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SURF with CUDA is not faster by a noticeable amount

asked 2018-05-16 03:34:49 -0500

I wrote a program to compare the increase in performance between SURF with CUDA and without it. The implementation with CUDA only resulted in a speed up of 1.25x times.

The following is my code.

while (true) 
    {

        stream1.read(Frame_1);
        stream1.read(Frame_2);          

        cvtColor(Frame_1,Frame_1,CV_BGR2GRAY);
        cvtColor(Frame_2,Frame_2,CV_BGR2GRAY);
        float t1,t2;


        t1 = getTickCount();

        Ptr<xfeatures2d::SURF> surf = xfeatures2d::SURF::create();
        Mat descriptor_1,descriptor_2;
        vector<KeyPoint> keypoint_1,keypoint_2;

        surf->detect(Frame_1,keypoint_1);
        surf->compute(Frame_1,keypoint_1,descriptor_1);
        surf->detect(Frame_2,keypoint_2);
        surf->compute(Frame_2,keypoint_2,descriptor_2); 
        Ptr<DescriptorMatcher> dscMatcher = DescriptorMatcher::create("BruteForce");
        vector< vector< DMatch > >  matches;

        dscMatcher->knnMatch(descriptor_1,descriptor_2,matches,2);


        t1 = getTickCount() - t1;


        t2 = getTickCount();
        cuda::SURF_CUDA surf_cuda ;

        cuda::GpuMat key_1_GPU,key_2_GPU,desc_1_GPU,desc_2_GPU,img_1,img_2;
        img_1.upload(Frame_1);
        img_2.upload(Frame_2);
        surf_cuda(img_1,cuda::GpuMat(),key_1_GPU,desc_1_GPU);
        surf_cuda(img_2,cuda::GpuMat(),key_2_GPU,desc_2_GPU);

        surf_cuda.downloadKeypoints(key_1_GPU,keypoint_1);
        surf_cuda.downloadKeypoints(key_2_GPU,keypoint_2);

        Ptr<cuda::DescriptorMatcher> dscMatcher1 = cuda::DescriptorMatcher::createBFMatcher();
        vector< vector< DMatch > >  matches1;       
        dscMatcher1->knnMatch(desc_1_GPU,desc_2_GPU,matches1,2);
        t2 = getTickCount() - t2;

        cout << "No cuda : " << t1/getTickFrequency() << "    With Cuda : "<< t2/getTickFrequency() << endl;



        if (waitKey(30) >= 0)
        break;

    }

The output which is the time taken gave the following results on the average. Without CUDA it took 0.54 seconds and with CUDA it took 0.43 seconds. I am implementing the code on a NVidia Jetson TX2. The images that I am processing has a size of 900 x 1440.

Then I proceeded to do the test with ORB which only resulted in a speed up of 1.6 times.

A similar question was asked here, but wasn't answered. link

I am wondering whether the problem is with the code I wrote or is it with the hardware.

Some details

  • OpenCV 3.4
  • CUDA 9.0
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Comments

only partly related, but if you do not require rotational invariance, try SURF with the UPRIGHT flag. it's almost as fast as ORB, on CPU already.

berak gravatar imageberak ( 2018-05-16 04:30:04 -0500 )edit

So I initialized the pointer like this

Ptr<xfeatures2d::surf> surf = xfeatures2d::SURF::create(100,4,3,false,true);

cuda::SURF_CUDA surf_cuda(100,4,3,false,0.01f,true);

The time for the one without cuda reduced to 0.3 seconds while the one with cuda remained the same

Kenneth Joseph Paul gravatar imageKenneth Joseph Paul ( 2018-05-16 04:38:07 -0500 )edit

ok. maybe i get more bc. using smaller images.

also, just saying, your code measures the matching, too, which also consumes relevant time/computing-power)

berak gravatar imageberak ( 2018-05-16 04:50:21 -0500 )edit

I tried measuring it before the matching part

w/o CUDA : 0.48 s with CUDA: 0.33 s

Could it be a problem with the hardware?

Kenneth Joseph Paul gravatar imageKenneth Joseph Paul ( 2018-05-16 04:56:15 -0500 )edit

sorry, idk.

berak gravatar imageberak ( 2018-05-16 05:00:02 -0500 )edit

is there any standard test for comparing performance of CUDA against CPU?

Kenneth Joseph Paul gravatar imageKenneth Joseph Paul ( 2018-05-16 05:01:37 -0500 )edit

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answered 2018-05-28 08:39:39 -0500

I was able to solve the problem. I executed the following command to boost the clocks

sudo /home/ubuntu/jetson_clocks.sh

After that I could see a noticeable improvement in performance ( approx 2.5x)

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Asked: 2018-05-16 03:34:49 -0500

Seen: 51 times

Last updated: May 28