nvidia-cuda
NVIDIA CUDA GPU 並列コンピューティングリファレンス。 CUDA C++ / CUDA Python, kernel, nvcc, Unified Memory, CUDA Graphs, Cooperative Groups, Driver API, マルチ GPU。 PTX ISA 命令セット, state space, MMA 命令。 Blackwell チューニング, Streaming Multiprocessor, NVLink。 CUTLASS / CuTe DSL / CuTe C++ GEMM, Tensor Core, tcgen05, Operator API, nsight-compute, compute-sanitizer。
How do I install this agent skill?
npx skills add https://github.com/fandhe-ai/agent-reference-skills --skill nvidia-cudaIs this agent skill safe to install?
- Gen Agent Trust Hubpass
This skill is a technical reference for NVIDIA CUDA and CUTLASS development. It provides documentation, architectural guidance, and code samples for GPU parallel computing. No security issues were detected.
- Socketpass
No alerts
- Snykpass
Risk: LOW · No issues
What does this agent skill do?
nvidia-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
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
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
api-reference.md
api-operator.md
api-arguments.md
api-discovery.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 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)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 |
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/fandhe-ai/agent-reference-skills/nvidia-cuda">View nvidia-cuda on skillZs</a>