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ermig1979 avatar ermig1979 commented on August 25, 2024

Hi. Could you to let know your info about your CPU ?

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teor292 avatar teor292 commented on August 25, 2024

I test it on two cpu: Intel Core I5-2500k and Intel Xeon CPU E3-1225 V3

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ermig1979 avatar ermig1979 commented on August 25, 2024

Is the performance decreasing strong?
If it is about 98-102% - then it is a measure error. Some of neural functions are limited by bandwidth of memory. So performance boosting is achieved when you use small image size which can be placed in CPU cache. In test framework try to use parameters -w=640 -h =480 instead of default values -w=1920 -h=1080.

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teor292 avatar teor292 commented on August 25, 2024

It is not strong, but AVX has 256 bit and SSE 128 bit, so I think it must be faster, not slower in any case. I test it not on test framework, but with my test program. For first image SSE give me 0.45 ms time and AVX 0.55 ms (on I5), for the second image (neural was the same, but with different input size of image) AVX 1.43 ms and SSE 1.38 ms (on Xeon). Of cource I can disable AVX, but I think that such results are strange.

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ermig1979 avatar ermig1979 commented on August 25, 2024

What is the function?

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teor292 avatar teor292 commented on August 25, 2024

NeuralSimple.txt
Here is simplify test function and neural architecture. It get 0.278 ms for AVX and 0.266 for SSE (and AVX2 get the same result as SSE).

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ermig1979 avatar ermig1979 commented on August 25, 2024

Neural is depricated now. Use Synet.

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