I am a newbee with TensorRT.
I am trying to use TensorRT on my dev computer equipped with a GTX 1060.
When optimizing my caffe net with my c++ program (designed from the samples provided with the library), I get the following message
“Half2 support requested on hardware without native FP16 support, performance will be negatively affected.”
when I try to use FP16. I get the same message with a GTX 1080 on a second computer.
I am using cuda 8.0.0 and cudnn 6.
My question is :
is FP16 supported on these gpus ?
is there a minimum driver version (mine is 375.26)
FP16 is supported but at a low rate. So performance won’t be interesting. The driver version you have should be fine. I would recommend using CUDA 8.0.61 (CUDA 8 GA2) which is what is currently publicly available.
The only GPUs with full-rate FP16 performance are Tesla P100, Quadro GP100, and Jetson TX1/TX2.
All GPUs with compute capability 6.1 (e.g. GTX 1050, 1060, 1070, 1080, Pascal Titan X, Titan Xp, Tesla P40, etc.) have low-rate FP16 performance. It’s not the fast path on these GPUs. All of these GPUs should support “full rate” INT8 performance, however.
Thanks for the information. I have another question.
Does TensorRT support INT8 inference on 9X0 series?
The information shows TensorRT support GPU capability 6.1, so how do I use TendorRT on GTX980?
Thanks
All GPUs of compute capability 3.0 and higher can be used with TF. The level of effort may vary depending on how you install or setup TF, and which version.
With a bit of Google-ing you can probably find more benchmark data. Gaming != AI. Which GPUs will be cost effective will depend on your workloads and usage patterns.