Typically, researchers who want to try a new attention variant need to hand-code it directly from PyTorch operators. However, this could result in "slow runtime and CUDA OOMs." ...

As with CUDA, ROCm is an ideal solution for AI applications, as some deep-learning frameworks already support a ROCm backend (e.g., TensorFlow, PyTorch, MXNet, ONNX, CuPy, and more).

SEO: Python-like language promises to be easier to write than native CUDA and specialized GPU code but has performance comparable to what expert GPU coders can produce and better than standard ...

PyTorch is an open source, machine learning framework used for both research prototyping and production deployment. According to its source code repository, PyTorch provides two high-level features: ...

This isn’t necessarily a problem, but we’re currently at PyTorch 1.5, so you may find yourself running into deprecation warnings when trying to replicate code on the latest version.

The code to make PyTorch optimized to work better over ethernet was merged into the PyTorch 1.13 update that became generally available on Oct. 28.