There is a newer version of cuDNNThe NVIDIA CUDA Deep Neural Network library (cuDNN) is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. cuDNN is part of the NVIDIA Deep Learning SDK.
Accessing cuDNN 220.127.116.11-gcccuda-2019b
To load the module for cuDNN 18.104.22.168-gcccuda-2019b please use this command on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs):
module load cuDNN/22.214.171.124-gcccuda-2019b
BEAR Apps Version
EL8-cascadelake — EL8-haswell — Ubuntu20.04-haswell
The listed architectures consist of two part: OS-CPU.
- BlueBEAR: The OS used on BlueBEAR is represented by EL and there are several different processor (CPU) types available on BlueBEAR. More information about the processor types on BlueBEAR is available on the BlueBEAR Job Submission page.
- BEAR and CaStLeS Cloud VMs: These VMs can have one of two OSes. Those with access to a BEAR Cloud or CaStLeS VM should check that the listed architectures for an application include the OS of VM being used. The VMs, irrespective of OS, will use the haswell CPU type.
For more information visit the cuDNN website.
This version of cuDNN has a direct dependency on: gcccuda/2019b
This version of cuDNN is a direct dependent of: JAX/0.1.77-fosscuda-2019b-Python-3.7.4 PyTorch/1.4.0-fosscuda-2019b-Python-3.7.4 PyTorch/1.3.1-fosscuda-2019b-Python-3.7.4 PyTorch/1.6.0-fosscuda-2019b-Python-3.7.4 TensorFlow/2.0.0-fosscuda-2019b-Python-3.7.4 TensorFlow/1.15.0-fosscuda-2019b-Python-3.7.4 TensorFlow/2.2.0-fosscuda-2019b-Python-3.7.4 Theano/1.0.4-fosscuda-2019b-Python-3.7.4
These versions of cuDNN are available on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs). These will be retained in accordance with our Applications Support and Retention Policy.
Last modified on 19th November 2019