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OpenVINO version is 2018.2.300
OS Ubuntu 16.04.03
Platform Core i5-8400
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[Summary]
Compare the performance of GPU & CPU by running demo script "demo_squeezenet_download_convert_run.sh"
- CPU mode, Average running time of one iteration: 2.27222 ms
- GPU mode, Average running time of one iteration: 5.77997 ms
It's unreasonable that GPU took much longer for an iteration. Could anyone advise what happened and how to improve GPU performance? Thanks!
Edward
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[Output Message: CPU Mode]
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[Output Message: GPU Mode]
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Hi Edward,
Sorry for the confusion.
Actually, the sample you choose is not good one to compare performance.
"classification_sample" is to show how to load inference engine, read network, run inference, and read output.
And just one time execution with still image.
There is one thing to understand when you run inference on GPU engine. (clDNN)
It bases OpenCL and it compiles kernels at run time, just once per execution.
So, single run with still image is not a good sample which you can check performance difference.
You'd be better choose other samples if you want to see performance difference.
Please try script I attached in this thread,
You should modify input files and components paths according to your installation env.
This is example for face, age, gender, head pose detection with USB camera.
One is using CPU for all detection and the other is using GPU for all detection.
You will see performance differences, definitely.
Please check "fps" numbers from screen and check CPU usage from "System monitor".
Regards,
Peter.
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Hi Edward,
Sorry for the confusion.
Actually, the sample you choose is not good one to compare performance.
"classification_sample" is to show how to load inference engine, read network, run inference, and read output.
And just one time execution with still image.
There is one thing to understand when you run inference on GPU engine. (clDNN)
It bases OpenCL and it compiles kernels at run time, just once per execution.
So, single run with still image is not a good sample which you can check performance difference.
You'd be better choose other samples if you want to see performance difference.
Please try script I attached in this thread,
You should modify input files and components paths according to your installation env.
This is example for face, age, gender, head pose detection with USB camera.
One is using CPU for all detection and the other is using GPU for all detection.
You will see performance differences, definitely.
Please check "fps" numbers from screen and check CPU usage from "System monitor".
Regards,
Peter.
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Hi Peter,
Thanks a lot for sharing the script. I had tried it. It showed significant performance difference between CPU and GPU modes.
regards!
Edward
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