What do I see performance and numerical accuracy issues with quantized INT8 deep learning networks using GPU Coder in R2021a?

3 Ansichten (letzte 30 Tage)
I’m generating code for a quantized deep learning network using GPU Coder but experiencing performance and numerical accuracy issues when using INT8 precision with cuDNN 8.
What versions of cuDNN are supported by GPU Coder in R2021a?

Akzeptierte Antwort

Bill Chou
Bill Chou am 24 Mär. 2021
In R2021a, GPU Coder supports cuDNN 8.1.0. For more information, see Installing Prerequisite Products (GPU Coder). It is recommended to use this version of cuDNN as other versions have significant performance and accuracy issues with INT8 workflows.
When using GPU Coder with cuDNN 8.0.x to generate CUDA code for a quantized deep learning network in INT8 precision, you may experience different issues depending on the version of cuDNN 8.0 used. The table below summarizes the issues you may experience.

Weitere Antworten (0)

Kategorien

Mehr zu Deep Learning with GPU Coder finden Sie in Help Center und File Exchange

Produkte


Version

R2021a

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by