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086a1f8861
This commit introduces utility tools for building, testing, and analyzing
Composable Kernel. The tools are designed to be LLM-agnostic and can be
used with any AI assistant or directly from the command line.
Tools Added:
============
1. ck-docker - Docker container management
- Start/stop ROCm-enabled containers
- Build targets with CMake + Ninja
- Run tests with gtest filters
- Auto-detect GPU targets (gfx950, gfx942, etc.)
- Per-user, per-branch container naming to avoid conflicts
2. ck-build-analysis - Build time profiling
- Uses Clang's -ftime-trace for compilation analysis
- Aggregates statistics across multiple trace files
- Identifies template instantiation bottlenecks
- Generates detailed Markdown reports with:
* Compilation phase breakdown
* Top expensive instantiations
* Template family analysis
* Data-driven optimization recommendations
- Configurable granularity (1µs to 500µs)
- PEP 723 compliant Python script with auto-dependency management via uv
Key Features:
=============
- LLM-agnostic design (works with any AI assistant)
- Zero-configuration setup with automatic dependency installation
- Comprehensive documentation in script/tools/README*.md
- Security hardening (input validation, no command injection)
- Multi-file trace aggregation for accurate build analysis
- Jinja2-based report generation for customizable output
Implementation:
===============
- script/tools/ck-docker - Main Docker orchestration script
- script/tools/ck-build-analysis - Build analysis orchestration
- script/tools/common.sh - Shared utilities (container mgmt, GPU detection)
- script/tools/analyze_build_trace.py - PEP 723 compliant Python analyzer
- script/tools/templates/ - Jinja2 templates for report generation
- script/tools/README*.md - Comprehensive documentation
Directory Structure:
====================
script/tools/
├── README.md # Main overview
├── README_ck-docker.md # ck-docker documentation
├── README_ck-build-analysis.md # ck-build-analysis documentation
├── ck-docker # Docker orchestration script
├── ck-build-analysis # Build analysis orchestration
├── common.sh # Shared utilities
├── analyze_build_trace.py # Python analyzer (PEP 723)
└── templates/
└── build_analysis_report.md.jinja # Report template
The tools follow Unix philosophy: do one thing well, compose easily,
and work from both CLI and programmatic contexts.
2.1 KiB
2.1 KiB
ck-docker
Build and test composable_kernel in Docker with ROCm support.
Terminal Usage
Direct command-line usage:
# From composable_kernel directory
script/tools/ck-docker start
script/tools/ck-docker build test_amdgcn_mma
script/tools/ck-docker test test_amdgcn_mma --gtest_filter=*Fp16*
script/tools/ck-docker status
script/tools/ck-docker shell
# Or add to PATH
export PATH="$PATH:$PWD/script/tools"
ck-docker start
LLM Assistant Integration
If using an LLM assistant, you can ask in natural language:
- "Start the docker container"
- "Build test_amdgcn_mma"
- "Run test_amdgcn_mma with filter Fp16"
- "Check container status"
- "Open a shell in the container"
Commands
ck-docker start [name] Start Docker container
ck-docker build [target] [--reconfigure] Build target (optionally reconfigure CMake)
ck-docker test <name> [options] Run test
ck-docker shell [name] Interactive shell
ck-docker status [name] Check status
ck-docker stop [name] Stop container
Configuration
- Image: rocm/composable_kernel:ck_ub24.04_rocm7.0.1
- GPU: Auto-detected via rocminfo (fallback: gfx950)
- Compiler: /opt/rocm/llvm/bin/clang++
- Build: Ninja + CMake (Release)
- Mount: Current directory → /workspace
- Container Name: Auto-generated as
ck_<username>_<branch>to avoid clashes
Environment
export CK_CONTAINER_NAME=my_build # Override default container name
export CK_DOCKER_IMAGE=rocm/composable_kernel:ck_ub24.04_rocm7.0.1 # Override Docker image
export GPU_TARGET=gfx942 # Override GPU target detection
Examples
# Start container
ck-docker start
# Build and run test
ck-docker build test_amdgcn_mma
ck-docker test test_amdgcn_mma
# Force clean CMake reconfiguration and build
ck-docker build --reconfigure test_amdgcn_mma
# Custom container
ck-docker start my_build
ck-docker build test_amdgcn_mma --name my_build
ck-docker test test_amdgcn_mma --name my_build
# Debug
ck-docker shell
ck-docker status