PyTorch 1.7.1-fosscuda-2020b

There is a newer install of PyTorch

PyTorch provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system.

Accessing PyTorch 1.7.1-fosscuda-2020b

To load the module for PyTorch 1.7.1-fosscuda-2020b please use this command on the BEAR systems (BlueBEAR, BEAR Cloud VMs, and CaStLeS VMs):

module load PyTorch/1.7.1-fosscuda-2020b

There is a CPU version of this module: PyTorch 1.7.1-foss-2020b

BEAR Apps Version

2020b

Architectures

EL8-icelake (GPUs: NVIDIA A100, NVIDIA A30)

The listed architectures consist of two part: OS-CPU. The OS used 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.

More Information

For more information visit the PyTorch website.

Dependencies

This version of PyTorch has a direct dependency on: cuDNN/8.0.4.30-CUDA-11.1.1 FFmpeg/4.3.1-GCCcore-10.2.0 fosscuda/2020b GMP/6.2.0-GCCcore-10.2.0 magma/2.5.4-fosscuda-2020b MPFR/4.1.0-GCCcore-10.2.0 NCCL/2.8.3-CUDA-11.1.1 Ninja/1.10.1-GCCcore-10.2.0 numactl/2.0.13-GCCcore-10.2.0 Pillow/8.0.1-GCCcore-10.2.0 protobuf/3.14.0-GCCcore-10.2.0 protobuf-python/3.14.0-GCCcore-10.2.0 pybind11/2.6.0-GCCcore-10.2.0 Python/3.8.6-GCCcore-10.2.0 PyYAML/5.3.1-GCCcore-10.2.0 SciPy-bundle/2020.11-fosscuda-2020b typing-extensions/3.7.4.3-GCCcore-10.2.0

Required By

This version of PyTorch is a direct dependent of: DECODE/0.10.0-fosscuda-2020b

Other Versions

These versions of PyTorch are available on the BEAR systems (BlueBEAR, BEAR Cloud VMs, and CaStLeS VMs). These will be retained in accordance with our Applications Support and Retention Policy.

Last modified on 24th February 2021