module: inductor oncall: pt2 triagedThis issue has been looked at a team member, and triaged and prioritized into an appropriate moduleThis issue has been looked at a team member, and triaged and ...

For reference, that's roughly the same bandwidth as a 40GB Nvidia A100 PCIe card with HBM2, but a heck of a lot more power. This means that, without optimizations to make the model less demanding, ...

In recent years, with the development of deep learning (DL), deep learning has made great contributions to the improvement of motor imagination brain-computer interface (MI-BCI). At the same time, the ...

Due to the parallel computing features of the Attention mechanism, on the NVIDIA A100-PCIE 40GB graphics card and CUDA 11.6 server, the training time of each epoch is reduced by 3-5s compared to the ...

The GPUs inside these liquid-cooled cards will have the same specs as those in the air-cooled cards. This means they will not run faster, and, for instance, the liquid-cooled A100 PCIe card will still ...

The direct-to-chip cooling cards will use just one PCIe slot in a server, rather than the two required by air-cooled ones. The company said that it partnered with Equinix to test out the new servers, ...

🐛 Describe the bug Calling nn.Conv2d (..., group=n) is slower than manually executing n separate convolutions. import torch as ch from torch import nn from torch.profiler import profile, ...

For example, SZTAKI, the Institute for Computer Science and Control, uses NVIDIA HGX™ A100-powered servers to perform AI research in medical processing, machine learning, and language processing.