Get our free extension to see links to code for papers anywhere online!

Add to Chrome

Add to Firefox

Picture for Adel Chaibi

Adel Chaibi

Reduced Precision Strategies for Deep Learning: A High Energy Physics Generative Adversarial Network Use Case

Mar 18, 2021
Florian Rehm, Sofia Vallecorsa, Vikram Saletore, Hans Pabst, Adel Chaibi, Valeriu Codreanu, Kerstin Borras, Dirk Krücker

Figure 1 for Reduced Precision Strategies for Deep Learning: A High Energy Physics Generative Adversarial Network Use Case

Figure 2 for Reduced Precision Strategies for Deep Learning: A High Energy Physics Generative Adversarial Network Use Case

Figure 3 for Reduced Precision Strategies for Deep Learning: A High Energy Physics Generative Adversarial Network Use Case

Figure 4 for Reduced Precision Strategies for Deep Learning: A High Energy Physics Generative Adversarial Network Use Case

* ICPRAM 2021
* Submitted at ICPRAM 2021; from CERN openlab - Intel collaboration

Access Paper or Ask Questions