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Support for nVidia tensorcore #2104
Description
More of a feature request than a problem report and forgive my ignorance if this is irrelevant but the nvidia 20x series and the 1660ti have tensor cores which could be use when called out on the nvidia driver using the fp16 extension. tensorflow does it that way. Is there a way to implement this on dlib?
see references
https://www.pugetsystems.com/labs/hpc/TensorFlow-Performance-with-1-4-GPUs----RTX-Titan-2080Ti-2080-2070-GTX-1660Ti-1070-1080Ti-and-Titan-V-1386/
https://medium.com/@noel_kennedy/how-to-use-half-precision-float16-when-training-on-rtx-cards-with-tensorflow-keras-d4033d59f9e4
https://www.pugetsystems.com/labs/hpc/NVIDIA-Titan-V-plus-Tensor-cores-Considerations-and-Testing-of-FP16-for-Deep-Learning-1141/
https://www.servethehome.com/nvidia-geforce-rtx-2060-super-review/5/
Activity
davisking commentedon Jun 16, 2020
Yeah, you can't use fp16 with dlib's dnn tooling right now. It's all fp32. If someone wants to go and update it to support fp16 that would be neat, although it's somewhat non-trivial.