Add real CuPy - CUDA in Python QuickByte#260
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Replaces the previously dead CuPy_on_CARC.ipynb link (issue #151, which was never actually added to the repo) with an actual tested tutorial: installing CuPy on Easley, basic array usage, and a real CPU-vs-GPU matmul benchmark run on an l40s GPU. Found and documented two real install gotchas along the way: - conda-forge's default cupy package pulls CUDA 13.x, which needs a newer driver than Easley's GPU nodes have (cudaErrorInsufficientDriver) - use the cupy-cuda12x pip wheel instead. - That wheel alone can't JIT-compile kernels (e.g. cupy.random) without the [ctk] extra, which bundles CUDA toolkit headers. Also includes a "Going Further" section on multi-GPU CuPy with NCCL and MPI, based on the CS491/591 HPC course's Lecture 20 slides - explicitly marked as conceptual/untested since a full working multi-GPU script wasn't verified for this QuickByte.
The two REPL snippets showed >>> commands and their printed output in the same code block. Split each into a command block and a separate "Expected output" block, matching this session's convention.
This was referenced Jul 7, 2026
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Summary
Related to #151. The README's "CuPy - Cuda in Python" link pointed to
CuPy_on_CARC.ipynb, which was never actually added to the repo (checked full history/all branches, no trace of it) — a 404 since it was written. This adds real content instead of just removing the dead link (see companion PR #258 for the minimal link-removal fix to the same issue, which no longer touches this README line so the two don't conflict).New
cupy_intro.mdcovers:cupy.ndarray,cupy.asnumpy)Test plan
conda install -c conda-forge cupyfails on Easley withcudaErrorInsufficientDriver(pulls CUDA 13.x, driver is R570 which only supports up to CUDA 12.x) — documented the fix (pip install cupy-cuda12x[ctk]).asnumpyverified in a live Python session on an l40s GPU.