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  • 向量算子优化Vector Operation Optimization

    向量算子优化Vector Operation Optimization

    查看MATLAB命令View MATLAB Command

    示例显示Simulink®编码器™ ,将生成向量的块输出,设置为标量,优化生成的代码,例如Mux、Sum、Gain和Bus。这种优化通过用局部变量替换临时局部数组来减少堆栈内存。

    示例模型Example Model

    模型采用矢量优化rtwdemo_VectorOptimization,增益块G1和G2的输出为矢量信号tmp1和tmp2。向量的宽度为10。

    model = 'rtwdemo_VectorOptimization';

    open_system(model);

    set_param(model, 'SimulationCommand', 'update')

     

    Generate Code

    为生成和检查过程,创建临时文件夹(在系统临时文件夹中)。

    currentDir = pwd;

    [~,cgDir] = rtwdemodir();

    Build the model.

    rtwbuild(model)

    ### Starting build procedure for: rtwdemo_VectorOptimization

    ### Successful completion of build procedure for: rtwdemo_VectorOptimization

     

    Build Summary

     

    Top model targets built:

     

    Model                       Action                       Rebuild Reason                                   

    ===========================================================================================================

    rtwdemo_VectorOptimization  Code generated and compiled  Code generation information file does not exist. 

     

    1 of 1 models built (0 models already up to date)

    Build duration: 0h 0m 25.92s

    The optimized code is in rtwdemo_VectorOptimization.c. The signals tmp1 and tmp2 are the local variables rtb_tmp1 and rtb_tmp2.

    cfile = fullfile(cgDir,'rtwdemo_VectorOptimization_grt_rtw',...

        'rtwdemo_VectorOptimization.c');

    rtwdemodbtype(cfile,'/* Model step', '/* Model initialize', 1, 0);

    /* Model step function */

    void rtwdemo_VectorOptimization_step(void)

    {

      real_T rtb_Sum3;

      real_T rtb_tmp1;

      real_T rtb_tmp2;

      int32_T i;

      for (i = 0; i < 10; i++) {

        /* Gain: '<Root>/G2' incorporates:

         *  UnitDelay: '<Root>/X2'

         */

        rtb_tmp2 = 0.3 * rtwdemo_VectorOptimization_DW.X2_DSTATE[i];

     

        /* Gain: '<Root>/G1' incorporates:

         *  UnitDelay: '<Root>/X1'

         */

        rtb_tmp1 = 0.2 * rtwdemo_VectorOptimization_DW.X1_DSTATE[i];

     

        /* Sum: '<Root>/Sum3' incorporates:

         *  Gain: '<Root>/G3'

         *  Inport: '<Root>/In2'

         *  Sum: '<Root>/Sum1'

         *  Sum: '<Root>/Sum2'

         *  UnitDelay: '<Root>/X3'

         */

        rtb_Sum3 = ((rtwdemo_VectorOptimization_U.In2[i] - 0.4 *

                     rtwdemo_VectorOptimization_DW.X3_DSTATE[i]) - rtb_tmp2) -

          rtb_tmp1;

     

        /* Outport: '<Root>/Out2' */

        rtwdemo_VectorOptimization_Y.Out2[i] = rtb_Sum3;

     

        /* Update for UnitDelay: '<Root>/X3' */

        rtwdemo_VectorOptimization_DW.X3_DSTATE[i] = rtb_tmp2;

     

        /* Update for UnitDelay: '<Root>/X2' */

        rtwdemo_VectorOptimization_DW.X2_DSTATE[i] = rtb_tmp1;

     

        /* Update for UnitDelay: '<Root>/X1' */

        rtwdemo_VectorOptimization_DW.X1_DSTATE[i] = rtb_Sum3;

      }

    }

    关闭模型和代码生成报告

    bdclose(model)

    rtwdemoclean;

    cd(currentDir)

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  • 原文地址:https://www.cnblogs.com/wujianming-110117/p/14306052.html
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