Worked on stabilizing the CUDA backend for ggml-org/llama.cpp by addressing a critical bug in the 3D im2col kernel. Focused on improving the kernel’s handling of non-contiguous input tensors, the solution involved deriving source indices from the actual input strides rather than assuming contiguous layouts. This approach enhanced the correctness and robustness of tensor manipulation within the CUDA environment, reducing the risk of downstream computation errors. Leveraged expertise in CUDA programming and GPU optimization to ensure the kernel now supports a broader range of input layouts, thereby strengthening the reliability of llama.cpp for models requiring flexible tensor operations.