Choose CUDA Launch Configuration

What problem does it solve?

This Skill guides AI agents through selecting efficient CUDA thread block and grid dimensions to maximize occupancy while respecting register and shared memory constraints, tail effects, and cooperatively launched grids.

Core Features & Use Cases

• Occupancy analysis: estimate theoretical and actual active warps per SM for candidate block sizes.
• Resource-aware tuning: account for register usage, shared memory, and dynamic smem in planning launches.
• Use Case: optimize a kernel with significant shared memory and registers by choosing block sizes that maximize occupancy and minimize tail effects, while considering cooperative launch constraints.

Quick Start

Start by profiling kernel resource usage, then select a block size and grid that maximize occupancy within hardware limits.