Modal Labs compiled a detailed glossary to solve the problem they themselves encountered when working with graphics processors in the Modal service.
The documentation is fragmented and it's often very difficult to compare concepts at different levels of the stack.
Modal Labs (the Modal brand) read the PDF documentation from NVIDIA, delved into thematic Discord communities, and even bought paper textbooks to compile a knowledge base that covers the entire stack in one place:
☞ CUDA cores, SM, tensor cores, warp schedulers;
☞ Streams, PTX, memory hierarchy;
☞ Roofline, divergence;
☞ Nvcc, nvidia-smi, cuBLAS, Nsight, libcuda.
In the guide, all pages are linked together, so you can go to the section on Warp Scheduler to better understand the streams you read about in the article on the CUDA programming model.
The project itself is open and available on Source and GitHub
#AI #ML #GPU #Glossary #Modal
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