What frameworks / models / GPUs, etc., do you want to see for comparison?

[u39kun]

This is an open thread for requests.

[u39kun]

Pre-orderd a 2080 Ti. I plan on posting results when I get it (should arrive early Oct.)

[clhne]

When use to training ,RTX 2080 Ti and TiTan V, which do you prefer ?

Thanks.

[clhne]

Could you compare the inference framework, such as Tensorflow Lite ,PaddlePaddle,TEngine,etc.
Thanks.

[jaapkroe]

A recent MxNet build would interesting to see in this comparison

[stefan-it]

@u39kun Here are the results for TensorFlow on the following system:

• AMD Ryzen 7 2700X CPU
• G.Skill Trident Z, 32 GB, CL14 14-14-34
• ASRock X470 Taichi Ultimate
• TensorFlow 1.12 for CUDA 10 + cudnn 7.3.1
• nvidia-docker with nvidia/cuda:10.0-cudnn7-devel

For a Zotac RTX 2070 AMP Extreme:

Precision	vgg16 eval	vgg16 train	resnet152 eval	resnet152 train
32-bit	42.6ms	130.6ms	65.1ms	264.2ms
16-bit	29.0ms	94.2ms	39.5ms	183.9ms

For a Zotac RTX 2080 TI:

Precision	vgg16 eval	vgg16 train	resnet152 eval	resnet152 train
32-bit	29.0ms	91.4ms	43.6ms	191.2ms
16-bit	18.7ms	60.2ms	25.5ms	135.0ms

[EmilPi]

Hi,
I am really interested to see mxnet benchmark. Please include it if possible.

[Ark-kun]

It would be great to have some AMD GPUs tested. See ROCm/tensorflow-upstream#173

[peterdu989]

Hi,
RX 3080 vs RX6800XT please

[HudenJear]

This code works well on the AMD rocm system.
12700K+6800XT
Pytorch1.12.1(ROCM5.1)
Test without MIOpen:
pytorch's vgg16 eval at fp32: 32.9ms avg
pytorch's vgg16 train at fp32: 126.4ms avg
pytorch's resnet152 eval at fp32: 48.9ms avg
pytorch's resnet152 train at fp32: 184.8ms avg
pytorch's densenet161 eval at fp32: 45.4ms avg
pytorch's densenet161 train at fp32: 170.6ms avg

pytorch's vgg16 eval at fp16: 19.9ms avg
pytorch's vgg16 train at fp16: 92.8ms avg
pytorch's resnet152 eval at fp16: 28.1ms avg
pytorch's resnet152 train at fp16: 132.8ms avg
pytorch's densenet161 eval at fp16: 37.8ms avg
pytorch's densenet161 train at fp16: 136.9ms avg

Hi, RX 3080 vs RX6800XT please