Profile GPU kernels when performance analysis or optimization is required.
Profile GPU kernels when performance analysis or optimization is required. Use for AMD ROCm GPU metrics, bandwidth, cache hit rates, coalescing, or kernel timing.This is the skill's description: the text your AI reads to decide when the skill applies.
intellikit-skill/SKILL.md
---
name: metrix-profiling
description: Profile GPU kernels when performance analysis or optimization is required. Use for AMD ROCm GPU metrics, bandwidth, cache hit rates, coalescing, or kernel timing.
---
# Metrix: GPU Profiling
Profile AMD GPU kernels and get human-readable metrics (bandwidth, cache, coalescing, FLOPS). Architecture is auto-detected.
## When to Use
- User asks to profile a GPU application or kernel
- Performance analysis, optimization, or bottleneck investigation
- Need HBM/L2/L1 bandwidth, hit rates, or compute metrics
- Need timing-only runs (fast, no hardware counters)
## Instructions
1. **Ensure the target runs on AMD ROCm** (e.g. `hipcc`-built binary or Python script that launches HIP/ROCm kernels).
2. **Choose execution path:**
- If a Metrix MCP server is available, use its profile tool with the same options below.
- Otherwise run the CLI or Python API from the environment where Metrix is installed.
### CLI