RTX 3090 vs A100 in deep learning.
124 vues (au cours des 30 derniers jours)
Afficher commentaires plus anciens
I ran ResNet on RTX 3090 and A100
Performance is better in RTX 3090 about 1.2 times than A100
I searched and found out that GPU Coder helps use TensorCore
So, I want to be sure if I use GPU Coder, A100's performance is going to better before I purchasing GPU Coder
Thanks.
0 commentaires
Réponse acceptée
Joss Knight
le 6 Mai 2022
According to the spec as documented on Wikipedia, the RTX 3090 has about 2x the maximum speed at single precision than the A100, so I would expect it to be faster. The A100 is much faster in double precision than the GeForce card.
Both will be using Tensor Cores for deep learning in MATLAB.
4 commentaires
Kyle Lee
le 10 Mai 2022
For understanding, I ask you to confirm.
Then, If other models like Alexnet, Googlenet etc.. are used , do these models automatically use Tensor Core?
Plus de réponses (1)
David Willingham
le 4 Mai 2022
Hi,
What version of MATLAB did you test ResNet out on? I'd recommend running benchmarks on the latest version of MATLAB.
Was it for inference or training?
AS an FYI, you can contact MathWorks and receive a trial of GPU Coder to test out the performance first hand.
0 commentaires
Voir également
Catégories
En savoir plus sur Get Started with GPU Coder dans Help Center et File Exchange
Produits
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!