Hi guys:
I'm an developing an opencl application on MTK P60(Mali G72 mp3). But i have met some problems.
The application has been run successfully on snapdragon 660(GPU Adreno 512), the performance was about 10ms. But when I run it on Mali G72 mp3, it should cost 60ms! When I check the gpu_utilization, it's almost 100 percent.
Firstly, I couldn't find any specification about the flops performance with the Mali G72.(Adreno 512 GPU flops performance: 255 Gflops)
Secondly, according to benchmarks, performance of G72 mp3 should close to the Adreno 512. I can't find out why it should perform so bad on G72 mp3.
Welcome to talk about this. :)
Not all flops are equal - there is no point counting adders if you need multipliers, etc - so generally flops numbers are not that useful.
Assuming a GPU clocked at 650 MHz you get 12 fp32 FMAs per core per clock.If you count an FMA as 2 FLOPS, then you get 12 * 2 * 3 * 650M = 46G FLOPS of FP32 FMAs. If you write well vectorized FP16 then you get double that.
If you can share your CL kernel we can probably provide more targeted advice.
Cheers, Pete
My kernel code may not be posted to the public. But I can share it to you by private messages.(I don't know how to do that.)
Generally, when testing the flops, the GPU should be running at full capacity with float precision or half precision, which is what I wonder. I suspect that the G72 is not fully loaded when it runs 60ms. Is there any means I can confirm this?
DS-5 Streamline should let you capture performance counters for the GPU.
I profile my project and the timeline graph is on the above. Each cycle is about 120ms. Something seems wired.
(1). I enqueue kernels continually to the command queue. But there seem to be a tiny idle time, and the GPU restart at each new pass.
(2). When it comes into a new pass, the 'Mali Core Cycle' falls(I don't know what dose it means) instead of keeping a high value.
I don't know if it is enough to get some useful information.
The low spot does indeed look strange - the shader core definitely isn't fully loaded, even though the GPU cycles counter is high (so something is queued on the GPU).
Normally this occurs because there is a high volume of very small kernels which are not able to parallelize and fully load the GPU because they are so small with a low thread count. Without knowing exactly what you are trying to do it's going to be hard to provide more specific advice.
That's right. I enqueue more than 1 hundred kernels to the queue as one pass and cycle it. But 80% of them are very small kernels .(like relu and sum operation in CNN) And several convolution kernels costs 80% of the time.
Peter Harris said:very small kernels which are not able to parallelize and fully load the GPU because they are so small with a low thread count
I am not quiet understand those words mean. When kernels are small and GPU cycles counter is high, will it affect the GPU load? I have tuned their work group size, and each small kernel can dispatch hundreds of threads. How could the GPU core is not fully loaded?
View all questions in Graphics and Gaming forum