What is shared memory? How is it used in your operating system? How is it used in PyTorch? What's shared memory good for in deep learning? Why use multiple processes rather than one process on a single node? What's the point of PyTorch's shared memory manager? How are allocators for shared memory implemented? How does CUDA shared memory work? What is the difference between CUDA shared memory and CPU shared memory? How did we implement safer CUDA shared memory?

Further reading.

• Implementations of vanilla shared memory allocator https://github.com/pytorch/pytorch/blob/master/aten/src/TH/THAllocator.cpp and the fancy managed allocator https://github.com/pytorch/pytorch/blob/master/torch/lib/libshm/libshm.h
• Multiprocessing best practices describes some things one should be careful about when working with shared memory https://pytorch.org/docs/stable/notes/multiprocessing.html
• More details on how CUDA shared memory works https://pytorch.org/docs/stable/multiprocessing.html#multiprocessing-cuda-sharing-details