Hi, I think it’s hard to believe that DLA is more energy efficient.
I used trtexec to examine inference time and energy consumption of model.
I used Resnet-50 caffe prototxt, but I removed last layer(softmax) and renamed last fully connected layer to prob, to avoid GPUfallback.
The command I used was something like this :
./trtexec --avgRuns=100 --deploy=../models/Resnet_without_prob.prototxt --fp16 --batch=8 --iterations=10000 --output=prob --useDLACore=0 --useSpinWait ./trtexec --avgRuns=100 --deploy=../models/Resnet_without_prob.prototxt --fp16 --batch=8 --iterations=10000 --output=prob --useSpinWait
I examined power consumption with tegrastats. And calculated (img/sec)/(Total Power consumption).
But using GPU with FP16 was always more efficient than DLA with FP16. (I tried MAX N mode, and 15W mode. Both tested after sudo jetson_clocks)
Of course DLA’s power consumption was low, but VDDRQ, SOC, CPU all these stuffs also needed energy, and DLA’s inference time was slower, so total power consumption was bad.
Could you give me some examples that I can check DLA is more energy efficient??
I’m really sorry.
I found if I use other networks, such as GoogleNet, using DLA can be more energy efficient.