Write the code
Open a CUDA C++ or Python project and make the change you want to understand.
Run CUDA in your browser. See what the GPU is really doing.
Write CUDA C++ or Python with Numba, run it on a real NVIDIA GPU with no local setup, and inspect the kernels, memory transfers, and execution timeline.
CUDA C++ and Python Real NVIDIA GPU No local CUDA setup
Watch the workflow
From CUDA source to a usable profile
Type → Run → Output One short GPU experiment
Create a free Workbench
Start with one project and Trace profiling. Limits vary by plan, and every run stops automatically after its short execution window.
Keep your code, run output, kernel launches, and GPU timeline together.
Already have an account? Sign inRun a short profile
Compile the saved revision and collect Trace data in a managed NVIDIA GPU sandbox.
Explain the behavior
Connect output, launches, transfers, utilization, and timeline evidence in one result.