About nvidia-cuda
nvidia-cuda is a reference skill for NVIDIA CUDA programming, aimed at developers writing GPU kernels in CUDA C++ or Python. It organizes material on programming models, PTX, Blackwell tuning, and CUTLASS/CuTe through task-based indexes.
Key features
- 01CUDA C++ and Python kernel development
- 02PTX instruction set reference
- 03Blackwell performance tuning
- 04CUTLASS and CuTe GEMM guidance
- 05Task-based documentation navigation
Use cases
- 01Finding guidance for writing and building CUDA kernels
- 02Looking up PTX instructions and memory models
- 03Tuning workloads for Blackwell GPUs
- 04Implementing GEMM with CUTLASS or CuTe
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ fandhe-ai/ agent-reference-skills --skill nvidia-cudaAfter installing, type/nvidia-cudain Claude Code to confirm it loaded.
Bundled files
References and scripts installed along with SKILL.md.
references/advanced/appendices/compute-capabilities.mdcpp-language-extensions.mdcpp-language-support.mdcuda-cpp-execution-model.mdcuda-cpp-memory-model.mddevice-callable-apis.mdenvironment-variables.mdmathematical-functions.mdREADME.mdreferences/advanced/core/advanced-host-programming.mdadvanced-kernel-programming.mddriver-api.mdfeature-survey.mdmulti-gpu-systems.mdREADME.mdreferences/advanced/features/async-barriers.mdasync-copies.mdcluster-launch-control.mdcompute-fabric-transport.mdcooperative-groups.mdcuda-graphs.mddriver-entry-point-access.mddynamic-parallelism.mderror-log-management.mdextended-gpu-memory.mdgraphics-interop.mdgreen-contexts.mdinter-process-communication.mdl2-cache-control.mdlazy-loading.mdDetails
From the project READMEnvidia-cuda
NVIDIA CUDA — GPU 上で汎用並列計算を行うためのプログラミングモデル・ツールチェーン・ライブラリ群。 CUDA C++/Python によるカーネル記述、PTX ISA 命令セット、Blackwell アーキテクチャ向けチューニング、 CUTLASS/CuTe による高性能 GEMM 実装をカバーする。
ディレクトリ構成
skills/nvidia-cuda/
SKILL.md
references/
programming-model/
README.md
introduction.md
programming-model.md
cuda-platform.md
intro-to-cuda-cpp.md
intro-to-cuda-python.md
writing-cuda-kernels.md
writing-tile-kernels.md
asynchronous-execution.md
understanding-memory.md
nvcc.md
advanced/
README.md
core/
README.md
advanced-host-programming.md
advanced-kernel-programming.md
driver-api.md
multi-gpu-systems.md
feature-survey.md
features/
README.md
unified-memory.md
cuda-graphs.md
stream-ordered-memory-allocation.md
cooperative-groups.md
programmatic-dependent-launch.md
green-contexts.md
locality-domains.md
compute-fabric-transport.md
lazy-loading.md
error-log-management.md
async-barriers.md
pipelines.md
async-copies.md
cluster-launch-control.md
l2-cache-control.md
memory-sync-domains.md
inter-process-communication.md
virtual-memory-management.md
extended-gpu-memory.md
dynamic-parallelism.md
graphics-interop.md
driver-entry-point-access.md
appendices/
README.md
compute-capabilities.md
environment-variables.md
cpp-language-support.md
cpp-language-extensions.md
mathematical-functions.md
device-callable-apis.md
cuda-cpp-memory-model.md
cuda-cpp-execution-model.md
ptx-isa/
README.md
introduction.md
programming-model.md
machine-model.md
syntax.md
state-spaces-types-variables.md
instruction-operands.md
abi.md
memory-consistency-model.md
instruction-set-overview.md
instructions-arithmetic.md
instructions-comparison-logic.md
instructions-data-movement.md
instructions-texture-surface.md
instructions-control-flow.md
instructions-sync-communication.md
instructions-matrix-multiply.md
instructions-video-misc.md
special-registers.md
directives.md
pragma-strings.md
release-notes.md
blackwell-tuning/
README.md
architecture.md
best-practices.md
streaming-multiprocessor.md
memory-system.md
nvlink.md
cutlass/
README.md
cute-dsl/
README.md
overview.md
functionality.md
quick-start.md
cute-dsl.md
dsl-introduction.md
dsl-code-generation.md
dsl-control-flow.md
dsl-jit-arg-generation.md
dsl-dynamic-layout.md
dsl-struct-types.md
dsl-jit-caching.md
dsl-jit-compilation-options.md
dsl-types.md
framework-integration.md
debugging.md
iket-profiling.md
primitives-api.md
task-scheduling.md
ts-introduction.md
ts-resources.md
ts-pipelines.md
ts-schedules.md
ts-patterns.md
ts-validation.md
ts-printout.md
ts-allocators.md
ts-pipeline-groups.md
ts-pdl.md
ts-api-task-scheduling.md
ts-api-resources.md
ts-api-task.md
ts-api-task-manager.md
ts-api-schedule-builder.md
ts-api-memory.md
ts-api-pipeline-group.md
ts-api-pipeline.md
ts-api-enums.md
autotuning-gemm.md
compile-with-tvm-ffi.md
dsl-ahead-of-time-compilation.md
naming-conventions.md
deprecation-policy.md
mma-intro.md
mma-wmma-programming.md
mma-wgmma-programming.md
mma-tcgen05-programming.md
limitations.md
faqs.md
api-overview.md
api-cute.md
api-cute-arch.md
api-cute-runtime.md
api-cute-nvgpu.md
api-cute-nvgpu-common.md
api-cute-nvgpu-warp.md
api-cute-nvgpu-warpgroup.md
api-cute-nvgpu-cpasync.md
api-cute-nvgpu-tcgen05.md
api-pipeline.md
api-utils.md
api-utils-sm90.md
api-utils-sm100.md
operator-api/
README.md
overview.md
tutorials.md
tutorial-000-gemm.md
tutorial-001-gemm-fused-epilogue.md
tutorial-002-bring-your-own-kernel.md
tutorial-003-host-latency-best-practices.md
tutorial-004-fake-tensors.md
tutorial-005-grouped-gemm-contiguous-offset.md
tutorial-006-block-scaled-gemm.md
tutorial-007-heuristics.md
api-reference.md
api-operator.md
api-arguments.md
api-discovery.md
api-heuristics.md
api-metadata.md
api-misc.md
cpp/
README.md
overview.md
getting-started.md
quickstart.md
ide-setup.md
build.md
build-windows-visual-studio.md
build-clang-host-compiler.md
functionality.md
terminology.md
fundamental-types.md
programming-guidelines.md
gemm-heuristics.md
efficient-gemm.md
pipeline.md
profiler.md
gemm-performance-measurement.md
dependent-kernel-launch.md
blackwell.md
blackwell-sm100-gemm.md
blackwell-cluster-launch-control.md
code-organization.md
cute.md
cute-quickstart.md
cute-layout.md
cute-layout-algebra.md
cute-tensor.md
cute-algorithms.md
cute-mma-atom.md
cute-gemm-tutorial.md
cute-predication.md
cute-tma-tensors.md
cutlass-3x.md
cutlass-3x-design.md
cutlass-3x-backwards-compatibility.md
gemm-api-3x.md
cutlass-2x.md
layout-2x.md
gemm-api-2x.md
tile-iterator-concept.md
utilities.md
grouped-scheduler.md
implicit-gemm-convolution.md
samples/
README.md
async-copy-pipeline.md
cooperative-groups-reduction.md
cuda-graph-explicit-nodes.md
cuda-graph-stream-capture.md
cute-dsl-gemm.md
cutlass-cpp-device-gemm.md
cutlass-operator-api-gemm.md
explicit-memory-transfer.md
multi-gpu-peer-to-peer.md
shared-memory-tiled-matmul.md
stream-ordered-allocation.md
stream-overlap.md
tile-kernel-vector-add.md
unified-memory.md
vector-add-kernel.md
scripts/
README.md
install.md
nvcc-build.md
binary-utilities.md
sanitize.md
debug.md
nsight-systems.md
nsight-compute.md
gpu-query.md
cutlass-build.md
探索手順
タスクからカテゴリを引き、カテゴリの README.md で目的のページを特定する:
- 下記マッピング表でタスクに対応するカテゴリを探す
- そのカテゴリの
references/{category}/README.md(advanced/cutlass/はサブディレクトリの README.md)を参照して目的のページを特定する - 該当ページの
.mdを Read して詳細を確認する
GB10 Grace Blackwell 実機のハードウェア仕様・DGX OS・PXE/fleet 運用・playbook 起動手順は dgx-spark スキル、
リモート接続管理・VS Code 起動等のデスクトップアプリ操作は nvidia-sync スキルを参照。
本スキルは CUDA C++/Python の書き方・PTX 命令・CUTLASS API を担当する。
タスク → カテゴリ マッピング
| タスク | カテゴリ | 参照 README |
|---|---|---|
| CUDA とは何か・GPU 階層モデル・CUDA プラットフォームの全体像を知りたい | programming-model | references/programming-model/README.md |
| CUDA C++/Python でカーネルを書く、nvcc でビルドする、非同期実行・ストリームを扱う | programming-model | references/programming-model/README.md |
| advanced カテゴリ全体の構成(core / features / appendices)を確認したい | advanced | references/advanced/README.md |
| Driver API・マルチ GPU・advanced host/kernel programming を調べたい | advanced/core | references/advanced/core/README.md |
| CUDA Graphs / Cooperative Groups / Unified Memory / VMM / IPC / Green Contexts / Locality Domains / Compute Fabric Transport 等の機能 API を調べたい | advanced/features | references/advanced/features/README.md |
| Compute Capability・環境変数・C++ 言語拡張・メモリ/実行モデルの技術付録を調べたい | advanced/appendices | references/advanced/appendices/README.md |
| PTX 命令セット・state space・レジスタ・memory consistency model を調べたい | ptx-isa | references/ptx-isa/README.md |
| Blackwell アーキテクチャ・SM occupancy・NVLink・メモリシステムのチューニングを知りたい | blackwell-tuning | references/blackwell-tuning/README.md |
| CUTLASS/CuTe 全体のカテゴリ構成(CuTe DSL / Operator API / C++)を確認したい | cutlass | references/cutlass/README.md |
| CuTe DSL (Python) で GEMM・MMA・レイアウト・Task Scheduling (TS) を書きたい | cutlass/cute-dsl | references/cutlass/cute-dsl/README.md |
| CUTLASS Operator API(Python、コンパイル済みカーネル呼び出し・nvMatmulHeuristics による operator ランキング)を使いたい | cutlass/operator-api | references/cutlass/operator-api/README.md |
| CUTLASS C++ / CuTe C++ でテンプレートベースの GEMM カーネルを実装したい | cutlass/cpp | references/cutlass/cpp/README.md |
| 典型的な使い方を知りたい(vector add, tiled matmul, GEMM, CUDA Graphs 等) | samples | samples/README.md |
| インストール・nvcc ビルド・nsight プロファイリング・compute-sanitizer コマンドを知りたい | scripts | scripts/README.md |