fb9\u7f18 AI \u670d\u52a1\u5668\u53ca\u5176\u5e02\u573a\u53d1\u5c55\u8d8b\u52bf\u3001\u5bf9 AI \u52a0\u901f\u5904\u7406\u5668\u7684\u8981\u6c42\uff0c\u4ee5\u53ca\u9002\u5408\u8fb9\u7f18 AI \u5e94\u7528\u7684\u5e76\u884c\u8ba1\u7b97\u67b6\u6784\u548c\u5904\u7406\u5668\u5b9e\u73b0\u3002<\/p>\n

    \u4e8c\u3001\u8fb9\u7f18 AI \u670d\u52a1\u5668\u5e02\u573a\u8d8b\u52bf<\/strong><\/p>\n

    AI \u670d\u52a1\u5668\u662f\u6307\u4e13\u4e3a\u4eba\u5de5\u667a\u80fd<\/mark>\u5e94\u7528\u800c\u8bbe\u8ba1\u7684\u9ad8\u6027\u80fd\u8ba1\u7b97\u673a\u8bbe\u5907\uff0c\u80fd\u591f\u652f\u6301\u5927\u89c4\u6a21\u6570\u636e\u5904\u7406\u3001\u6a21\u578b\u8bad\u7ec3\u3001\u63a8\u7406\u8ba1\u7b97\u7b49\u590d\u6742\u4efb\u52a1\u3002AI \u670d\u52a1\u5668\u901a\u5e38\u914d\u5907\u9ad8\u6027\u80fd\u7684\u5904\u7406\u5668\u3001\u9ad8\u901f\u5185\u5b58\u3001\u5927\u5bb9\u91cf\u9ad8\u901f\u5b58\u50a8\u7cfb\u7edf\uff0c\u4ee5\u53ca\u9ad8\u6548\u7684\u6563\u70ed\u7cfb\u7edf\uff0c\u4ee5\u6ee1\u8db3 AI \u7b97\u6cd5\u5bf9\u8ba1\u7b97\u8d44\u6e90\u7684\u6781\u9ad8\u9700\u6c42\u3002\u6309\u4e0d\u540c\u7684\u5206\u7c7b\u6807\u51c6\uff0cAI \u670d\u52a1\u5668\u53ef\u4ee5\u5927\u81f4\u5206\u4e3a\u8bad\u7ec3\u670d\u52a1\u5668\u3001\u63a8\u7406\u670d\u52a1\u5668\u3001GPU \u670d\u52a1\u5668\u3001FPGA \u670d\u52a1\u5668\u3001CPU \u670d\u52a1\u5668\u3001\u4e91\u7aef AI \u670d\u52a1\u5668\uff0c\u4ee5\u53ca\u8fb9\u7f18 AI \u670d\u52a1\u5668\u7b49\u3002<\/p>\n

    \u636e Gartner \u9884\u6d4b\uff0c\u4ece\u73b0\u5728\u5230 2027 \u5e74\uff0cAI \u670d\u52a1\u5668\u5e02\u573a\u89c4\u6a21\u5c06\u4fdd\u6301\u9ad8\u901f\u589e\u957f\uff0c\u5e74\u590d\u5408\u589e\u957f\u7387\u9ad8\u8fbe 30%\u3002\u8be5\u673a\u6784\u53d1\u5e03\u7684\u300a2024 \u5e74\u7b2c\u4e00\u5b63\u5ea6\u5168\u7403\u670d\u52a1\u5668\u5e02\u573a\u62a5\u544a\u300b\u663e\u793a\uff0c\u4eca\u5e74 Q1 \u5168\u7403\u670d\u52a1\u5668\u5e02\u573a\u9500\u552e\u989d\u4e3a 407.5 \u4ebf\u7f8e\u5143\uff0c\u540c\u6bd4\u589e\u957f 59.9%\uff1b\u51fa\u8d27\u91cf\u4e3a 282.0 \u4e07\u53f0\uff0c\u540c\u6bd4\u589e\u957f 5.9%\u3002\u5728\u4f17\u591a AI \u670d\u52a1\u5668\u4f9b\u5e94\u5546\u4e2d\uff0c\u6d6a\u6f6e\u4fe1\u606f\u8749\u8054\u5168\u7403\u7b2c\u4e8c\uff0c\u4e2d\u56fd\u7b2c\u4e00\uff0c\u5176\u670d\u52a1\u5668\u51fa\u8d27\u91cf\u5728\u5168\u7403\u5e02\u573a\u5360\u6bd4 11.3%\uff0c\u540c\u6bd4\u589e\u957f 50.4%\uff0c\u5728 TOP5 \u5382\u5546\u4e2d\u589e\u901f\u7b2c\u4e00\u3002<\/p>\n

    \u53e6\u636e\u4e2d\u5546\u4ea7\u4e1a\u7814\u7a76\u9662\u53d1\u5e03\u7684\u300a2024-2029 \u5e74\u4e2d\u56fd\u670d\u52a1\u5668\u884c\u4e1a\u9700\u6c42\u9884\u6d4b\u53ca\u53d1\u5c55\u8d8b\u52bf\u524d\u77bb\u62a5\u544a\u300b\uff0c2022 \u5e74\u672b\uff0c\u56fd\u5185\u5e02\u573a\u603b\u89c4\u6a21\u8d85\u8fc7 420 \u4ebf\u5143\uff0c\u540c\u6bd4\u589e\u957f\u7ea6 20%\uff1b2023 \u5e74\u7ea6\u4e3a 490 \u4ebf\u5143\uff0c\u5e02\u573a\u589e\u901f\u9010\u6b65\u653e\u7f13\uff1b\u9884\u8ba1 2024 \u5e74\u5e02\u573a\u89c4\u6a21\u5c06\u8fbe 560 \u4ebf\u5143\u3002\u4ece\u51fa\u8d27\u91cf\u6765\u770b\uff0c2022 \u5e74\u4e2d\u56fd AI \u670d\u52a1\u5668\u5e02\u573a\u51fa\u8d27\u91cf\u7ea6 28.4 \u4e07\u53f0\uff0c\u540c\u6bd4\u589e\u957f\u7ea6 25.66%\uff1b2023 \u5e74\u7ea6\u4e3a 35.4 \u4e07\u53f0\uff0c\u9884\u8ba1 2024 \u5e74\u5c06\u8fbe\u5230 42.1 \u4e07\u53f0\u3002<\/p>\n

    \u5728 AI \u5927\u6a21\u578b\u53d1\u5c55\u65e9\u671f\uff0cAI \u670d\u52a1\u5668\u9700\u6c42\u4ee5\u6a21\u578b\u8bad\u7ec3\u4e3a\u4e3b\uff0c\u56e0\u800c\u8bad\u7ec3\u578b\u670d\u52a1\u5668\u5360\u636e\u5e02\u573a\u4e3b\u5bfc\u5730\u4f4d\u3002\u76ee\u524d\uff0cAI \u670d\u52a1\u5668\u5e02\u573a\u4e2d 57.33\uff05\u4e3a\u8bad\u7ec3\u578b\u670d\u52a1\u5668\uff0c\u63a8\u7406\u578b\u670d\u52a1\u5668\u5360\u6bd4\u8fbe 42.67%\u3002\u7136\u800c\uff0c\u968f\u7740\u751f\u6210\u5f0f AI \u5e94\u7528\u5f80\u8fb9\u7f18\u7aef\u6e17\u900f\uff0c\u9884\u8ba1\u672a\u6765\u63a8\u7406\u578b\u670d\u52a1\u5668\u5c06\u9010\u6e10\u6210\u4e3a\u5e02\u573a\u4e3b\u6d41\uff0c\u8fb9\u7f18 AI \u670d\u52a1\u5668\u4ece\u51fa\u8d27\u91cf\u4e0a\u5c06\u8d85\u8fc7\u4e91\u7aef\u8bad\u7ec3\u548c\u63a8\u7406\u670d\u52a1\u5668\u3002<\/p>\n

    IDC \u6700\u65b0\u53d1\u5e03\u7684\u300a\u4e2d\u56fd\u534a\u5e74\u5ea6\u8fb9\u7f18\u8ba1\u7b97<\/mark>\u5e02\u573a\uff082023 \u5168\u5e74\uff09\u8ddf\u8e2a\u300b\u62a5\u544a\u6570\u636e\u663e\u793a\uff0c2023 \u5e74\u4e2d\u56fd\u8fb9\u7f18\u8ba1\u7b97<\/mark>\u670d\u52a1\u5668\u5e02\u573a\u7ee7\u7eed\u4fdd\u6301\u7a33\u6b65\u4e0a\u5347\uff0c\u540c\u6bd4\u589e\u957f 29.1%\u3002IDC \u9884\u6d4b\uff0c\u5230 2028 \u5e74\uff0c\u4e2d\u56fd\u8fb9\u7f18\u8ba1\u7b97<\/mark>\u670d\u52a1\u5668\u5e02\u573a\u89c4\u6a21\u5c06\u8fbe\u5230 132 \u4ebf\u7f8e\u5143\u3002<\/p>\n

    <\/a><\/p>\n

    \u4f5c\u4e3a\u8fb9\u7f18\u8ba1\u7b97<\/mark>\u7684\u91cd\u8981\u7ec4\u6210\u90e8\u5206\uff0c2023 \u5e74\u5b9a\u5236\u8fb9\u7f18\u670d\u52a1\u5668\u89c4\u6a21\u5df2\u8fbe 2.4 \u4ebf\u7f8e\u5143\uff0c\u76f8\u8f83 2022 \u5e74\u589e\u957f 16.8%\u3002\u4ece\u5382\u5546\u9500\u552e\u989d\u89d2\u5ea6\u6765\u770b\uff0c\u8fb9\u7f18\u5b9a\u5236\u670d\u52a1\u5668\u5e02\u573a\u4e2d\u5360\u6bd4\u8f83\u5927\u7684\u5382\u5546\u5206\u522b\u662f\u6d6a\u6f6e\u4fe1\u606f\u3001\u8054\u60f3\u3001\u534e\u4e3a<\/mark>\u3001\u65b0\u534e\u4e09\u3002\u968f\u7740\u8fb9\u7f18\u8ba1\u7b97<\/mark>\u5e94\u7528\u7684\u591a\u6837\u5316\u53d1\u5c55\uff0c\u65b0\u5174\u670d\u52a1\u5668\u5382\u5546\u5728\u8f66\u8def\u534f\u540c\u3001\u8fb9\u7f18 AI \u548c\u667a\u80fd\u7ec8\u7aef\u7b49\u4e1a\u52a1\u573a\u666f\u548c\u5e94\u7528\u5e02\u573a\u5c06\u6709\u8f83\u5927\u7a81\u7834\uff0c\u4f7f\u5f97\u8fb9\u7f18\u670d\u52a1\u5668\u5e02\u573a\u5448\u73b0\u51fa\u591a\u6837\u5316\u683c\u5c40\u3002<\/p>\n

    \u4e09\u3001\u9002\u5408\u8fb9\u7f18 AI \u7684\u7406\u60f3\u8ba1\u7b97\u67b6\u6784<\/strong><\/p>\n

    PC \u65f6\u4ee3\u7531 WINTEL\uff08\u5fae\u8f6f Windows + \u82f1\u7279\u5c14<\/mark> CPU\uff09\u8054\u76df\u4e3b\u5bfc\u3001\u667a\u80fd\u624b\u673a\u65f6\u4ee3\u7531 Android+Arm \u8054\u76df\u4e3b\u5bfc\uff0cAI \u65f6\u4ee3\u5c06\u7531\u54ea\u4e2a\u8054\u76df\u4e3b\u5bfc\u5462\uff1f\u4e00\u4e2a\u65b0\u7684\u8054\u76df\u6b63\u521d\u9732\u7aef\u502a\uff0c\u90a3\u5c31\u662f\u7531\u82f1\u4f1f\u8fbe\u548c\u53f0\u79ef\u7535<\/mark>\u7ec4\u6210\u7684 NT \u8054\u76df\uff08Nvidia+TSMC\uff09\u3002\u636e\u534e\u5c14\u8857\u6295\u8d44\u4e13\u5bb6\u9884\u6d4b\uff0c2024 \u5e74 NT \u8054\u76df\u603b\u8425\u6536\u9884\u8ba1\u5c06\u8fbe\u5230 2000 \u4ebf\u7f8e\u5143\uff0c\u603b\u51c0\u5229\u6da6 1000 \u4ebf\u7f8e\u5143\uff0c\u603b\u5e02\u503c\u6709\u671b\u7a81\u7834 5 \u4e07\u4ebf\u7f8e\u5143\u3002\u7531\u4e91\u7aef AI \u8bad\u7ec3\u548c AI \u5927\u6a21\u578b\u5e94\u7528\u9a71\u52a8\u7684\u82f1\u4f1f\u8fbe GPU \u548c\u53f0\u79ef\u7535<\/mark> AI \u82af\u7247\u5236\u9020\u4e1a\u52a1\u5c06\u6210\u4e3a\u4eca\u5e74\u6700\u5927\u7684\u8d62\u5bb6\u3002<\/p>\n

    \u5c3d\u7ba1\u82f1\u4f1f\u8fbe\u5728\u4e91\u7aef AI \u8bad\u7ec3\u548c\u63a8\u7406\u5e02\u573a\u5360\u636e\u4e86\u7edd\u5bf9\u4e3b\u5bfc\u5730\u4f4d\uff0c\u4f46\u5728\u8fb9\u7f18 AI \u5e94\u7528\u573a\u666f\u4e2d\u82f1\u4f1f\u8fbe\u7684 GPGPU \u5374\u4e0d\u662f\u6700\u4f73\u9009\u62e9\uff0c\u56e0\u4e3a\u5176\u8ba1\u7b97\u67b6\u6784\u56fa\u6709\u7684\u9ad8\u529f\u8017\u548c\u9ad8\u6210\u672c\u95ee\u9898\u9650\u5236\u4e86\u5176\u5728\u66f4\u4e3a\u5e7f\u6cdb\u800c\u5206\u6563\u7684\u8fb9\u7f18 AI \u5e94\u7528\u4e2d\u7684\u4f5c\u7528\u3002\u8ba1\u7b97\u673a\u67b6\u6784\u9886\u57df\u7684\u5b66\u8005\u4e13\u5bb6\u90fd\u5728\u5bfb\u6c42\u80fd\u591f\u66ff\u4ee3 GPGPU \u7684\u9ad8\u80fd\u6548\u5e76\u884c\u6280\u672f\u67b6\u6784\uff0c\u57fa\u4e8e\u7279\u5b9a\u57df\u4e13\u7528\u67b6\u6784\uff08DSA\uff09\u7684 ASIC \u8bbe\u8ba1\u662f\u4e00\u79cd\u53ef\u884c\u7684\u5173\u952e\u601d\u8def\uff0c\u6bd4\u5982\u8c37\u6b4c\u7684\u5f20\u91cf<\/mark>\u5904\u7406\u5355\u5143 (TPU) \uff0c\u8fd9\u79cd\u4e13\u4e3a\u52a0\u901f\u673a\u5668\u5b66\u4e60<\/mark>\u5de5\u4f5c\u8d1f\u8f7d\u800c\u8bbe\u8ba1\u7684\u5904\u7406\u5668\u91c7\u7528\u8109\u52a8\u9635\u5217\u67b6\u6784\uff0c\u53ef\u9ad8\u6548\u6267\u884c\u4e58\u6cd5\u548c\u7d2f\u52a0\u8fd0\u7b97\uff0c\u4e3b\u8981\u9762\u5411\u6570\u636e\u4e2d\u5fc3\u5e94\u7528\u3002\u53e6\u5916\u4e00\u4e2a\u601d\u8def\u662f\u4ee5\u4e09\u661f\u4e3a\u4ee3\u8868\u7684\u795e\u7ecf\u5904\u7406\u5355\u5143 (NPU) \uff0c\u5b83\u4e13\u4e3a\u79fb\u52a8\u573a\u666f\u800c\u8bbe\u8ba1\uff0c\u5177\u6709\u8282\u80fd\u7684\u5185\u79ef\u5f15\u64ce\uff0c\u53ef\u5229\u7528\u8f93\u5165\u7279\u5f81\u56fe\u7a00\u758f\u6027\u6765\u4f18\u5316\u6df1\u5ea6\u5b66\u4e60<\/mark>\u63a8\u7406\u7684\u6027\u80fd\u3002<\/p>\n

    \u867d\u7136 TPU \u548c NPU \u90fd\u80fd\u591f\u63d0\u4f9b\u90e8\u5206\u66ff\u4ee3 GPGPU \u7684\u9ad8\u6027\u80fd\u548c\u8282\u80fd\u89e3\u51b3\u65b9\u6848\uff0c\u4f46\u5b83\u4eec\u7684\u4e13\u7528\u8bbe\u8ba1\u5c5e\u6027\u9650\u5236\u4e86\u5176\u591a\u529f\u80fd\u6027\u548c\u5e7f\u6cdb\u7684\u9002\u7528\u6027\u3002\u603b\u90e8\u4f4d\u4e8e\u7f8e\u56fd\u52a0\u5dde\u4e14\u5728\u53f0\u6e7e\u548c\u5927\u9646\u90fd\u6709\u7814\u53d1\u4e2d\u5fc3\u7684\u8fb9\u7f18 AI \u82af\u7247\u521d\u521b\u516c\u53f8\u8010\u80fd\uff08Kneron\uff09\u63d0\u51fa\u4e86\u53ef\u91cd\u6784 NPU \u7684\u65b9\u6848\uff0c\u4f7f\u5f97 NPU \u82af\u7247\u6709 ASIC \u9ad8\u6027\u80fd\u800c\u53c8\u4e0d\u727a\u7272\u6570\u636e\u5bc6\u96c6\u578b\u7b97\u6cd5\u7684\u53ef\u7f16\u7a0b\u6027\u3002\u51ed\u501f\u72ec\u7279\u521b\u65b0\u7684\u67b6\u6784\u548c\u4f18\u5f02\u7684\u6027\u80fd\uff0c\u8010\u80fd\u56e2\u961f\u83b7\u5f97 IEEE CAS 2021 \u5e74 Darlington \u6700\u4f73\u8bba\u6587\u5956\u3002\u8010\u80fd\u7b2c 4 \u4ee3\u53ef\u91cd\u6784 NPU \u53ef\u4ee5\u652f\u6301\u540c\u65f6\u8fd0\u884c CNN \u548c Transformer \u7f51\u7edc\uff0c\u65e2\u53ef\u505a\u673a\u5668\u89c6\u89c9<\/mark>\uff0c\u4e5f\u53ef\u8fd0\u884c\u8bed\u4e49\u5206\u6790<\/mark>\u3002\u4e0e\u4ec5\u9762\u5411\u7279\u5b9a\u5e94\u7528\u7684\u666e\u901a AI \u6a21\u578b\u4e0d\u540c\uff0c\u8010\u80fd\u7684\u53ef\u91cd\u6784\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\uff08RANN\uff09\u6280\u672f\u66f4\u52a0\u7075\u6d3b\uff0c\u53ef\u6ee1\u8db3\u4e0d\u540c\u5e94\u7528\u9700\u6c42\u5e76\u9002\u5e94\u5404\u79cd\u8ba1\u7b97\u4f53\u7cfb\u67b6\u6784\u3002\u636e\u8be5\u516c\u53f8\u5ba3\u79f0\uff0c\u5176\u8fb9\u7f18 GPT AI \u82af\u7247 KL830 \u53ef\u5e94\u7528\u4e8e AI PC\u3001USB \u52a0\u901f\u68d2\u548c\u8fb9\u7f18\u670d\u52a1\u5668\uff0c\u5f53\u4e0e GPU \u914d\u5408\u4f7f\u7528\u65f6\uff0cNPU \u53ef\u5c06\u8bbe\u5907\u80fd\u8017\u964d\u4f4e 30%\u3002<\/p>\n

    \u53ef\u91cd\u6784\u786c\u4ef6\u662f\u53e6\u4e00\u79cd\u53ef\u63d0\u4f9b\u9ad8\u6027\u80fd\u548c\u8282\u80fd\u8ba1\u7b97\u7684\u89e3\u51b3\u65b9\u6848\uff0c\u73b0\u573a\u53ef\u7f16\u7a0b\u95e8\u9635\u5217<\/mark> (FPGA) \u662f\u53ef\u91cd\u6784\u786c\u4ef6\u8ba1\u7b97\u7684\u4ee3\u8868\uff0c\u5176\u7279\u70b9\u662f\u7ec6\u7c92\u5ea6\u53ef\u91cd\u6784\u6027\u3002FPGA \u5229\u7528\u5177\u6709\u53ef\u7f16\u7a0b\u4e92\u8fde\u7684\u53ef\u914d\u7f6e\u903b\u8f91<\/mark>\u5757\u6765\u5b9e\u73b0\u81ea\u5b9a\u4e49\u8ba1\u7b97\u5185\u6838\u3002\u8fd9\u79cd\u5b9a\u5236\u7684\u8ba1\u7b97\u80fd\u529b\u4f7f\u5f97\u57fa\u4e8e FPGA \u7684\u52a0\u901f\u5668\u80fd\u591f\u90e8\u7f72\u5728\u91d1\u878d\u8ba1\u7b97\u3001\u6df1\u5ea6\u5b66\u4e60<\/mark>\u548c\u79d1\u5b66\u4eff\u771f\u7b49\u5e7f\u6cdb\u7684\u5927\u89c4\u6a21\u8ba1\u7b97\u5e94\u7528\u4e2d\u3002\u7136\u800c\uff0cFPGA \u63d0\u4f9b\u7684\u4f4d\u7ea7\u53ef\u91cd\u6784\u6027\u4f1a\u5e26\u6765\u660e\u663e\u7684\u9762\u79ef\u548c\u529f\u7387\u989d\u5916\u5f00\u9500\uff0c\u800c\u4e14\u6ca1\u6709\u89c4\u6a21\u6210\u672c\u6548\u76ca\uff0c\u8fd9\u6781\u5927\u5730\u9650\u5236\u4e86\u5176\u5728\u9700\u8981\u4f4e\u529f\u8017\u548c\u5c0f\u5c3a\u5bf8\u7684\u5e94\u7528\u573a\u666f\u4e2d\u7684\u9002\u7528\u6027\u3002<\/p>\n

    \u7c97\u7c92\u5ea6\u53ef\u91cd\u6784\u67b6\u6784 (CGRA) \u4ee3\u8868\u53e6\u4e00\u7c7b\u53ef\u91cd\u6784\u786c\u4ef6\u3002\u4e0e FPGA \u76f8\u6bd4\uff0cCGRA \u63d0\u4f9b\u7c97\u7c92\u5ea6\u7684\u53ef\u91cd\u6784\u6027\uff0c\u4f8b\u5982\u5b57\u7ea7\u53ef\u91cd\u6784\u529f\u80fd\u5355\u5143\u3002\u7531\u4e8e CGRA \u5185\u90e8\u7684 ALU \u6a21\u5757\u5df2\u7ecf\u6784\u5efa\u5b8c\u6210\uff0c\u4e14\u5176\u4e92\u8054\u4e5f\u8981\u6bd4 FPGA \u66f4\u7b80\u5355\u3001\u89c4\u6a21\u66f4\u5c0f\uff0c\u56e0\u6b64\u5176\u5ef6\u65f6\u548c\u6027\u80fd\u8981\u663e\u8457\u597d\u4e8e\u5728\u95e8\u7ea7\u4e0a\u8fdb\u884c\u4e92\u8fde\u5f62\u6210\u7ec4\u5408\u8ba1\u7b97\u903b\u8f91<\/mark>\u7684 FPGA\u3002CGRA \u66f4\u9002\u5408 word-wise \u7c7b\u578b (32bit \u4e3a\u5355\u4f4d) \u7684\u53ef\u91cd\u6784\u8ba1\u7b97\uff0c\u800c\u4e14\u53ef\u4ee5\u7f13\u89e3 FPGA \u5b58\u5728\u7684\u65f6\u5e8f\u3001\u9762\u79ef\u548c\u529f\u7387\u5f00\u9500\u95ee\u9898\uff0c\u662f\u672a\u6765\u8fb9\u7f18 AI \u7684\u7406\u60f3\u9ad8\u6027\u80fd\u5e76\u884c\u8ba1\u7b97\u67b6\u6784\u3002<\/p>\n

    \u4e0b\u9762\u6211\u4eec\u5927\u81f4\u68b3\u7406\u4e00\u4e0b CGRA \u7684\u53d1\u5c55\u5386\u7a0b\uff1a<\/p>\n

      \n
    1. \n

      \u65e9\u5728 1991 \u5e74\uff0c\u56fd\u9645\u5b66\u672f\u754c\u5c31\u5f00\u542f\u4e86\u53ef\u91cd\u6784\u82af\u7247\u7684\u7814\u7a76\uff1b<\/p>\n<\/li>\n

    2. \n

      2003 \u5e74\uff0c\u6b27\u6d32\u5b87\u822a\u9632\u52a1\u96c6\u56e2 (EADS) \u7387\u5148\u5728\u536b\u661f\u4e0a\u91c7\u7528\u53ef\u91cd\u6784\u8ba1\u7b97\u82af\u7247\uff1b<\/p>\n<\/li>\n

    3. \n

      2004 \u5e74\uff0c\u6b27\u6d32 IMEC \u63d0\u51fa\u52a8\u6001\u53ef\u91cd\u6784\u7ed3\u6784 ADRES\uff0c\u5728\u4e09\u661f\u7684\u751f\u7269\u533b\u7597\u3001\u9ad8\u6e05\u7535\u89c6\u7b49\u7cfb\u5217\u4ea7\u54c1\u4e2d\u5f97\u5230\u5e94\u7528\uff0c\u65e5\u672c\u7684\u745e\u8428\u79d1\u6280\u4e5f\u91c7\u7528\u8fd9\u79cd\u67b6\u6784\u3002<\/p>\n<\/li>\n

    4. \n

      2006 \u5e74\uff0c\u6e05\u534e\u5927\u5b66<\/mark>\u5fae\u7535\u5b50\u6240\u9b4f\u5c11\u519b<\/mark>\u6559\u6388\u5e26\u9886\u7684\u53ef\u91cd\u6784\u8ba1\u7b97\u56e2\u961f\u5f00\u59cb\u8fdb\u884c\u53ef\u91cd\u6784\u8ba1\u7b97\u7406\u8bba\u548c\u67b6\u6784\u7814\u7a76\uff1b<\/p>\n<\/li>\n

    5. \n

      2017 \u5e74\uff0c\u7f8e\u56fd\u56fd\u9632\u9ad8\u7ea7\u7814\u7a76\u8ba1\u5212\u5c40\uff08DARPA\uff09\u5ba3\u5e03\u542f\u52a8\u7535\u5b50\u590d\u5174\u8ba1\u5212\uff08Electronics Resurgence Initiative\uff0c\u7b80\u79f0 ERI\uff09\uff0c\u5c06 \u201c\u53ef\u91cd\u6784\u8ba1\u7b97\u201d \u6280\u672f\u5217\u4e3a\u7f8e\u56fd\u672a\u6765 30 \u5e74\u7684\u6218\u7565\u6280\u672f\u4e4b\u4e00\uff1b<\/p>\n<\/li>\n

    6. \n

      2018 \u5e74\uff0c\u57fa\u4e8e\u6e05\u534e\u5927\u5b66<\/mark>\u53ef\u91cd\u6784\u8ba1\u7b97\u6280\u672f\u7684\u6e05\u5fae\u667a\u80fd\u6210\u7acb\uff0c\u6b63\u5f0f\u5f00\u542f\u5546\u4e1a\u5316\u8fdb\u7a0b\u30022019 \u5e74\uff0c\u6e05\u5fae\u667a\u80fd\u91cf\u4ea7\u5168\u7403\u7b2c\u4e00\u6b3e\u53ef\u91cd\u6784\u667a\u80fd\u8bed\u97f3\u82af\u7247 TX210\uff0c\u8bc1\u660e\u4e86\u53ef\u91cd\u6784\u8ba1\u7b97\u7684\u5546\u4e1a\u4ef7\u503c\u30022020 \u5e74\uff0c\u6e05\u5fae\u667a\u80fd\u83b7\u5f97\u4e2d\u56fd\u7535\u5b50\u5b66\u4f1a\u6280\u672f\u53d1\u660e\u4e00\u7b49\u5956\uff1b2023 \u5e74\uff0c\u56fd\u5bb6\u5927\u57fa\u91d1\u4e8c\u671f\u6295\u8d44\u6e05\u5fae\u667a\u80fd\u3002\u76ee\u524d\uff0c\u6e05\u5fae\u667a\u80fd\u5171\u6709\u8fb9\u7f18\u7aef TX2\u3001TX5 \u7cfb\u5217\u82af\u7247\uff0c\u4ee5\u53ca\u7528\u4e8e\u670d\u52a1\u5668\u9886\u57df\u7684 TX8 \u7cfb\u5217\u4e09\u5927\u82af\u7247\u4ea7\u54c1\u3002\u5176\u4e2d\uff0cTX2 \u548c TX5 \u7cfb\u5217\u82af\u7247\u5df2\u5e94\u7528\u4e8e\u667a\u80fd\u5b89\u9632\u3001\u91d1\u878d\u652f\u4ed8\u3001\u667a\u80fd\u7a7f\u6234\uff0c\u667a\u80fd\u673a\u5668\u4eba\u7b49\u591a\u4e2a\u9886\u57df\uff1b\u9762\u5411\u4e91\u7aef\u5e02\u573a\u7684 TX8 \u9ad8\u7b97\u529b\u82af\u7247\u4e3b\u8981\u5e94\u7528\u573a\u666f\u662f AI \u5927\u6a21\u578b\u7684\u8bad\u7ec3\u548c\u63a8\u7406\u3002<\/p>\n<\/li>\n

    7. \n

      \u56fd\u5185\u53e6\u4e00\u5bb6\u57fa\u4e8e\u53ef\u91cd\u6784\u8ba1\u7b97\u6280\u672f\u7684 AI \u82af\u7247\u521d\u521b\u516c\u53f8\u73e0\u6d77\u82af\u52a8\u529b\u4e8e 2017 \u5e74\u6210\u7acb\uff0c\u5176\u53ef\u91cd\u6784\u5e76\u884c\u5904\u7406\u5668\uff08RPP\uff09\u67b6\u6784\u662f\u6539\u8fdb\u7248\u7684 CGRA\u30022021 \u5e74\u9996\u9897\u82af\u7247 RPP-R8 \u6210\u529f\u6d41\u7247\uff0c2023 \u5e74\u8fdb\u5165\u91d1\u878d\u8ba1\u7b97\u3001\u5de5\u4e1a\u6444\u50cf\u548c\u673a\u5668\u4eba\u7b49\u8fb9\u7f18 AI \u5e94\u7528\u5e02\u573a\uff0c\u5e76\u4e0e\u6d6a\u6f6e\u4fe1\u606f\u8fbe\u6210\u6218\u7565\u5408\u4f5c\u8fdb\u5165\u8fb9\u7f18 AI \u670d\u52a1\u5668\u5e02\u573a\u3002<\/p>\n<\/li>\n<\/ol>\n

      \u56fd\u9645\u8ba1\u7b97\u673a\u5b66\u672f\u754c\u548c\u9ad8\u79d1\u6280\u4ea7\u4e1a\u754c\u5df2\u5f62\u6210\u5171\u8bc6\uff0c\u57fa\u4e8e CGRA \u67b6\u6784\u7684\u53ef\u91cd\u6784\u8ba1\u7b97\u82af\u7247\u5177\u5907\u5e7f\u6cdb\u7684\u901a\u7528\u8ba1\u7b97\u80fd\u529b\uff0c\u53ef\u4ee5\u5e94\u7528\u4e8e\u5404\u79cd\u8fb9\u7f18 AI \u8ba1\u7b97\u573a\u666f\uff0c\u662f\u89e3\u51b3\u901a\u7528\u9ad8\u7b97\u529b\u548c\u4f4e\u529f\u8017\u9700\u6c42\u7684\u5fc5\u7531\u4e4b\u8def\u3002<\/p>\n

      \u56db\u3001RPP \u5904\u7406\u5668\u67b6\u6784\u8be6\u89e3<\/strong><\/p>\n

      RPP \u548c CGRA \u90fd\u662f\u5c5e\u4e8e\u7c97\u7c92\u5ea6\u7684\u53ef\u91cd\u6784\u9635\u5217\uff0c\u90fd\u53ef\u4ee5\u8fbe\u5230\u7c7b\u4f3c ASIC \u7684\u9762\u79ef\u5bc6\u5ea6\u548c\u529f\u7387\u6548\u7387\uff0c\u800c\u4e14\u90fd\u662f\u53ef\u4ee5\u7528\u8f6f\u4ef6\u7f16\u7a0b\u7684\u3002\u4f46\u662f\uff0cRPP \u5728\u53ef\u91cd\u6784\u7c7b\u578b\u548c\u7f16\u7a0b\u6a21\u578b\u65b9\u9762\u8ddf CGRA \u8fd8\u662f\u4e0d\u540c\u7684\uff0c\u5177\u4f53\u8868\u73b0\u4e3a\uff1a<\/p>\n

      1. RPP \u662f\u51c6\u9759\u6001\u53ef\u91cd\u6784\u9635\u5217\uff0c\u800c\u4f20\u7edf CGRA \u4e00\u822c\u7528\u4e8e\u52a8\u6001\u53ef\u91cd\u6784\u9635\u5217\u3002\u9759\u6001\u53ef\u91cd\u6784\u6574\u5217\u662f\u6307\u6bcf\u4e2a\u6307\u4ee4\u5728\u5904\u7406\u5355\u5143\uff08PE\uff09\u7684\u6267\u884c\u4e0d\u968f\u65f6\u95f4\u53d8\u5316\uff0c\u6570\u636e\u6d41\u4e5f\u662f\u4e0d\u53d8\u7684\u3002\u5bf9\u4e8e\u7f16\u8bd1\u5668\u6765\u8bb2\uff0c\u9759\u6001\u7684\u53ef\u91cd\u6784\u9635\u5217\u4e0d\u9700\u8981\u5bf9\u6307\u4ee4\u5728\u65f6\u95f4\u4e0a\u8fdb\u884c\u5b89\u6392\uff0c\u8fd9\u6837\u5c31\u53ef\u4ee5\u8ba9 RPP \u6784\u9020\u66f4\u52a0\u7b80\u5355\uff0c\u6307\u4ee4\u7684\u5206\u914d\u901f\u5ea6\u5f88\u4f4e\u3002\u56e0\u6b64\uff0cRPP \u5f88\u5bb9\u6613\u5b9e\u73b0\u4e00\u4e2a\u5927\u578b\u7684\u9635\u5217\uff0c\u8b6c\u5982 32×32 \u7684\u9635\u5217\u3002RPP \u6bd4\u4f20\u7edf CGRA \u66f4\u52a0\u9002\u7528\u4e8e\u5927\u89c4\u6a21\u5e76\u884c\u8ba1\u7b97\u3002<\/p>\n

      2. RPP \u4f7f\u7528\u7684\u662f\u591a\u7ebf\u7a0b SIMT \u7f16\u7a0b\u6a21\u578b\uff0c\u800c CGRA \u901a\u5e38\u4f7f\u7528\u7684\u662f\u5355\u7ebf\u7a0b\u8bed\u8a00\u7f16\u7a0b\u3002RPP \u53ef\u4ee5\u517c\u5bb9 CUDA \u8bed\u8a00\uff0c\u66f4\u52a0\u9002\u5408\u5e76\u884c\u8ba1\u7b97\u3002CUDA \u8bed\u8a00\u8981\u6c42\u7f16\u7a0b\u4eba\u5458\u4ece\u4e00\u5f00\u59cb\u5c31\u8003\u8651\u6570\u636e\u7684\u5e76\u884c\u5ea6\uff0c\u628a\u5e76\u884c\u7b97\u6cd5\u7528 CUDA \u8bed\u8a00\u8868\u73b0\u51fa\u6765\uff1b\u7f16\u8bd1\u5668\u5219\u4e0d\u9700\u8981\u5206\u6790\u5e76\u884c\u8ba1\u7b97\u5ea6\uff0c\u7f16\u8bd1\u5668\u5c31\u975e\u5e38\u7b80\u5355\uff1bCUDA \u8bed\u8a00\u662f SIMT \u7c7b\u578b\uff0c\u53ea\u7528\u4e8e\u6570\u636e\u5e76\u884c\u7684\u8ba1\u7b97\uff0c\u800c\u4e14\u5e76\u884c\u5ea6\u5728\u4e00\u4e2a\u7a0b\u5e8f\u91cc\u4fdd\u6301\u4e0d\u53d8\u3002CGRA \u5219\u901a\u5e38\u4f7f\u7528 C \u8bed\u8a00 + \u72ec\u7acb\u7684\u7f16\u8bd1\u5668\uff0c\u867d\u7136\u7406\u8bba\u4e0a\u53ef\u4ee5\u8986\u76d6\u4efb\u610f\u7684\u8ba1\u7b97\u7c7b\u578b\uff0c\u4f46\u662f\u7f16\u8bd1\u5668\u975e\u5e38\u590d\u6742\uff0c\u5f88\u96be\u8fbe\u5230\u8f83\u9ad8\u7684\u7f16\u8bd1\u6548\u7387\u3002<\/p>\n

      \u4e0b\u9762\u56fe\u8868\u5bf9 RPP \u53ca\u51e0\u4e2a\u4e3b\u6d41\u7684\u53ef\u91cd\u6784\u52a0\u901f\u67b6\u6784\u505a\u4e86\u5bf9\u6bd4\u3002<\/p>\n

      <\/a><\/p>\n

      RPP \u67b6\u6784\u7684\u4f18\u52bf\u53ef\u4ee5\u603b\u7ed3\u4e3a\u4ee5\u4e0b\u56db\u70b9\uff1a<\/p>\n

        \n
      1. \n

        \u5177\u6709\u57ab\u7247\u6682\u5b58\u5668\uff08gasket memory\uff09\u7684\u73af\u5f62\u53ef\u91cd\u6784\u5e76\u884c\u5904\u7406\u67b6\u6784\uff0c\u5141\u8bb8\u5728\u4e0d\u540c\u6570\u636e\u6d41\u4e4b\u95f4\u9ad8\u6548\u5730\u91cd\u7528\u6570\u636e\uff1b<\/p>\n<\/li>\n

      2. \n

        \u5206\u5c42\u5f0f\u5185\u5b58\u8bbe\u8ba1\u5177\u6709\u591a\u79cd\u6570\u636e\u8bbf\u95ee\u6a21\u5f0f\u3001\u5730\u5740\u6620\u5c04<\/mark>\u7b56\u7565\u548c\u5171\u4eab\u5185\u5b58\u6a21\u5f0f\uff0c\u53ef\u5b9e\u73b0\u9ad8\u6548\u7075\u6d3b\u7684\u5185\u5b58\u8bbf\u95ee\uff1b<\/p>\n<\/li>\n

      3. \n

        \u5404\u79cd\u786c\u4ef6\u4f18\u5316\u673a\u5236\uff0c\u5982\u5e76\u53d1\u5185\u6838\u6267\u884c\u3001\u5bc4\u5b58\u5668\u62c6\u5206\u548c\u91cd\u65b0\u586b\u5145\uff0c\u4ee5\u53ca\u5f02\u6784\u6807\u91cf\u548c\u5411\u91cf\u8ba1\u7b97\uff0c\u4ece\u800c\u63d0\u9ad8\u4e86\u6574\u4f53\u786c\u4ef6\u5229\u7528\u7387\u548c\u6027\u80fd\uff1b<\/p>\n<\/li>\n

      4. \n

        \u4e00\u4e2a\u517c\u5bb9 CUDA \u7684\u7aef\u5230\u7aef\u5b8c\u6574\u8f6f\u4ef6\u6808\uff0c\u5177\u6709\u7f16\u8bd1\u5668\u3001\u8fd0\u884c\u65f6\u73af\u5883\u3001\u9ad8\u5ea6\u4f18\u5316\u7684 RPP \u5e93\uff0c\u53ef\u5b9e\u73b0\u8fb9\u7f18 AI \u5e94\u7528\u7684\u5feb\u901f\u9ad8\u6548\u90e8\u7f72\u3002<\/p>\n<\/li>\n<\/ol>\n

        \u82af\u52a8\u529b\u57fa\u4e8e RPP \u67b6\u6784\u63d0\u51fa\u4e86 RPP \u786c\u4ef6\u8bbe\u8ba1\u6846\u56fe\uff0c\u5e76\u901a\u8fc7 R8 \u82af\u7247\u771f\u5b9e\u7684\u5c55\u73b0\u51fa\u8fd9\u79cd\u5e76\u884c\u8ba1\u7b97\u67b6\u6784\u7684\u4f18\u8d8a\u6027\u3002\u8fd9\u79cd\u786c\u4ef6\u8bbe\u8ba1\u5b9e\u73b0\u4e3b\u8981\u7531\u4e00\u4e2a\u73af\u5f62\u53ef\u91cd\u6784\u5904\u7406\u5668\uff08Circular Reconfigurable Processor\uff09\u3001\u4e00\u4e2a\u5185\u5b58\u5355\u5143\u548c\u4e00\u4e2a\u5e8f\u5217\u5668\u7ec4\u6210\uff0c\u89c1\u4e0b\u56fe\u3002<\/p>\n

          \n
        1. \n

          \u5faa\u73af\u53ef\u91cd\u6784\u5904\u7406\u5668\u662f\u5927\u89c4\u6a21\u5e76\u884c\u8ba1\u7b97\u7684\u6838\u5fc3\u8ba1\u7b97\u7ec4\u4ef6\u3002<\/p>\n<\/li>\n

        2. \n

          \u5185\u5b58\u5355\u5143\u88ab\u5206\u6210\u591a\u4e2a\u5185\u5b58\u7ec4\uff0c\u6bcf\u4e2a\u5185\u5b58\u7ec4\u90fd\u4e0e\u4e00\u4e2a\u7f13\u5b58\u914d\u5bf9\uff0c\u4ee5\u5229\u7528\u7a0b\u5e8f\u7684\u65f6\u95f4\u548c\u7a7a\u95f4\u5c40\u90e8\u6027\u5b9e\u73b0\u9ad8\u6548\u7684\u6570\u636e\u91cd\u7528\u3002\u53ea\u6709\u5f53\u73af\u5f62\u53ef\u91cd\u6784\u5904\u7406\u5668\u5185\u7684\u5bc4\u5b58\u5668\u548c\u7f13\u51b2\u533a\u5df2\u6ee1\u65f6\uff0c\u4e2d\u95f4\u6570\u636e\u624d\u4f1a\u88ab\u4f20\u8f93\u5e76\u5b58\u50a8\u5728\u5185\u5b58\u5355\u5143\u4e2d\u3002<\/p>\n<\/li>\n

        3. \n

          \u5e8f\u5217\u5668\u7528\u4e8e\u89e3\u7801\u548c\u5206\u53d1\u6307\u4ee4\u5230\u73af\u5f62\u53ef\u91cd\u6784\u5904\u7406\u5668\uff0c\u5e76\u4f7f\u7528\u7f13\u5b58\u6765\u5b58\u50a8\u4ece DDR \u6536\u5230\u7684\u6307\u4ee4\u3002<\/p>\n<\/li>\n<\/ol>\n

          <\/a><\/p>\n

          \u73af\u5f62\u53ef\u91cd\u6784\u5904\u7406\u5668\u5305\u62ec NPU \u5904\u7406\u5355\u5143 (PE) \u548c\u4e00\u4e2a\u57ab\u7247\u5185\u5b58\u3002\u6bcf\u4e2a PE \u90fd\u914d\u5907\u4e86\u4e00\u4e2a\u5185\u5b58\u7aef\u53e3\uff0c\u4ee5\u65b9\u4fbf\u5bf9\u5185\u5b58\u5355\u5143\u8fdb\u884c\u6570\u636e\u8bbf\u95ee\u3002\u5185\u5b58\u7aef\u53e3\u8bbe\u8ba1\u6709\u6a21\u5f0f\u63a7\u5236\u5668\u3001\u5730\u5740\u8ba1\u7b97\u5355\u5143\u548c\u591a\u4e2a\u591a\u8def\u590d\u7528\u5668\uff0c\u4ee5\u652f\u6301\u4e0d\u540c\u7684\u6570\u636e\u8bbf\u95ee\u6a21\u5f0f\u548c\u5171\u4eab\u5185\u5b58\u6a21\u5f0f\u3002\u4e3a\u4e86\u5b9e\u73b0\u7075\u6d3b\u7684\u5904\u7406\u5668\u5185\u901a\u4fe1\uff0c\u6bcf\u4e2a PE \u90fd\u96c6\u6210\u4e86\u4e00\u4e2a\u5f00\u5173\u76d2 (SB) \u548c\u4e00\u4e2a\u4e92\u8fde\u5f00\u5173\u76d2 (ICSB)\uff0c\u4ee5\u5b9e\u73b0\u9ad8\u6548\u7684\u6570\u636e\u8f6c\u53d1\u3002\u8fd9\u4e9b PE \u6309\u7ebf\u6027\u987a\u5e8f\u8fde\u63a5\uff0c\u57ab\u7247\u5185\u5b58\u5145\u5f53\u7b2c\u4e00\u4e2a\u548c\u6700\u540e\u4e00\u4e2a PU \u4e4b\u95f4\u7684\u6865\u6881\uff0c\u4ece\u800c\u5f62\u6210\u73af\u5f62\u62d3\u6251\u3002<\/p>\n

          \u73af\u5f62\u53ef\u91cd\u6784\u5904\u7406\u5668\u5185\u7684\u6570\u636e\u5904\u7406\u4ece\u7b2c\u4e00\u4e2a PE \u5f00\u59cb\uff0c\u5e76\u4ee5\u6d41\u6c34\u7ebf\u65b9\u5f0f\u904d\u5386 PE\uff0c\u4e2d\u95f4\u8ba1\u7b97\u7ed3\u679c\u6309\u987a\u5e8f\u8f93\u51fa\u5230\u540e\u7eed PE\u3002\u57ab\u7247\u5185\u5b58\u7f13\u5b58\u6700\u540e\u4e00\u4e2a PE \u7684\u8f93\u51fa\u5e76\u5c06\u5b83\u4eec\u91cd\u65b0\u5faa\u73af\u5230\u7b2c\u4e00\u4e2a PE\uff0c\u4ece\u800c\u6700\u5927\u9650\u5ea6\u5730\u63d0\u9ad8\u6570\u636e\u5c40\u90e8\u6027\u5e76\u6d88\u9664\u5185\u5b58\u5355\u5143\u7684\u5185\u5b58\u6d41\u91cf\u3002PE \u4e2d\u7684\u5173\u952e\u8ba1\u7b97\u7ec4\u4ef6\u662f\u5904\u7406\u5f15\u64ce\u3002\u5728\u6bcf\u4e2a PE \u4e2d\uff0c\u90fd\u6709\u591a\u4e2a\u7b97\u672f<\/mark>\u903b\u8f91<\/mark>\u5355\u5143 (ALU)\uff0c\u5176\u4e2d\u6bcf\u4e2a ALU \u90fd\u4e0e\u6570\u636e\u5bc4\u5b58\u5668\u548c\u5730\u5740\u5bc4\u5b58\u5668\u8026\u5408\u3002\u8fd9\u4e9b\u6570\u636e\u5bc4\u5b58\u5668\u805a\u5408\u5728\u4e00\u8d77\u5f62\u6210\u4e00\u4e2a\u6570\u636e\u7f13\u51b2\u533a\uff0c\u4fbf\u4e8e\u5728\u6bcf\u4e2a PE \u5185\u5feb\u901f\u8bbf\u95ee\u6570\u636e\u3002<\/p>\n

          \u6b64\u5916\uff0c\u7ebf\u6027\u4ea4\u6362\u7f51\u7edc\u548c\u57ab\u7247\u5b58\u50a8\u5668\u7684\u7ec4\u5408\u5b9e\u73b0\u4e86\u7075\u6d3b\u7684\u6570\u636e\u6d41\u63a7\u5236\u548c\u9ad8\u6548\u7684\u6570\u636e\u91cd\u7528\uff0c\u540c\u65f6\u6d88\u9664\u4e86\u4f20\u7edf\u57fa\u4e8e\u7f51\u683c\u7684 CGRA \u8bbe\u8ba1\u4e2d\u590d\u6742\u7684\u7f51\u7edc\u8def\u7531\u3002\u7ed3\u5408\u5bf9\u5185\u5b58\u5355\u5143\u7684\u7075\u6d3b\u9ad8\u6548\u6570\u636e\u8bbf\u95ee\uff0cRPP \u53ef\u4ee5\u4f18\u5316\u6570\u636e\u6d41\u5904\u7406\uff0c\u6700\u5c0f\u5316\u5185\u5b58\u6d41\u91cf\uff0c\u4ece\u800c\u6700\u5927\u9650\u5ea6\u5730\u63d0\u9ad8\u8d44\u6e90\u5229\u7528\u6548\u7387\u3002<\/p>\n

          RPP \u5904\u7406\u5668\u91c7\u7528 SIMT \u7f16\u7a0b\u6a21\u578b\u6765\u4e3a\u7075\u6d3b\u591a\u7ebf\u7a0b\u7ba1\u9053\u542f\u7528\u6d41\u5f0f\u6570\u636e\u6d41\u5904\u7406\u3002<\/p>\n

          <\/a><\/p>\n

          \u4e3a\u4e86\u786e\u4fdd\u4e0e\u73b0\u6709 GPGPU \u8f6f\u4ef6\u751f\u6001\u7cfb\u7edf\u7684\u517c\u5bb9\u6027\uff0c\u82af\u52a8\u529b\u7684 RPP \u5904\u7406\u5668\u91c7\u7528\u4e86\u62e5\u6709\u5e7f\u6cdb\u7528\u6237\u7fa4\u7684 CUDA\u3002CUDA \u4ee3\u7801\u7531\u57fa\u4e8e LLVM \u7684\u524d\u7aef\u89e3\u6790\uff0c\u4e3a RPP \u540e\u7aef\u751f\u6210 PTX \u4ee3\u7801\u3002RPP \u7f16\u8bd1\u5668\u5c06 CUDA \u5185\u6838\u89e3\u91ca\u4e3a\u6570\u636e\u6d41\u56fe\u5e76\u5c06\u5b83\u4eec\u6620\u5c04<\/mark>\u5230\u865a\u62df\u6570\u636e\u8def\u5f84\uff08VDP\uff09\u3002\u7136\u540e\u6839\u636e\u786c\u4ef6\u7ea6\u675f\u5c06 VDP \u5206\u89e3\u4e3a\u591a\u4e2a\u7269\u7406\u6570\u636e\u8def\u5f84\uff08PDP\uff09\uff0c\u6bcf\u4e2a PDP \u7684\u914d\u7f6e\u7531\u5e8f\u5217\u5668\u5728\u8fd0\u884c\u65f6\u751f\u6210\u3002<\/p>\n

          RPP \u7684\u8f6f\u4ef6\u5806\u6808\u53ef\u4ee5\u652f\u6301\u5e7f\u6cdb\u7684\u5927\u89c4\u6a21\u5e76\u884c\u5e94\u7528\uff0c\u5305\u62ec\u673a\u5668\u5b66\u4e60<\/mark>\u3001\u89c6\u9891 \/ \u56fe\u50cf\u5904\u7406<\/mark>\u548c\u4fe1\u53f7\u5904\u7406<\/mark>\u7b49\u3002\u5bf9\u4e8e\u673a\u5668\u5b66\u4e60<\/mark>\u5e94\u7528\uff0c\u8be5\u5806\u6808\u4e0e\u4e0d\u540c\u7684\u4e3b\u6d41\u6846\u67b6\u517c\u5bb9\uff0c\u4f8b\u5982 PyTorch\u3001ONNX\u3001Caffe \u548c TensorFlow<\/mark>\u3002\u6b64\u5916\uff0c\u7528\u6237\u53ef\u4ee5\u7075\u6d3b\u5730\u4f7f\u7528 CUDA \u5b9a\u4e49\u4ed6\u4eec\u7684\u81ea\u5b9a\u4e49\u7a0b\u5e8f\u3002\u8fd9\u4e9b\u9ad8\u7ea7\u5e94\u7528\u7a0b\u5e8f\u7531 RPP \u6846\u67b6\u5904\u7406\uff0c\u8be5\u6846\u67b6\u5305\u542b\u4e00\u4e2a\u7f16\u8bd1\u5668\u548c\u4e0d\u540c\u9886\u57df\u7279\u5b9a\u7684\u5e93\u3002\u5728\u8f6f\u4ef6\u5806\u6808\u7684\u5e95\u90e8\uff0c\u91c7\u7528 RPP \u8fd0\u884c\u65f6\u73af\u5883\u548c RPP \u9a71\u52a8\u7a0b\u5e8f\u6765\u786e\u4fdd\u4f7f\u7528\u5de5\u5177\u94fe\u7f16\u8bd1\u7684\u7a0b\u5e8f\u53ef\u4ee5\u5728\u5e95\u5c42\u786c\u4ef6\u4e0a\u65e0\u7f1d\u6267\u884c\u3002<\/p>\n

          \u4e94\u3001RPP \u5904\u7406\u5668 R8 \u80fd\u6548\u5bf9\u6bd4<\/strong><\/p>\n

          \u57fa\u4e8e\u4ee5\u4e0a RPP \u5904\u7406\u5668\u786c\u4ef6\u8bbe\u8ba1\u548c\u5b8c\u6574\u8f6f\u4ef6\u5806\u6808\u5b9e\u73b0\u7684 RPP-R8 \u82af\u7247\u5728\u8ba1\u7b97\u6027\u80fd\u548c\u80fd\u6548\u4e0a\u8868\u73b0\u5982\u4f55\u5462\uff1f<\/p>\n

          R8 \u82af\u7247\u7684\u6027\u80fd\u53c2\u6570<\/mark>\u5982\u4e0b\u8868\u6240\u793a\uff1a<\/p>\n

          <\/a><\/p>\n

          \u9488\u5bf9\u8fb9\u7f18\u8ba1\u7b97<\/mark>\u573a\u666f\uff0c\u82af\u52a8\u529b\u5c06 RPP-R8 \u82af\u7247\u4e0e\u4e24\u6b3e\u82f1\u4f1f\u8fbe\u8fb9\u7f18 GPU \u8fdb\u884c\u4e86\u6bd4\u8f83\uff1aJetson Nano \u548c Jetson Xavier AGX\u3002Jetson Nano \u7684\u82af\u7247\u5c3a\u5bf8\u4e0e RPP \u76f8\u4f3c\uff0c\u53ef\u5728\u7269\u7406\u9762\u79ef\u9650\u5236\u5185\u63d0\u4f9b\u76f8\u5173\u6bd4\u8f83\uff1b\u9009\u62e9 Jetson Xavier AGX \u662f\u57fa\u4e8e\u5176\u4e0e RPP-R8 \u76f8\u5f53\u7684\u7406\u8bba\u541e\u5410\u91cf\u3002\u82af\u52a8\u529b\u5728 ResNet-50 \u63a8\u7406\u4e0a\u8bc4\u4f30\u4e86\u8fd9\u4e09\u4e2a AI \u52a0\u901f\u5e73\u53f0\uff0c\u5176\u4e2d Jetson Nano \u7684\u541e\u5410\u91cf\u6765\u81ea\u57fa\u51c6<\/mark>\u6d4b\u8bd5\u8bba\u6587\uff0c\u800c Xavier AGX \u7684\u6027\u80fd\u6570\u636e\u6765\u81ea\u82f1\u4f1f\u8fbe\u5b98\u65b9\u7f51\u7ad9\u3002<\/p>\n

          <\/a><\/p>\n

          \u5982\u4e0a\u8868\u6240\u793a\uff0cRPP-R8 \u7684\u5b9e\u6d4b\u8fd0\u884c\u541e\u5410\u91cf\u5206\u522b\u662f Jetson Nano \u548c Jetson Xavier AGX \u7684 41.3 \u500d\u548c 2.3 \u500d\u3002\u8981\u77e5\u9053\uff0cJetson Xavier AGX \u7684\u82af\u7247\u5c3a\u5bf8\u51e0\u4e4e\u662f R8 \u7684\u4e09\u500d\uff0c\u5de5\u827a\u4e5f\u66f4\u5148\u8fdb\uff0812 nm vs. 14 nm\uff09\uff0c\u4f46\u5176\u6027\u80fd\u4f4e\u4e8e R8\u3002\u5728\u80fd\u6548\u65b9\u9762\uff0cR8 \u7684\u80fd\u6548\u5206\u522b\u662f Jetson Nano \u548c Jetson Xavier AGX \u7684 27.5 \u500d\u548c 4.6 \u500d\u3002\u8fd9\u4e9b\u7ed3\u679c\u8868\u660e\uff0c\u5728\u9762\u79ef\u548c\u529f\u7387\u9884\u7b97\u6709\u9650\u7684\u8fb9\u7f18 AI \u573a\u666f\u4e2d\uff0cRPP-R8 \u7684\u8868\u73b0\u660e\u663e\u4f18\u4e8e Jetson Nano \u548c Jetson Xavier AGX\u3002<\/p>\n

          <\/a><\/p>\n

          \u6df1\u5ea6\u5b66\u4e60<\/mark>\u63a8\u7406\u662f\u4e00\u79cd\u5e7f\u53d7\u8ba4\u53ef\u7684\u5927\u89c4\u6a21\u5e76\u884c\u5de5\u4f5c\u8d1f\u8f7d\uff0c\u4e5f\u662f RPP-R8 \u786c\u4ef6\u7684\u5173\u952e\u5e94\u7528\u3002\u9274\u4e8e Yolo \u7cfb\u5217\u6a21\u578b\u4e0e ResNet-50 \u7b49\u5206\u7c7b\u6a21\u578b\u76f8\u6bd4\u8868\u73b0\u51fa\u66f4\u9ad8\u7684\u8ba1\u7b97\u590d\u6742\u5ea6\uff0c\u82af\u52a8\u529b\u9009\u62e9\u82f1\u4f1f\u8fbe Jeston Nano Orin \u4f5c\u4e3a GPU \u5e73\u53f0\uff0c\u5176\u5cf0\u503c\u541e\u5410\u91cf\u6bd4 Jetson AGX Xavier \u66f4\u9ad8\uff0c\u4e3a 40 TOPS\u3002\u7531\u4e8e CPU \u901a\u5e38\u4e0d\u662f\u4e3a\u9ad8\u6027\u80fd\u6df1\u5ea6\u5b66\u4e60<\/mark>\u63a8\u7406\u800c\u6784\u5efa\u7684\uff0c\u56e0\u6b64\u9009\u62e9 Jetson Xavier Nx \u4f5c\u4e3a\u6bd4\u8f83\u4f4e\u7aef\u7684 GPU \u5e73\u53f0\uff0c\u5177\u6709 21 TOPS \u7684\u5cf0\u503c\u541e\u5410\u91cf\u3002\u8bc4\u4f30\u6279\u5904\u7406\u5927\u5c0f\u4e3a 1\u30012 \u548c 4 \u7684\u5de5\u4f5c\u8d1f\u8f7d\uff0c\u53cd\u6620\u4e86\u771f\u5b9e\u7684\u8fb9\u7f18\u573a\u666f\u3002\u4e0a\u56fe\u663e\u793a\u4e86\u4e09\u4e2a\u5e73\u53f0\u7684\u541e\u5410\u91cf\u6027\u80fd\u6bd4\u8f83\uff0cRPP-R8 \u5728 Yolo-v5m \u548c Yolo-v7 tiny \u4e0a\u5c55\u793a\u4e86\u66f4\u9ad8\u7684\u541e\u5410\u91cf\u3002\u5728\u6279\u91cf\u5927\u5c0f\u4e3a 1 \u7684\u60c5\u51b5\u4e0b\uff0cRPP-R8 \u7684\u541e\u5410\u91cf\u5927\u7ea6\u6bd4 Jeston Nano Orin \u9ad8 1.5\u00d7 \u223c2.5 \u500d\uff0c\u6bd4 Jeston Xavier Nx \u9ad8 2.6\u00d7 \u223c4.3 \u500d\u3002<\/p>\n

          \u8bc4\u4f30\u4e0e\u6d4b\u8bd5\u7ed3\u679c\u8868\u660e\uff0cRPP \u5728\u5ef6\u8fdf\u3001\u541e\u5410\u91cf\u548c\u80fd\u6548\u65b9\u9762\u4f18\u4e8e\u4f20\u7edf\u7684 GPU\u3001CPU \u548c DSP \u7b49\u67b6\u6784\u3002RPP \u5904\u7406\u5668\u7684\u6027\u80fd\u63d0\u5347\u5f52\u529f\u4e8e\u5176\u72ec\u7279\u7684\u786c\u4ef6\u7279\u6027\uff0c\u4e3b\u8981\u5305\u62ec\uff1a1) \u5faa\u73af\u6570\u636e\u6d41\u5904\u7406\uff1a\u4e2d\u95f4\u7ed3\u679c\u6d41\u7ecf PE \u4e4b\u95f4\u7684\u6d41\u6c34\u7ebf\u5bc4\u5b58\u5668\u548c FIFO\uff0c\u663e\u8457\u51cf\u5c11\u4e86\u6570\u636e\u79fb\u52a8\u548c\u5230\u8fdc\u7a0b\u5185\u5b58\u5b58\u50a8\u7684\u5185\u5b58\u6d41\u91cf\uff1b\u4e0e GPU \u548c CPU \u4e2d\u7684\u6570\u636e\u5904\u7406\u76f8\u6bd4\uff0c\u8fd9\u79cd\u6a21\u5f0f\u6548\u7387\u66f4\u9ad8\u30022) \u5206\u5c42\u5185\u5b58\u7cfb\u7edf\uff1aRPP \u901a\u8fc7\u5176\u5206\u5c42\u5185\u5b58\u7cfb\u7edf\u6700\u5927\u5316\u6570\u636e\u5c40\u90e8\u6027\u3002RPP-R8 \u82af\u7247\u9762\u79ef\u7684\u5f88\u5927\u4e00\u90e8\u5206\uff08\u7ea6 39.9%\uff09\u4e13\u7528\u4e8e\u7247\u4e0a\u5b58\u50a8\u5668\u3002\u8fd9\u79cd\u8bbe\u8ba1\u9009\u62e9\u63d0\u4f9b\u4e86\u5e7f\u6cdb\u7684\u5185\u5b58\u5bb9\u91cf\uff0c\u589e\u5f3a\u4e86\u6570\u636e\u91cd\u7528\u5e76\u51cf\u5c11\u4e86\u9891\u7e41\u8bbf\u95ee\u5916\u90e8\u5b58\u50a8\u5668\u7684\u9700\u6c42\u30023) \u77e2\u91cf\u5316<\/mark>\u548c\u591a\u7ebf\u7a0b\u7ba1\u9053\uff1aRPP \u7684\u786c\u4ef6\u67b6\u6784\u548c\u7f16\u7a0b\u6a21\u578b\u53ef\u5b9e\u73b0\u6709\u6548\u7684\u77e2\u91cf\u5316<\/mark>\u548c\u591a\u7ebf\u7a0b\u7ba1\u9053\u3002\u8fd9\u79cd\u8bbe\u8ba1\u5145\u5206\u5229\u7528\u4e86 RPP \u8fdb\u884c\u5e76\u884c\u5904\u7406\u7684\u5168\u90e8\u8ba1\u7b97\u6f5c\u529b\uff0c\u786e\u4fdd\u5176\u8d44\u6e90\u5f97\u5230\u6700\u5927\u7a0b\u5ea6\u7684\u5229\u7528\uff0c\u4ece\u800c\u63d0\u9ad8\u6027\u80fd\u3002<\/p>\n

          \u9664\u4e86\u5728\u80fd\u8017\u3001\u5ef6\u8fdf\u548c\u541e\u5410\u91cf\u65b9\u9762\u7684\u4f18\u52bf\u5916\uff0cRPP \u8fd8\u56e0\u5176\u5c0f\u9762\u79ef\u800c\u8131\u9896\u800c\u51fa\u3002\u53ea\u6709 119 \u5e73\u65b9\u6beb\u7c73\u7684\u82af\u7247\u9762\u79ef\u6d88\u8017\u4f7f\u5f97 RPP-R8 \u6210\u4e3a\u9762\u79ef\u53d7\u9650\u7684\u8fb9\u7f18\u8ba1\u7b97<\/mark>\u7684\u7406\u60f3\u5e73\u53f0\u3002RPP \u7684\u53e6\u4e00\u4e2a\u7279\u70b9\u662f\u5176\u9ad8\u53ef\u7f16\u7a0b\u6027\uff0c\u7531\u5168\u9762\u7684\u7aef\u5230\u7aef\u8f6f\u4ef6\u5806\u6808\u652f\u6301\uff0c\u53ef\u663e\u8457\u63d0\u9ad8\u90e8\u7f72\u6548\u7387\u3002\u4e0e CUDA \u7684\u517c\u5bb9\u6027\u4f7f\u7528\u6237\u80fd\u591f\u5229\u7528\u719f\u6089\u7684 CUDA \u751f\u6001\u7cfb\u7edf\uff0c\u4ece\u800c\u7f29\u77ed\u5b66\u4e60\u66f2\u7ebf<\/mark>\u5e76\u4fc3\u8fdb\u66f4\u5bb9\u6613\u7684\u91c7\u7528\u3002\u652f\u6301\u5373\u65f6\u7f16\u7a0b\u548c\u56fe\u5f62\u7f16\u7a0b\u6a21\u5f0f\uff0c\u4e3a\u7528\u6237\u63d0\u4f9b\u4e86\u9ad8\u5ea6\u7684\u7075\u6d3b\u6027\uff0c\u6ee1\u8db3\u5404\u79cd\u8ba1\u7b97\u9700\u6c42\u3002\u5305\u62ec OpenRT \u548c RPP-BLAS \u5728\u5185\u7684\u4e0d\u540c\u5e93\u652f\u6301\u4e5f\u4fc3\u8fdb\u4e86\u5404\u79cd\u573a\u666f\u4e2d\u7684\u9ad8\u6027\u80fd\u548c\u9ad8\u6548\u90e8\u7f72\u3002\u5168\u6808\u89e3\u51b3\u65b9\u6848\uff0c\u5305\u62ec\u786c\u4ef6\u67b6\u6784\u548c\u8f6f\u4ef6\u652f\u6301\uff0c\u4f7f RPP \u5728\u5404\u79cd\u8fb9\u7f18\u8ba1\u7b97<\/mark>\u786c\u4ef6\u4e2d\u8131\u9896\u800c\u51fa\u3002<\/p>\n

          \u516d\u3001RPP \u67b6\u6784\u5f97\u5230\u56fd\u9645\u5b66\u672f\u6743\u5a01\u8ba4\u53ef<\/strong><\/p>\n

          \u7531\u82af\u52a8\u529b\u643a\u624b\u82f1\u56fd\u5e1d\u56fd\u7406\u5de5\u3001\u5251\u6865\u5927\u5b66\u3001\u6e05\u534e\u5927\u5b66<\/mark>\u548c\u4e2d\u5c71\u5927\u5b66\u7b49\u9876\u5c16\u5b66\u5e9c\u7684\u8ba1\u7b97\u673a\u67b6\u6784\u56e2\u961f\u5171\u540c\u64b0\u5199\u7684\u8bba\u6587\u300aCircular Reconfigurable Parallel Processor for Edge Computing\u300b\uff08RPP \u82af\u7247\u67b6\u6784\uff09\u5df2\u6210\u529f\u88ab\u7b2c 51 \u5c4a\u8ba1\u7b97\u673a\u4f53\u7cfb\u7ed3\u6784\u56fd\u9645\u7814\u8ba8\u4f1a\uff08ISCA 2024\uff09\u7684 Industry Track \u6536\u5f55\u3002\u82af\u52a8\u529b\u521b\u59cb\u4eba\u517c CEO \u674e\u539f\u535a\u58eb\u4e0e\u5e1d\u56fd\u7406\u5de5\u535a\u58eb\u6bd5\u4e1a\u751f Hongxiang Fan\uff08\u73b0\u5728\u82f1\u56fd\u5251\u6865\u7684\u4e09\u661f AI \u4e2d\u5fc3\u505a\u7814\u7a76\u79d1\u5b66\u5bb6\uff09\u53d7\u9080\u5728\u963f\u6839\u5ef7\u5e03\u5b9c\u8bfa\u65af\u827e\u5229\u65af\u4e3e\u884c\u7684 ISCA 2024 \u4f1a\u8bae\u4e0a\u53d1\u8868\u6f14\u8bb2\uff0c\u4e0e Intel \u548c AMD<\/mark> \u7b49\u56fd\u9645\u77e5\u540d\u4f01\u4e1a\u7684\u4e13\u5bb6\u540c\u53f0\u4ea4\u6d41\u3002<\/p>\n

          <\/a><\/p>\n

          \u672c\u5c4a ISCA \u5171\u6536\u5230\u6765\u81ea\u5168\u7403 423 \u7bc7\u9ad8\u8d28\u91cf\u8bba\u6587\u6295\u7a3f\uff0c\u7ecf\u8fc7\u4e25\u8c28\u7684\u8bc4\u5ba1\u6d41\u7a0b\uff0c\u4ec5\u6709 83 \u7bc7\u8bba\u6587\u8131\u9896\u800c\u51fa\uff0c\u603b\u4f53\u63a5\u6536\u7387\u4f4e\u81f3 19.6%\u3002\u5176\u4e2d\uff0cIndustry Track \u7684\u5f55\u53d6\u96be\u5ea6\u5c24\u4e3a\u7a81\u51fa\uff0c\u63a5\u6536\u7387\u4ec5\u4e3a 15.3%\u3002<\/p>\n

          \u4f5c\u4e3a\u8ba1\u7b97\u673a\u4f53\u7cfb\u7ed3\u6784\u9886\u57df\u7684\u9876\u7ea7\u5b66\u672f\u76db\u4f1a\uff0cISCA \u7531 ACM SIGARCH \u4e0e IEEE TCCA \u8054\u5408\u4e3e\u529e\u3002\u81ea 1973 \u5e74\u521b\u529e\u4ee5\u6765\uff0c\u4e00\u76f4\u662f\u63a8\u52a8\u8ba1\u7b97\u673a\u7cfb\u7edf\u7ed3\u6784\u9886\u57df\u8fdb\u6b65\u7684\u5148\u950b\u529b\u91cf\uff0c\u5176\u5e7f\u6cdb\u7684\u5f71\u54cd\u529b\u548c\u5353\u8d8a\u7684\u8d21\u732e\u4f7f\u5176\u6210\u4e3a\u8c37\u6b4c\u3001\u82f1\u7279\u5c14<\/mark>\u3001\u82f1\u4f1f\u8fbe\u7b49\u884c\u4e1a\u5de8\u5934\u7ade\u76f8\u5c55\u793a\u524d\u6cbf\u7814\u7a76\u6210\u679c\u7684\u9ad8\u7aef\u5e73\u53f0\u3002ISCA \u4e0e MICRO\u3001HPCA\u3001ASPLOS \u5e76\u79f0\u4e3a\u56db\u5927\u9876\u7ea7\u4f1a\u8bae\uff0c\u800c ISCA \u66f4\u662f\u5176\u4e2d\u7684\u4f7c\u4f7c\u8005\uff0c\u8bba\u6587\u5f55\u53d6\u7387\u5e38\u5e74\u4fdd\u6301\u5728 18% \u5de6\u53f3\u3002\u591a\u5e74\u6765\uff0c\u4f17\u591a\u5728 ISCA \u4e0a\u53d1\u8868\u7684\u7814\u7a76\u6210\u679c\u5df2\u6210\u4e3a\u63a8\u52a8\u534a\u5bfc\u4f53\u548c\u8ba1\u7b97\u673a\u884c\u4e1a\u53d1\u5c55\u7684\u5173\u952e\u52a8\u529b\u3002<\/p>\n

          \u672c\u6b21\u5165\u9009\u7684\u53ef\u91cd\u6784\u5e76\u884c\u5904\u7406\u5668\uff08RPP\uff09\u8bba\u6587\u4e3a\u8fb9\u7f18\u8ba1\u7b97<\/mark>\u9886\u57df\u6ce8\u5165\u4e86\u5f3a\u52b2\u52a8\u529b\u3002\u5b9e\u9a8c\u7ed3\u679c\u5145\u5206\u8bc1\u5b9e\uff0c\u4f5c\u4e3a\u4e00\u6b3e\u5e76\u884c\u8ba1\u7b97\u7684\u786c\u4ef6\u5e73\u53f0\uff0cRPP \u7684\u6027\u80fd\u5168\u9762\u8d85\u8d8a\u5f53\u524d\u5e02\u573a\u4e0a\u7684 GPU\uff0c\u7279\u522b\u662f\u5728\u5bf9\u5ef6\u8fdf\u3001\u529f\u8017\u548c\u4f53\u79ef\u6709\u7740\u6781\u9ad8\u8981\u6c42\u7684\u5e94\u7528\u573a\u666f\u4e2d\u8868\u73b0\u5c24\u4e3a\u51fa\u8272\u3002<\/p>\n

          \u516d\u3001\u7ed3\u8bed<\/strong><\/p>\n

          ChatGPT \u5f15\u7206\u4e86 AI \u5927\u6a21\u578b\uff0c\u4ece\u800c\u5e26\u52a8\u4e86 GPU \u548c AI \u52a0\u901f\u5668\u7684\u5de8\u5927\u9700\u6c42\u3002AI \u5e94\u7528\u7684\u53d1\u5c55\u8d8b\u52bf\u5c06\u4ece\u4e91\u7aef AI \u8bad\u7ec3\u548c\u63a8\u7406\u9010\u6e10\u5f80\u8fb9\u7f18\u548c\u7aef\u4fa7 AI \u6e17\u900f\uff0c\u4e3a\u5404\u79cd AI \u5e94\u7528\u63d0\u4f9b\u8f6f\u786c\u4ef6\u652f\u6301\u7684 AI \u670d\u52a1\u5668\u4e5f\u540c\u6837\u9075\u5faa\u4ece\u6570\u636e\u4e2d\u5fc3\u5230\u8fb9\u7f18\u8ba1\u7b97<\/mark>\u7684\u5206\u5e03\u5f0f\u6269\u5c55\u8d8b\u52bf\u3002\u4f20\u7edf GPGPU \u5728\u8fb9\u7f18 AI \u5e94\u7528\u573a\u666f\u4e2d\u5f00\u59cb\u66b4\u9732\u51fa\u660e\u663e\u7684\u67b6\u6784\u7f3a\u9677\uff0c\u5176\u9ad8\u6210\u672c\u3001\u9ad8\u529f\u8017\u548c\u9ad8\u5ef6\u8fdf\u95ee\u9898\u8feb\u4f7f\u4e1a\u754c\u4e13\u5bb6\u5bfb\u6c42\u66f4\u4e3a\u9ad8\u80fd\u6548\u7684\u5e76\u884c\u8ba1\u7b97\u67b6\u6784\u3002<\/p>\n

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