{"id":1614,"date":"2023-08-17T01:54:38","date_gmt":"2023-08-17T01:54:38","guid":{"rendered":"https:\/\/www.gptmain.news\/?p=1614"},"modified":"2023-08-17T01:54:38","modified_gmt":"2023-08-17T01:54:38","slug":"%d0%bd%d0%b5%d0%b9%d1%80%d0%be%d0%bd%d0%bd%d0%b0%d1%8f-%d1%81%d0%b5%d1%82%d1%8c-%d1%81-%d0%bd%d1%83%d0%bb%d1%8f-%d1%87%d0%b0%d1%81%d1%82%d1%8c-1-gptmain-news","status":"publish","type":"post","link":"https:\/\/gptmain.news\/?p=1614","title":{"rendered":"\u041d\u0435\u0439\u0440\u043e\u043d\u043d\u0430\u044f \u0441\u0435\u0442\u044c \u0441 \u043d\u0443\u043b\u044f \u2014 \u0447\u0430\u0441\u0442\u044c 1\n | GPTMain News"},"content":{"rendered":"
\n

\u041f\u043e\u043b\u043d\u043e\u0441\u0442\u044c\u044e \u043f\u043e\u0434\u043a\u043b\u044e\u0447\u0435\u043d\u043d\u0430\u044f \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u0430\u044f \u0441\u0435\u0442\u044c<\/h2>\n

\u0414\u0430\u0432\u0430\u0439\u0442\u0435 \u0441\u043e\u0437\u0434\u0430\u0434\u0438\u043c \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0443 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u043e\u0439 \u0441\u0435\u0442\u0438 \u0441 \u043d\u0443\u043b\u044f. \u042f \u0438\u043c\u0435\u044e \u0432 \u0432\u0438\u0434\u0443, \u043f\u043e\u0447\u0435\u043c\u0443 \u0431\u044b \u0438 \u043d\u0435\u0442? \u0412\u044b \u043c\u043e\u0436\u0435\u0442\u0435 \u0441\u043a\u0430\u0437\u0430\u0442\u044c: \u041f\u0444\u0444… \u0411\u043e\u043b\u044c\u0448\u043e\u0435 \u0434\u0435\u043b\u043e.. \u0421 Python \u0438 Numpy \u044d\u0442\u043e \u0432\u0441\u0435\u0433\u043e \u043b\u0438\u0448\u044c \u0432\u043e\u043f\u0440\u043e\u0441 \u0447\u0430\u0441\u043e\u0432. \u0427\u0442\u043e, \u0435\u0441\u043b\u0438 \u044f \u0441\u043a\u0430\u0436\u0443 \u0432\u0430\u043c, \u0447\u0442\u043e \u0431\u0443\u0434\u0443 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c C++. \u041d\u0435\u0442, \u044f \u0448\u0443\u0447\u0443. \u042f \u0441\u043e\u0431\u0438\u0440\u0430\u044e\u0441\u044c \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0421.<\/p>\n

\u041f\u0440\u0438\u0447\u0438\u043d\u0430 \u044d\u0442\u043e\u0433\u043e \u0432 \u0442\u043e\u043c, \u0447\u0442\u043e \u044f \u0445\u043e\u0447\u0443 \u043e\u0431\u0443\u0447\u0438\u0442\u044c \u0441\u0432\u043e\u044e \u0441\u0435\u0442\u044c \u043d\u0430 GPU, \u0430 GPU \u043d\u0435 \u043f\u043e\u043d\u0438\u043c\u0430\u044e\u0442 \u043d\u0438 Python, \u043d\u0438 \u0434\u0430\u0436\u0435 C++. \u042f \u043f\u043b\u0430\u043d\u0438\u0440\u0443\u044e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c OpenCL \u0432\u043c\u0435\u0441\u0442\u0435 \u0441 C++ \u0434\u043b\u044f \u0441\u043e\u0437\u0434\u0430\u043d\u0438\u044f \u043f\u043e\u043b\u043d\u043e\u0444\u0443\u043d\u043a\u0446\u0438\u043e\u043d\u0430\u043b\u044c\u043d\u043e\u0439 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 \u0434\u043b\u044f \u0441\u043e\u0437\u0434\u0430\u043d\u0438\u044f \u0441\u043e\u0431\u0441\u0442\u0432\u0435\u043d\u043d\u043e\u0439 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u043e\u0439 \u0441\u0435\u0442\u0438 \u0438 \u0435\u0435 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f. \u0418 \u0447\u0442\u043e\u0431\u044b \u043d\u0435\u043c\u043d\u043e\u0433\u043e \u043e\u0436\u0438\u0432\u0438\u0442\u044c \u0435\u0433\u043e, \u043f\u043e\u0447\u0435\u043c\u0443 \u0431\u044b \u043d\u0435 \u0440\u0435\u0430\u043b\u0438\u0437\u043e\u0432\u0430\u0442\u044c \u0441\u0432\u0451\u0440\u0442\u043e\u0447\u043d\u0443\u044e \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u0443\u044e \u0441\u0435\u0442\u044c \u0432\u043c\u0435\u0441\u0442\u043e \u043f\u0440\u043e\u0441\u0442\u043e\u0439, \u0441\u043a\u0443\u0447\u043d\u043e\u0439 \u043f\u043e\u043b\u043d\u043e\u0441\u0432\u044f\u0437\u043d\u043e\u0439 \u041d\u0421. \u041d\u043e \u043e\u0431\u043e \u0432\u0441\u0435\u043c \u043f\u043e \u043f\u043e\u0440\u044f\u0434\u043a\u0443.<\/p>\n

\u0414\u0430\u0432\u0430\u0439\u0442\u0435 \u043d\u0435 \u0431\u0443\u0434\u0435\u043c \u0441\u0440\u0430\u0437\u0443 \u0443\u0433\u043b\u0443\u0431\u043b\u044f\u0442\u044c\u0441\u044f \u0432 \u043a\u043e\u0434 \u044f\u0434\u0440\u0430 \u0433\u0440\u0430\u0444\u0438\u0447\u0435\u0441\u043a\u043e\u0433\u043e \u043f\u0440\u043e\u0446\u0435\u0441\u0441\u043e\u0440\u0430. \u0421\u043d\u0430\u0447\u0430\u043b\u0430 \u043c\u044b \u0434\u043e\u043b\u0436\u043d\u044b \u043f\u043e\u0441\u0442\u0440\u043e\u0438\u0442\u044c \u0441\u043a\u0435\u043b\u0435\u0442 \u043d\u0430\u0448\u0435\u0439 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438.<\/p>\n

OpenCL<\/span>::<\/span>initialize_OpenCL<\/span>(<\/span>)<\/span>;<\/span><\/p>
std<\/span>::<\/span>vector<\/span><<\/span>std<\/span>::<\/span>vector<\/span><<\/span>float<\/span>><\/span> <\/span>><\/span> inputs<\/span>,<\/span> targets<\/span>;<\/span><\/p>
std<\/span>::<\/span>vector<\/span><<\/span>std<\/span>::<\/span>vector<\/span><<\/span>float<\/span>><\/span> <\/span>><\/span> testinputs<\/span>;<\/span><\/p>
std<\/span>::<\/span>vector<\/span><<\/span>float<\/span>><\/span> testtargets<\/span>;<\/span><\/p>
ConvNN m_nn<\/span>;<\/span><\/p>
std<\/span>::<\/span>vector<\/span><<\/span>int<\/span>><\/span> netVec<\/span>;<\/span><\/p>
netVec <\/span>=<\/span> <\/span>{<\/span> <\/span>1024<\/span>,<\/span>10<\/span> <\/span>}<\/span>;<\/span><\/p>
m_nn<\/span>.<\/span>createFullyConnectedNN<\/span>(<\/span>netVec<\/span>,<\/span> <\/span>1<\/span>,<\/span> <\/span>32<\/span>)<\/span>;<\/span><\/p>
 m_nn<\/span>.<\/span>trainFCNN<\/span>(<\/span>inputs<\/span>,<\/span> targets<\/span>,<\/span> testinputs<\/span>,<\/span> testtargets<\/span>,<\/span> <\/span>50000<\/span>)<\/span>;<\/span><\/p>
m_nn<\/span>.<\/span>trainingAccuracy<\/span>(<\/span>testinputs<\/span>,<\/span> testtargets<\/span>,<\/span> <\/span>2000<\/span>,<\/span> <\/span>1<\/span>)<\/span>;<\/span><\/p><\/pre>\n
\u0425\u043e\u0440\u043e\u0448\u043e, \u044d\u0442\u043e \u043e\u0431\u044b\u0447\u043d\u044b\u0439 \u043f\u0440\u043e\u0446\u0435\u0441\u0441 \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u043a\u043e\u043d\u0432\u0435\u0439\u0435\u0440\u0430 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u0441 \u0442\u043e\u0439 \u0440\u0430\u0437\u043d\u0438\u0446\u0435\u0439, \u0447\u0442\u043e \u0432\u043c\u0435\u0441\u0442\u043e \u0444\u0443\u043d\u043a\u0446\u0438\u0439 Sklearn \u0438\u043b\u0438 Tensorflow \u0437\u0434\u0435\u0441\u044c \u0443 \u043d\u0430\u0441 \u0435\u0441\u0442\u044c C++.  \u0412\u043f\u043e\u043b\u043d\u0435 \u0434\u043e\u0441\u0442\u0438\u0436\u0435\u043d\u0438\u0435!  \u0412\u0435\u0440\u043d\u043e?<\/p>\n
\u0412\u0441\u0435 \u0438\u0434\u0435\u0442 \u043d\u043e\u0440\u043c\u0430\u043b\u044c\u043d\u043e.  \u0423 \u043d\u0430\u0441 \u0435\u0441\u0442\u044c \u0431\u0430\u0437\u043e\u0432\u0430\u044f \u0432\u0435\u0440\u0441\u0438\u044f \u043d\u0430\u0448\u0435\u0433\u043e \u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043c\u043d\u043e\u0433\u043e \u043e\u0431\u0435\u0441\u043f\u0435\u0447\u0435\u043d\u0438\u044f.  \u0422\u0435\u043f\u0435\u0440\u044c \u043f\u0440\u0438\u0448\u043b\u043e \u0432\u0440\u0435\u043c\u044f \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u0430\u0442\u044c \u0444\u0430\u043a\u0442\u0438\u0447\u0435\u0441\u043a\u0443\u044e \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u0443 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u043e\u0439 \u0441\u0435\u0442\u0438.  \u0411\u0430\u0437\u043e\u0432\u044b\u043c \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u043c \u043b\u044e\u0431\u043e\u0439 NN \u044f\u0432\u043b\u044f\u0435\u0442\u0441\u044f \u0443\u0437\u0435\u043b, \u0438 \u043c\u043d\u043e\u0436\u0435\u0441\u0442\u0432\u043e \u0443\u0437\u043b\u043e\u0432, \u0441\u043b\u043e\u0436\u0435\u043d\u043d\u044b\u0445 \u0432\u043c\u0435\u0441\u0442\u0435, \u043e\u0431\u0440\u0430\u0437\u0443\u044e\u0442 \u0441\u043b\u043e\u0439.  \u0412\u043e\u0442 \u043e\u043d\u043e:<\/p>\n
\u0423\u0437\u0435\u043b \u0438 \u0441\u043b\u043e\u0439<\/h2>\n
typedef<\/span> <\/span>struct<\/span> <\/span>Node<\/span> <\/span>{<\/span><\/p>
    <\/span>int<\/span> numberOfWeights<\/span>;<\/span><\/p>
    <\/span>float<\/span> weights<\/span>[<\/span>1200<\/span>]<\/span>;<\/span><\/p>
    <\/span>float<\/span> output<\/span>;<\/span><\/p>
    <\/span>float<\/span> delta<\/span>;<\/span><\/p>
}<\/span>Node<\/span>;<\/span><\/p>
typedef<\/span> <\/span>struct<\/span> <\/span>Layer<\/span> <\/span>{<\/span><\/p>
    <\/span>int<\/span> numOfNodes<\/span>;<\/span><\/p>
    Node nodes<\/span>[<\/span>1200<\/span>]<\/span>;<\/span><\/p>
}<\/span>Layer<\/span>;<\/span><\/p><\/pre>\n
\u0422\u0430\u043a \u043a\u0430\u043a \u044d\u0442\u043e \u043f\u0440\u043e\u0441\u0442\u043e\u0439 C, \u043c\u044b \u043d\u0435 \u043c\u043e\u0436\u0435\u043c \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c std::vector \u0438 \u043d\u0430\u043c \u043d\u0443\u0436\u0435\u043d \u043f\u0440\u043e\u0441\u0442\u043e\u0439 C, \u043f\u043e\u0442\u043e\u043c\u0443 \u0447\u0442\u043e \u043f\u0440\u0438\u0432\u0435\u0434\u0435\u043d\u043d\u044b\u0439 \u0432\u044b\u0448\u0435 \u043a\u043e\u0434 \u0431\u0443\u0434\u0435\u0442 \u0441\u043a\u043e\u043c\u043f\u0438\u043b\u0438\u0440\u043e\u0432\u0430\u043d \u0438 \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d \u0440\u0435\u0430\u043b\u044c\u043d\u044b\u043c GPU.  \u041d\u043e \u043c\u044b \u043f\u0440\u0438\u0431\u043b\u0438\u0436\u0430\u0435\u043c\u0441\u044f \u043a \u044d\u0442\u043e\u043c\u0443.  \u041e\u0431\u0440\u0430\u0442\u0438\u0442\u0435 \u0432\u043d\u0438\u043c\u0430\u043d\u0438\u0435, \u0447\u0442\u043e \u043b\u0443\u0447\u0448\u0435, \u0447\u0435\u043c \u043c\u0430\u0441\u0441\u0438\u0432 \u0441 \u043f\u0440\u0435\u0434\u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u043d\u043e\u0439 \u0434\u043b\u0438\u043d\u043e\u0439, \u043a\u0430\u0436\u0434\u044b\u0439 \u0440\u0430\u0437 \u0432\u044b\u0434\u0435\u043b\u044f\u0442\u044c \u043d\u0435\u043e\u0431\u0445\u043e\u0434\u0438\u043c\u043e\u0435 \u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0441\u0442\u0432\u043e \u0432 \u043f\u0430\u043c\u044f\u0442\u0438, \u043d\u043e \u044d\u0442\u043e \u0432 \u0434\u0440\u0443\u0433\u043e\u0439 \u0440\u0430\u0437.<\/p>\n
\u041c\u044b \u0441\u043e\u0437\u0434\u0430\u0435\u043c \u043d\u0430\u0448\u0438 \u0431\u0430\u0437\u043e\u0432\u044b\u0435 \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u044b \u0434\u043b\u044f \u0443\u0437\u043b\u0430 \u0438 \u0441\u043b\u043e\u044f, \u043f\u043e\u044d\u0442\u043e\u043c\u0443 \u043f\u0440\u0438\u0448\u043b\u043e \u0432\u0440\u0435\u043c\u044f \u0437\u0430\u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043c\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043d\u0430\u0441\u0442\u043e\u044f\u0449\u0443\u044e \u0441\u0435\u0442\u044c, \u043a\u043e\u0442\u043e\u0440\u0430\u044f \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 \u0441\u043e\u0431\u043e\u0439 \u043f\u0440\u043e\u0441\u0442\u043e \u043d\u0430\u0431\u043e\u0440 \u0441\u043b\u043e\u0435\u0432.<\/p>\n
\u041d\u0435\u0439\u0440\u043e\u043d\u043d\u0430\u044f \u0441\u0435\u0442\u044c<\/h2>\n
h_netVec <\/span>=<\/span> newNetVec<\/span>;<\/span><\/p>
Layer <\/span>*<\/span>inputLayer <\/span>=<\/span> <\/span>layer<\/span>(<\/span>h_netVec<\/span>[<\/span>0<\/span>]<\/span>,<\/span> <\/span>0<\/span>)<\/span>;<\/span><\/p>
h_layers<\/span>.<\/span>push_back<\/span>(<\/span>*<\/span>inputLayer<\/span>)<\/span>;<\/span><\/p>
for<\/span> <\/span>(<\/span>unsigned<\/span> <\/span>int<\/span> i <\/span>=<\/span> <\/span>1<\/span>;<\/span> i <\/span><<\/span>h_netVec<\/span>.<\/span>size<\/span>(<\/span>)<\/span>;<\/span> i<\/span>++<\/span>)<\/span><\/p>
{<\/span><\/p>
    Layer <\/span>*<\/span>hidlayer <\/span>=<\/span> <\/span>layer<\/span>(<\/span>h_netVec<\/span>[<\/span>i<\/span>]<\/span>,<\/span> h_netVec<\/span>[<\/span>i <\/span>-<\/span> <\/span>1<\/span>]<\/span>)<\/span>;<\/span><\/p>
    h_layers<\/span>.<\/span>push_back<\/span>(<\/span>*<\/span>hidlayer<\/span>)<\/span>;<\/span><\/p>
}<\/span><\/p><\/pre>\n
\u0412\u043e\u0442 \u043e\u043d\u043e.  \u041d\u0430\u0448\u0430 \u043f\u0440\u043e\u0441\u0442\u0430\u044f \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u0430\u044f \u0441\u0435\u0442\u044c \u043d\u0430\u043f\u0438\u0441\u0430\u043d\u0430 \u043d\u0430 C++.  \u041f\u043e \u0441\u0443\u0442\u0438, \u044d\u0442\u043e \u043d\u0435 \u0431\u043e\u043b\u0435\u0435 \u0447\u0435\u043c \u0432\u0435\u043a\u0442\u043e\u0440 \u0441\u043b\u043e\u0435\u0432, \u0433\u0434\u0435 \u043a\u0430\u0436\u0434\u044b\u0439 \u0441\u043b\u043e\u0439 \u044f\u0432\u043b\u044f\u0435\u0442\u0441\u044f \u0432\u0435\u043a\u0442\u043e\u0440\u043e\u043c \u0443\u0437\u043b\u043e\u0432.  \u0412\u044b \u043c\u043e\u0436\u0435\u0442\u0435 \u043f\u043e\u0434\u0443\u043c\u0430\u0442\u044c, \u0447\u0442\u043e \u043d\u0430\u0448\u0430 \u0440\u0430\u0431\u043e\u0442\u0430 \u0437\u0434\u0435\u0441\u044c \u0441\u0434\u0435\u043b\u0430\u043d\u0430.  \u0425\u0430-\u0445\u0430!  \u041c\u044b \u0434\u0430\u0436\u0435 \u043d\u0435 \u0431\u043b\u0438\u0437\u043a\u0438.  \u041c\u044b \u0434\u043e\u043b\u0436\u043d\u044b \u043e\u0431\u0443\u0447\u0430\u0442\u044c \u043d\u0430\u0448\u0443 \u0441\u0435\u0442\u044c \u043d\u0430 \u0440\u0435\u0430\u043b\u044c\u043d\u044b\u0445 \u0434\u0430\u043d\u043d\u044b\u0445.  \u042d\u0442\u043e \u0432\u0440\u0435\u043c\u044f, \u043a\u043e\u0433\u0434\u0430 OpenCL \u0432\u0441\u0442\u0443\u043f\u0430\u0435\u0442 \u0432 \u0438\u0433\u0440\u0443.<\/p>\n
\u0413\u0440\u0430\u0444\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u043f\u0440\u043e\u0446\u0435\u0441\u0441\u043e\u0440 \u043d\u0435 \u043c\u043e\u0436\u0435\u0442 \u043f\u043e\u043b\u0443\u0447\u0438\u0442\u044c \u0434\u043e\u0441\u0442\u0443\u043f \u043a \u044d\u0442\u0438\u043c \u0432\u0435\u043a\u0442\u043e\u0440\u0430\u043c, \u043f\u043e\u044d\u0442\u043e\u043c\u0443 \u043c\u044b \u0434\u043e\u043b\u0436\u043d\u044b \u043f\u0440\u0435\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u0442\u044c \u0438\u0445 \u0432 \u0434\u0440\u0443\u0433\u0443\u044e \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u0443, \u043d\u0430\u0437\u044b\u0432\u0430\u0435\u043c\u0443\u044e \u0431\u0443\u0444\u0435\u0440\u043e\u043c, \u0431\u0430\u0437\u043e\u0432\u044b\u043c \u044d\u043b\u0435\u043c\u0435\u043d\u0442\u043e\u043c OpenCL.  \u041d\u043e \u043b\u043e\u0433\u0438\u043a\u0430 \u0442\u043e\u0447\u043d\u043e \u0442\u0430\u043a\u0430\u044f \u0436\u0435, \u043a\u0430\u043a \u0438 \u0440\u0430\u043d\u044c\u0448\u0435.<\/p>\n
\u0411\u0443\u0444\u0435\u0440\u044b OpenCL<\/h2>\n
d_InputBuffer <\/span>=<\/span> cl<\/span>::<\/span>Buffer<\/span>(<\/span>OpenCL<\/span>::<\/span>clcontext<\/span>,<\/span> CL_MEM_READ_WRITE<\/span>,<\/span> <\/span>sizeof<\/span>(<\/span>float<\/span>)<\/span>*<\/span>inpdim<\/span>*<\/span>inpdim<\/span>)<\/span>;<\/span><\/p>
tempbuf <\/span>=<\/span> cl<\/span>::<\/span>Buffer<\/span>(<\/span>OpenCL<\/span>::<\/span>clcontext<\/span>,<\/span> CL_MEM_READ_WRITE<\/span>,<\/span> <\/span>sizeof<\/span>(<\/span>Node<\/span>)<\/span>*<\/span>h_layers<\/span>[<\/span>0<\/span>]<\/span>.<\/span>numOfNodes<\/span>)<\/span>;<\/span><\/p>
(<\/span>OpenCL<\/span>::<\/span>clqueue<\/span>)<\/span>.<\/span>enqueueWriteBuffer<\/span>(<\/span>tempbuf<\/span>,<\/span>CL_TRUE<\/span>,<\/span>0<\/span>,<\/span>sizeof<\/span>(<\/span>Node<\/span>)<\/span>*<\/span>h_layers<\/span>[<\/span>0<\/span>]<\/span>.<\/span>numOfNodes<\/span>,<\/span>h_layers<\/span>[<\/span>0<\/span>]<\/span>.<\/span>nodes<\/span>)<\/span>;<\/span><\/p>
d_layersBuffers<\/span>.<\/span>push_back<\/span>(<\/span>tempbuf<\/span>)<\/span>;<\/span><\/p>
for<\/span> <\/span>(<\/span>int<\/span> i <\/span>=<\/span> <\/span>1<\/span>;<\/span> i<\/span><<\/span>h_layers<\/span>.<\/span>size<\/span>(<\/span>)<\/span>;<\/span> i<\/span>++<\/span>)<\/span> <\/span>{<\/span><\/p>
    tempbuf <\/span>=<\/span> cl<\/span>::<\/span>Buffer<\/span>(<\/span>OpenCL<\/span>::<\/span>clcontext<\/span>,<\/span> CL_MEM_READ_WRITE<\/span>,<\/span> <\/span>sizeof<\/span>(<\/span>Node<\/span>)<\/span>*<\/span>h_layers<\/span>[<\/span>i<\/span>]<\/span>.<\/span>numOfNodes<\/span>)<\/span>;<\/span><\/p>
    <\/span>(<\/span>OpenCL<\/span>::<\/span>clqueue<\/span>)<\/span>.<\/span>enqueueWriteBuffer<\/span>(<\/span>tempbuf<\/span>,<\/span> CL_TRUE<\/span>,<\/span>0<\/span>,<\/span> <\/span>sizeof<\/span>(<\/span>Node<\/span>)<\/span>*<\/span>h_layers<\/span>[<\/span>i<\/span>]<\/span>.<\/span>numOfNodes<\/span>,<\/span> h_layers<\/span>[<\/span>i<\/span>]<\/span>.<\/span>nodes<\/span>)<\/span>;<\/span><\/p>
    d_layersBuffers<\/span>.<\/span>push_back<\/span>(<\/span>tempbuf<\/span>)<\/span>;<\/span><\/p>
}<\/span><\/p><\/pre>\n
\u041d\u0435 \u0437\u0430\u043f\u0443\u0442\u0430\u0439\u0442\u0435\u0441\u044c \u0432\u043e \u0432\u0441\u0435\u0445 \u044d\u0442\u0438\u0445 “cl::”, “clqueue” \u0438 “context”.  \u042d\u0442\u043e \u0432\u0435\u0449\u0438 OpenCL.  \u041b\u043e\u0433\u0438\u043a\u0430 \u043e\u0441\u0442\u0430\u0435\u0442\u0441\u044f \u043d\u0435\u043e\u0441\u044f\u0437\u0430\u0435\u043c\u043e\u0439.<\/p>\n
\u041f\u0440\u0435\u0436\u0434\u0435 \u0447\u0435\u043c \u043c\u044b \u043f\u043e\u0433\u0440\u0443\u0437\u0438\u043c\u0441\u044f \u0432 \u0437\u0430\u0445\u0432\u0430\u0442\u044b\u0432\u0430\u044e\u0449\u0443\u044e \u0447\u0430\u0441\u0442\u044c, \u043c\u044b \u0434\u043e\u043b\u0436\u043d\u044b \u0441\u0434\u0435\u043b\u0430\u0442\u044c \u0435\u0449\u0435 \u043e\u0434\u043d\u0443 \u0432\u0435\u0449\u044c.  \u041c\u044b \u0434\u043e\u043b\u0436\u043d\u044b \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0438\u0442\u044c \u044f\u0434\u0440\u0430 OpenCL.  \u042f\u0434\u0440\u0430 \u2014 \u044d\u0442\u043e \u0444\u0430\u043a\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u043a\u043e\u0434, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0435\u0442\u0441\u044f \u0433\u0440\u0430\u0444\u0438\u0447\u0435\u0441\u043a\u0438\u043c \u043f\u0440\u043e\u0446\u0435\u0441\u0441\u043e\u0440\u043e\u043c.  \u0412\u0441\u0435\u0433\u043e \u043d\u0430\u043c \u043d\u0443\u0436\u043d\u043e 3 \u044f\u0434\u0440\u0430:<\/p>\n
    \n
  • \u041e\u0434\u0438\u043d \u0434\u043b\u044f \u043f\u0440\u044f\u043c\u043e\u0433\u043e \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0435\u043d\u0438\u044f<\/li>\n
  • \u041e\u0434\u0438\u043d \u0434\u043b\u044f \u043e\u0431\u0440\u0430\u0442\u043d\u043e\u0433\u043e \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0435\u043d\u0438\u044f \u0432 \u0432\u044b\u0445\u043e\u0434\u043d\u043e\u043c \u0441\u043b\u043e\u0435<\/li>\n
  • \u041e\u0434\u0438\u043d \u0434\u043b\u044f \u043e\u0442\u0441\u0442\u0430\u043b\u044b\u0445 \u0432 \u0441\u043a\u0440\u044b\u0442\u043e\u043c \u0441\u043b\u043e\u0435<\/li>\n<\/ul>\n
    \u044f\u0434\u0440\u043e<\/h2>\n
    compoutKern <\/span>=<\/span> cl<\/span>::<\/span>Kernel<\/span>(<\/span>OpenCL<\/span>::<\/span>clprogram<\/span>,<\/span> <\/span>\"compout\"<\/span>)<\/span>;<\/span><\/p>
    backpropoutKern <\/span>=<\/span> cl<\/span>::<\/span>Kernel<\/span>(<\/span>OpenCL<\/span>::<\/span>clprogram<\/span>,<\/span> <\/span>\"backpropout\"<\/span>)<\/span>;<\/span><\/p>
    bakckprophidKern <\/span>=<\/span> cl<\/span>::<\/span>Kernel<\/span>(<\/span>OpenCL<\/span>::<\/span>clprogram<\/span>,<\/span> <\/span>\"backprophid\"<\/span>)<\/span>;<\/span><\/p><\/pre>\n
    \u0422\u044b \u0443\u0433\u0430\u0434\u0430\u043b.  \u041d\u0430\u0441\u0442\u0430\u043b\u0430 \u043e\u0447\u0435\u0440\u0435\u0434\u044c GPU.  \u042f \u043d\u0435 \u0431\u0443\u0434\u0443 \u0432\u0434\u0430\u0432\u0430\u0442\u044c\u0441\u044f \u0432 \u043f\u043e\u0434\u0440\u043e\u0431\u043d\u043e\u0441\u0442\u0438 \u043e \u0442\u043e\u043c, \u043a\u0430\u043a \u0440\u0430\u0431\u043e\u0442\u0430\u0435\u0442 OpenCL \u0438 \u043a\u0430\u043a GPU \u043e\u0431\u0440\u0430\u0431\u0430\u0442\u044b\u0432\u0430\u0435\u0442 \u0434\u0430\u043d\u043d\u044b\u0435, \u043d\u043e \u043a\u043e\u0435-\u0447\u0442\u043e \u043d\u0443\u0436\u043d\u043e \u043f\u043e\u043c\u043d\u0438\u0442\u044c:<\/p>\n
      \n
    1. \u0413\u0440\u0430\u0444\u0438\u0447\u0435\u0441\u043a\u0438\u0435 \u043f\u0440\u043e\u0446\u0435\u0441\u0441\u043e\u0440\u044b \u0438\u043c\u0435\u044e\u0442 \u043c\u043d\u043e\u0433\u043e \u044f\u0434\u0435\u0440, \u043f\u043e\u044d\u0442\u043e\u043c\u0443 \u043e\u043d\u0438 \u043f\u043e\u0434\u0445\u043e\u0434\u044f\u0442 \u0434\u043b\u044f \u0440\u0430\u0441\u043f\u0430\u0440\u0430\u043b\u043b\u0435\u043b\u0438\u0432\u0430\u043d\u0438\u044f.<\/li>\n
    2. \u041c\u044b \u0441\u0447\u0438\u0442\u0430\u0435\u043c, \u0447\u0442\u043e \u043a\u0430\u0436\u0434\u043e\u0435 \u044f\u0434\u0440\u043e \u200b\u200b\u0437\u0430\u043f\u0443\u0441\u043a\u0430\u0435\u0442 \u043a\u043e\u0434 \u0434\u043b\u044f \u043e\u0434\u043d\u043e\u0433\u043e \u0443\u0437\u043b\u0430 \u0441\u043b\u043e\u044f.<\/li>\n
    3. \u041a\u043e\u0433\u0434\u0430 \u0432\u044b\u0447\u0438\u0441\u043b\u0435\u043d\u0438\u044f \u0441\u043b\u043e\u044f \u0437\u0430\u0432\u0435\u0440\u0448\u0435\u043d\u044b, \u043c\u044b \u043f\u0435\u0440\u0435\u0445\u043e\u0434\u0438\u043c \u043a \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0435\u043c\u0443 \u0441\u043b\u043e\u044e \u0438 \u0442\u0430\u043a \u0434\u0430\u043b\u0435\u0435.<\/li>\n<\/ol>\n
      \u041e\u0431\u0440\u0430\u0442\u043d\u043e\u0435 \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0435\u043d\u0438\u0435<\/h2>\n
      \u0418\u043c\u0435\u0439\u0442\u0435 \u044d\u0442\u043e \u0432 \u0432\u0438\u0434\u0443, \u0442\u0435\u043f\u0435\u0440\u044c \u043c\u044b \u043c\u043e\u0436\u0435\u043c \u043b\u0435\u0433\u043a\u043e \u043f\u043e\u043d\u044f\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u0444\u0440\u0430\u0433\u043c\u0435\u043d\u0442:<\/p>\n
      kernel <\/span>void<\/span> <\/span>compout<\/span>(<\/span>  global Node<\/span>*<\/span>  nodes<\/span>,<\/span>global Node <\/span>*<\/span> prevnodes<\/span>,<\/span>int<\/span> softflag<\/span>)<\/span><\/p>
      {<\/span><\/p>
          <\/span>const<\/span> <\/span>int<\/span> n <\/span>=<\/span> <\/span>get_global_size<\/span>(<\/span>0<\/span>)<\/span>;<\/span><\/p>
          <\/span>const<\/span> <\/span>int<\/span> i <\/span>=<\/span> <\/span>get_global_id<\/span>(<\/span>0<\/span>)<\/span>;<\/span><\/p>
          <\/span>float<\/span> t <\/span>=<\/span> <\/span>0<\/span>;<\/span><\/p>
          <\/span>for<\/span> <\/span>(<\/span> <\/span>int<\/span> j <\/span>=<\/span> <\/span>0<\/span>;<\/span> j <\/span><<\/span> nodes<\/span>[<\/span>i<\/span>]<\/span>.<\/span>numberOfWeights<\/span>;<\/span> j<\/span>++<\/span>)<\/span><\/p>
             t <\/span>+=<\/span> nodes<\/span>[<\/span>i<\/span>]<\/span>.<\/span>weights<\/span>[<\/span>j<\/span>]<\/span> <\/span>*<\/span> prevnodes<\/span>[<\/span>j<\/span>]<\/span>.<\/span>output<\/span>;<\/span><\/p>
      t<\/span>+=<\/span>0.1<\/span>;<\/span><\/p>
      nodes<\/span>[<\/span>i<\/span>]<\/span>.<\/span>output <\/span>=<\/span>sigmoid<\/span>(<\/span>t<\/span>)<\/span>;<\/span><\/p>
      }<\/span><\/p><\/pre>\n
      \u0410 \u0434\u043b\u044f \u043e\u0431\u0440\u0430\u0442\u043d\u043e\u0433\u043e \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0435\u043d\u0438\u044f \u0438\u043c\u0435\u0435\u043c:<\/p>\n
      kernel <\/span>void<\/span> <\/span>backprophid<\/span>(<\/span>global Node<\/span>*<\/span>  nodes<\/span>,<\/span>global Node <\/span>*<\/span> prevnodes<\/span>,<\/span>global Node <\/span>*<\/span>nextnodes<\/span>,<\/span>int<\/span> nextnumNodes<\/span>,<\/span>float<\/span> a<\/span>)<\/span><\/p>
      {<\/span><\/p>
      const<\/span> <\/span>int<\/span> n <\/span>=<\/span> <\/span>get_global_size<\/span>(<\/span>0<\/span>)<\/span>;<\/span><\/p>
      const<\/span> <\/span>int<\/span> i <\/span>=<\/span> <\/span>get_global_id<\/span>(<\/span>0<\/span>)<\/span>;<\/span><\/p>
      float<\/span> delta <\/span>=<\/span> <\/span>0<\/span>;<\/span><\/p>
      for<\/span> <\/span>(<\/span>int<\/span> j <\/span>=<\/span> <\/span>0<\/span>;<\/span> j <\/span>!=<\/span>nextnumNodes<\/span>;<\/span> j<\/span>++<\/span>)<\/span><\/p>
          delta <\/span>+=<\/span> nextnodes<\/span>[<\/span>j<\/span>]<\/span>.<\/span>delta <\/span>*<\/span> nextnodes<\/span>[<\/span>j<\/span>]<\/span>.<\/span>weights<\/span>[<\/span>i<\/span>]<\/span>;<\/span><\/p>
      delta <\/span>*=<\/span> <\/span>devsigmoid<\/span>(<\/span>nodes<\/span>[<\/span>i<\/span>]<\/span>.<\/span>output<\/span>)<\/span>;<\/span>break<\/span>;<\/span><\/p>
      nodes<\/span>[<\/span>i<\/span>]<\/span>.<\/span>delta <\/span>=<\/span> delta<\/span>;<\/span><\/p>
      for<\/span> <\/span>(<\/span>int<\/span> j <\/span>=<\/span> <\/span>0<\/span>;<\/span> j <\/span>!=<\/span> nodes<\/span>[<\/span>i<\/span>]<\/span>.<\/span>numberOfWeights<\/span>;<\/span> j<\/span>++<\/span>)<\/span><\/p>
              nodes<\/span>[<\/span>i<\/span>]<\/span>.<\/span>weights<\/span>[<\/span>j<\/span>]<\/span> <\/span>-=<\/span> a<\/span>*<\/span>delta<\/span>*<\/span>prevnodes<\/span>[<\/span>j<\/span>]<\/span>.<\/span>output<\/span>;<\/span><\/p>
      }<\/span><\/p>
      kernel <\/span>void<\/span> <\/span>backpropout<\/span>(<\/span>global Node<\/span>*<\/span>  nodes<\/span>,<\/span>global Node <\/span>*<\/span> prevnodes<\/span>,<\/span>global <\/span>float<\/span>*<\/span> targets<\/span>,<\/span>float<\/span> a<\/span>,<\/span>int<\/span> softflag <\/span>)<\/span><\/p>
      {<\/span><\/p>
      const<\/span> <\/span>int<\/span> n <\/span>=<\/span> <\/span>get_global_size<\/span>(<\/span>0<\/span>)<\/span>;<\/span><\/p>
      const<\/span> <\/span>int<\/span> i <\/span>=<\/span> <\/span>get_global_id<\/span>(<\/span>0<\/span>)<\/span>;<\/span><\/p>
      float<\/span> delta<\/span>=<\/span>0<\/span>;<\/span><\/p>
      delta <\/span>=<\/span> <\/span>(<\/span>nodes<\/span>[<\/span>i<\/span>]<\/span>.<\/span>output<\/span>-<\/span>targets<\/span>[<\/span>i<\/span>]<\/span>)<\/span>*<\/span>devsigmoid<\/span>(<\/span>nodes<\/span>[<\/span>i<\/span>]<\/span>.<\/span>output<\/span>)<\/span>;<\/span><\/p>
      for<\/span> <\/span>(<\/span>int<\/span> j <\/span>=<\/span> <\/span>0<\/span>;<\/span> j <\/span>!=<\/span>nodes<\/span>[<\/span>i<\/span>]<\/span>.<\/span>numberOfWeights<\/span>;<\/span> j<\/span>++<\/span>)<\/span><\/p>
          nodes<\/span>[<\/span>i<\/span>]<\/span>.<\/span>weights<\/span>[<\/span>j<\/span>]<\/span> <\/span>-=<\/span> a<\/span>*<\/span>delta<\/span>*<\/span>prevnodes<\/span>[<\/span>j<\/span>]<\/span>.<\/span>output<\/span>;<\/span><\/p>
      nodes<\/span>[<\/span>i<\/span>]<\/span>.<\/span>delta<\/span>=<\/span>delta<\/span>;<\/span><\/p>
      }<\/span><\/p><\/pre>\n
      \u0415\u0441\u043b\u0438 \u0432\u044b \u0447\u0443\u0432\u0441\u0442\u0432\u0443\u0435\u0442\u0435 \u0441\u0435\u0431\u044f \u043f\u043e\u0442\u0435\u0440\u044f\u043d\u043d\u044b\u043c, \u043f\u043e\u0437\u0432\u043e\u043b\u044c\u0442\u0435 \u043c\u043d\u0435 \u043d\u0430\u043f\u043e\u043c\u043d\u0438\u0442\u044c \u0432\u0430\u043c \u0443\u0440\u0430\u0432\u043d\u0435\u043d\u0438\u044f \u0434\u043b\u044f \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u0430 \u043e\u0431\u0440\u0430\u0442\u043d\u043e\u0433\u043e \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0435\u043d\u0438\u044f:<\/p>\n
      <\/p>\n
          
      \n  \"\u0423\u0440\u0430\u0432\u043d\u0435\u043d\u0438\u044f\"<\/p>\n
          <\/span><\/p>\n
      \u0422\u0435\u043f\u0435\u0440\u044c \u0432\u0441\u0435 \u0438\u043c\u0435\u0435\u0442 \u0441\u043c\u044b\u0441\u043b, \u0432\u0435\u0440\u043d\u043e?<\/p>\n
      \u041d\u0443 \u0432\u043e\u0442 \u0438 \u0432\u0441\u0435.  \u0412\u0441\u0435, \u0447\u0442\u043e \u043d\u0430\u043c \u043d\u0443\u0436\u043d\u043e \u0441\u0434\u0435\u043b\u0430\u0442\u044c, \u044d\u0442\u043e \u0437\u0430\u0433\u0440\u0443\u0437\u0438\u0442\u044c \u043d\u0430\u0448\u0438 \u0434\u0430\u043d\u043d\u044b\u0435 \u0438 \u0437\u0430\u043f\u0443\u0441\u0442\u0438\u0442\u044c \u044f\u0434\u0440\u0430.  \u042f \u043d\u0435 \u0437\u043d\u0430\u044e, \u043f\u043e\u043d\u044f\u043b\u0438 \u043b\u0438 \u0432\u044b \u044d\u0442\u043e, \u043d\u043e \u043c\u044b \u0437\u0430\u043a\u043e\u043d\u0447\u0438\u043b\u0438.  \u041c\u044b \u043f\u0440\u043e\u0441\u0442\u043e \u0441\u043e\u0437\u0434\u0430\u0435\u043c \u043d\u0430\u0448\u0443 \u0441\u0435\u0442\u044c Neura \u043f\u043e\u043b\u043d\u043e\u0441\u0442\u044c\u044e \u0441 \u043d\u0443\u043b\u044f \u0438 \u043e\u0431\u0443\u0447\u0430\u0435\u043c \u0435\u0435 \u0440\u0430\u0431\u043e\u0442\u0435 \u0441 GPU.<\/p>\n
      \u0414\u043b\u044f \u043f\u043e\u043b\u0443\u0447\u0435\u043d\u0438\u044f \u043f\u043e\u043b\u043d\u043e\u0433\u043e \u043a\u043e\u0434\u0430 \u043f\u043e\u0441\u0435\u0442\u0438\u0442\u0435 \u043c\u043e\u0439 \u0440\u0435\u043f\u043e\u0437\u0438\u0442\u043e\u0440\u0438\u0439 github: \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0430 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0445 \u0441\u0435\u0442\u0435\u0439.<\/p>\n
      \u0412 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0435\u0439 \u0447\u0430\u0441\u0442\u0438 \u043c\u044b \u0440\u0430\u0441\u0448\u0438\u0440\u0438\u043c \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0443, \u0432\u043a\u043b\u044e\u0447\u0438\u0432 \u0432 \u043d\u0435\u0435 \u0441\u0432\u0435\u0440\u0442\u043e\u0447\u043d\u044b\u0435 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0435 \u0441\u0435\u0442\u0438.  \u0421\u043b\u0435\u0434\u0438\u0442\u0435 \u0437\u0430 \u043e\u0431\u043d\u043e\u0432\u043b\u0435\u043d\u0438\u044f\u043c\u0438…<\/p>\n
      \n
      \"\u041a\u043d\u0438\u0433\u0430