CUDA Python Kernel Authoring
summary
Deploy steps use Brev and a GCP L4 GPU, CUDA 12.8 instance, then install the CUDA toolkit (apt repo) because pip alone misses NVRTC. Examples use CuPy and cuDF and both pip/UV and conda/miniforge paths; a compiled C++ CUDA kernel runs with block=256 and grid computed by ceil, matrix multiply and reduce succeed. JIT compile shows a first-call pause (about 4 s then ~4 ms on repeat). Real workloads drop multi‑day pipelines (11 days) to hours (4 hours).
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