Profiling GPU (CUDA) — Introducing GPU Flight

Last year, I took a GPU programming course at Johns Hopkins University as part of my graduate studies, where I learned CUDA programming. For my final project, I built a lightweight GPU monitoring and profiling tool focused on CUDA. I enjoyed the process so much that I decided to continue developing it beyond the course. In this post, I’d like to briefly introduce the project: GPU Flight — a 100% open-source GPU observability tool GitHub: https://github.com/gpu-flight/gpufl-client Why I Started GPU Flight When profiling a CUDA application, you typically: Install profiling tools such as Nsight Or manually integrate CUPTI into your application, which often makes the code complex and difficult to manage Deal with additional complexity in cloud or containerized environments This workflow can be inconvenient — especially in production systems. I wanted something lighter. Something that works more like a flight recorder for GPUs . So I built GPU Flight. Instead of requiring heavy tooling at r