tilegym-improve-cutile-kernel-perf

# Iterative cuTile Kernel Performance Optimization Systematically profile, diagnose bottlenecks, and iteratively tune a cuTile kernel's performance in the TileGym repository. ## Instructions Follow the three phases in order: **Setup** the environment and baseline, run the **Experimentation** loop with a tracked log, then iterate **The experiment loop** until perf goals are met or further gains plateau. ## Setup Work with user to prepare optimization environment: 1. Create a fresh git branch: Propose a branch name, e.g., `cutile-perf-<kernel_name>-<date>` from current branch. Checkout `git checkout -b <branch name>` 2. Locate the target kernel: - cuTile kernels live under `src/tilegym/suites/<suite>/cutile/` or `src/tilegym/ops/cutile/` - Read the kernel file and identify: the `@ct.kernel` decorated function(s), the launch wrapper (`ct.launch()` or `ct_experimental.autotune_launch()`), the `@register_impl` registration, and current autotune configs (if any) 3. Classify the kernel: - Arithmetic Intensity < 10 -> Memory-bound - Arithmetic Intensity 10-50 -> Balanced - Arithmetic Intensity > 50 -> Compute-bound Note: classification is only used to pick the optimization priority order in the experiment loop. The **core metric** is always `latency (ms)`. 4. Check GPU environment: - Ensure a GPU node (Blackwell or Ampere GPU) is available - All subsequent benchmark commands should run on the GPU node 5. Study related references: - `references/optimizat...