The 2 AM kernel debugging session nobody warned you about Last month I was helping a friend debug a training pipeline that worked perfectly on his 4090 dev box but produced garbage loss values once it hit the cluster. No segfault. No cudaErrorInvalidValue . Just wrong numbers, intermittently. Six hours in, we found it: a kernel was writing one element past a shared memory buffer when blockDim.x happened to fall in a specific range. On the dev card the stomped bytes were padding. On the cluster they were the next thread block's working set. If you've written more than a few hundred lines of CUDA, you've hit some flavor of this. Let's walk through why GPU kernels go silently wrong, how to actually catch the bug, and what newer tooling — including some interesting Rust-based experiments — is trying to do about the underlying problem. Root cause: the kernel boundary breaks your safety net When you write host C++, you have a stack of tools that catch memory bugs early. ASan. Valgrind.…