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Found 2 Skills
Iteratively optimize cuTile kernel performance through systematic profiling, bottleneck analysis, IR comparison, and targeted tuning. Covers tile sizes, occupancy, autotune configs, TMA, latency hints, persistent scheduling, num_ctas, flush_to_zero, and IR-level debugging. Use when asked to "optimize cutile kernel", "improve kernel perf", "tune cutile performance", "make kernel faster", or iteratively benchmark and refine a cuTile GPU kernel in the TileGym project.
Operate a Serverless endpoint that already exists: diagnose queued jobs and dying workers, tune scaling, idle timeout and FlashBoot safely, pin the GPU selection, and manage the queue (cancel a job, purge). Read-only by default; changes only the exact setting the user authorized, with a read before and after. Use when the user has an endpoint and asks why it is slow, stuck or failing, or wants one of its settings changed through the Runpod MCP tools.