Agent skill · software engineering · nvidia
tilegym-converting-cutile-to-julia
Converts cuTile Python GPU kernels (@ct.kernel) to cuTile.jl Julia equivalents. Handles kernel syntax translation, 0-indexed to 1-indexed conversion, broadcasting differences, memory layout (row-major to column-major), type system mapping, and launch API differences. Use when converting, porting, or translating cuTile Python kernels to Julia cuTile.jl, or debugging/optimizing existing Julia cuTile translations.
Why this skill is useful
Adds a comprehensive conversion script and workflow for translating cuTile Python kernels to Julia, including error handling and testing procedures.
What it needs
Requires cuda, julia installed locally. About 4k tokens when loaded. Last updated 2026-08-07. 2,816 stars on the source repository.
What this skill does
cuTile Python → cuTile.jl (Julia) Conversion Convert @ct.kernel Python kernels to Julia function ... end cuTile.jl kernels. Workflow Selection Standard conversion → Full workflow: translations/workflow.md Errors (CodegenErrors, MethodError, UndefVarError, numerical mismatch) → references/debugging.md Quick reference → references/api-mapping.md + references/critical-rules.md Test patterns → references/testing.md Architecture Julia kernels are standalone — no Python bridge, no pytest integration. The Julia sub-project lives in julia/ at the repo root with its own Project.toml for dependency management. Ground-truth reference: Always consult julia/kernels/.jl and julia/test/.jl for patterns that compile and pass tests. These are the canonical examples of working cuTile.jl code. Instructions 1. Analyze the Python kernel: identify patterns, shapes, dtypes, operations 2. Write Julia kernel — julia/kernels/<op>.jl with cuTile.jl kernel + bridge function(s) 3. Convert kernel signature (see translations/workflow.md Phase 2) 4. Convert kernel body (apply references/api-mapping.md + references/critical-rules.md) 5. Write Julia test — julia/test/test<op>.jl using Test stdlib + NNlib.jl for reference 6. Register test — add include(...) in julia/test/runtests.jl 7. Validate — run the bundled validator: python <skill-dir>/scripts/validatecutilejl.py <file.jl> 8. Test — run julia --project=julia/ julia/test/runtests.jl Full conversion checklist with post-conversion verification → translations/workflow.md ⚠️ Top Pitfalls The most dangerous translation errors. Full rules (18 total) in references/critical-rules.md. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/tilegym-converting-cutile-to-julia