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SKILL.md
npx skills add nvidia/skills --skill 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.
npx skills add nvidia/skills --skill tilegym-converting-cutile-to-julia
Convert @ct.kernel Python kernels to Julia function ... end cuTile.jl kernels.
translations/workflow.mdMethodError, IRError, numerical mismatch) → references/debugging.mdreferences/api-mapping.md + references/critical-rules.mdreferences/testing.mdJulia 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.
julia/kernels/<op>.jl with cuTile.jl kernel + bridge function(s)translations/workflow.md Phase 2)references/api-mapping.md + references/critical-rules.md)julia/test/test_<op>.jl using Test stdlib + NNlib.jl for referenceinclude(...) in julia/test/runtests.jlpython <skill-dir>/scripts/validate_cutile_jl.py <file.jl>julia --project=julia/ julia/test/runtests.jlFull conversion checklist with post-conversion verification → translations/workflow.md
The most dangerous translation errors. Full rules (17 total) in references/critical-rules.md.
| # | Pitfall | One-line fix |
|---|---|---|
| 1 | ct.full() doesn't exist in Julia | Use fill(val, shape), zeros(T, dims...), or ones(T, dims...) |
| 2 | max(a, b) on tiles → IRError | Use max.(a, b) (broadcast dot) |
| 3 | IRError / MethodError mentioning IRStructurizer | Compiler bug — file upstream with minimal reproducer |
| 4 | ct.launch arg order silently wrong | Args are positional — match kernel signature exactly |
| 5 | ct.load with order — index positions wrong | order remaps BOTH shape AND index (Critical Rule 16) |
Side-by-side Python → Julia conversions matching the released Julia kernels in julia/kernels/. Each directory contains cutile_python.py (before) and cutile_julia.jl (after).
| # | Example | Key Patterns | When to Reference |
|---|---|---|---|
| 01 | add | 1D ct.load/ct.store, alpha scaling, scalar broadcast, fill/zeros, keyword load/store | Starting point; basic TMA + element-wise patterns |
| 02 | matmul | muladd, TF32 conversion, K-loop with for, 2D swizzle, standard Julia layout, ct.@compiler_options | MMA / tensor core operations |
| 03 | softmax | Persistent scheduling, for loops, gather/scatter, padding_mode, multi-pass | Large-tensor reduction patterns |
These match the released kernels in julia/kernels/ (add.jl, matmul.jl, softmax.jl). The examples are simplified teaching versions — always consult julia/kernels/*.jl for the canonical, tested implementations.
| Category | Document | Content |
|---|---|---|
| Workflows | translations/workflow.md | Full conversion workflow with todo list, validation loop, checklist |
| Rules | references/critical-rules.md | 17 Critical Rules for cuTile Python → Julia conversion |
| API | references/api-mapping.md | Python↔Julia bidirectional API mapping + kernel patterns |
| Testing | references/testing.md | Julia-native test patterns, tolerances, failure diagnosis |
| Debugging | references/debugging.md | Julia-specific error diagnosis + IR debug commands |
| Scripts | scripts/validate_cutile_jl.py | Static validation for Julia anti-patterns (run it) |
| Ground Truth | julia/kernels/*.jl + julia/test/*.jl | Actual working implementations in the codebase |
Prerequisite — Julia: this skill requires the Julia version declared in julia/Project.toml under [compat] julia. If julia --version is missing or older than that, install from the official Julia site at https://julialang.org/install/ following the verified installer instructions for your OS. Resume below once julia --version is compatible.
Then, from the repo root:
Requirements:
julia/Project.toml under [compat] julia)julia/Project.toml: CUDA.jl, cuTile.jl, NNlib.jl, Test# Install Julia dependencies declared in julia/Project.toml
julia --project=julia/ -e 'using Pkg; Pkg.instantiate()'
# Run tests
julia --project=julia/ julia/test/runtests.jl