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M2K: Making the Model-Kernel Interface Explicit for Reliable CUDA Kernel Verification
Large language model (LLM) inference systems rely on CUDA kernels for core GPU computations, yet the interface between models and kernels is implicit and poorly specified. Models and kernels evolve independently and often make incompatible assumptions about tensor shapes and input sizes, leading to
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