During December 2024, Balin developed a comprehensive OpenVINO Aurora GPU inference tutorial for the argonne-lcf/user-guides repository. He reintroduced a previously commented-out C++ example, providing a complete ResNet50 inference workflow that includes model loading, input data generation, and GPU-based inference. The solution leveraged C++, CMake, and GPU computing technologies such as SYCL and OpenCL to bridge CPU and GPU execution, offering vendor-agnostic parallel programming guidance. By documenting setup and build steps, Balin streamlined onboarding for new developers, reducing time-to-first-run and delivering practical, actionable instructions for running OpenVINO-based GPU inference on the Aurora system.