Skip to content
cccskills
FreePublished on GitHub

apple-silicon

Apple Silicon GPU コンピュート/数値計算リファレンス。

MSL (address space, atomic, SIMD-group, TensorOps, cooperative_tensor, matmul2d), threadgroup sizing, argument buffer, indirect command buffer, unified memory, GPU counters, MTLTensor, MTL4MachineLearningCommandEncoder, MPS / MPSGraph / MPSMatrix / MPSNDArray / MPSNNGraph, MLX (mx.array, lazy evaluation, grad / vmap, mx.compile, mx.fft, export_function, mlx.nn, distributed)。

The English summary is being prepared. Showing the original description.

See how to install

Files included (90)

  • SKILL.md7.1 KB
  • references/metal-compute/argument-buffers.md3.8 KB
  • references/metal-compute/compute-pass-encoding.md3.8 KB
  • references/metal-compute/compute-pipeline-configuration.md3.5 KB
  • references/metal-compute/counter-sample-buffers.md3.9 KB
  • references/metal-compute/gpu-counters.md2.0 KB
  • references/metal-compute/indirect-command-buffers.md3.7 KB
  • references/metal-compute/indirect-compute-commands.md3.8 KB
  • references/metal-compute/machine-learning-passes.md5.9 KB
  • references/metal-compute/README.md2.0 KB
  • references/metal-compute/tensors.md5.9 KB
  • references/metal-compute/threadgroup-sizing.md3.8 KB
  • references/metal-compute/unified-memory.md4.2 KB
  • references/mlx/array.md2.7 KB
  • references/mlx/compilation.md2.6 KB
  • references/mlx/data-types.md2.7 KB
  • references/mlx/devices-streams.md2.8 KB
  • references/mlx/distributed.md3.6 KB
  • references/mlx/environment-variables.md5.3 KB
  • references/mlx/export.md3.7 KB
  • references/mlx/fast-custom-kernels.md3.6 KB
  • references/mlx/fft.md3.1 KB
  • references/mlx/function-transforms.md2.5 KB
  • references/mlx/indexing.md2.1 KB
  • references/mlx/kv-cache.md2.3 KB
  • references/mlx/lazy-evaluation.md2.3 KB
  • references/mlx/linalg.md1.7 KB
  • references/mlx/memory-management.md2.5 KB
  • references/mlx/metal-backend.md2.6 KB
  • references/mlx/nn-layers.md3.9 KB
  • references/mlx/nn-losses-activations.md2.1 KB
  • references/mlx/nn-module.md2.5 KB
  • references/mlx/operations.md5.7 KB
  • references/mlx/optimizers.md2.3 KB
  • references/mlx/precision.md1.7 KB
  • references/mlx/random.md2.1 KB
  • references/mlx/README.md3.8 KB
  • references/mlx/saving-loading.md2.2 KB
  • references/mlx/tree-utils.md1.8 KB
  • references/mlx/unified-memory-model.md2.2 KB
  • references/mps/cnn-kernels.md10.5 KB
  • references/mps/image-filters.md5.3 KB
  • references/mps/matrix-arithmetic.md3.0 KB
  • references/mps/matrix-decomposition-solve.md1.8 KB
  • references/mps/mpsgraph-executable.md2.2 KB
  • references/mps/mpsgraph-operations.md3.2 KB
  • references/mps/mpsgraph-tensor.md2.0 KB
  • references/mps/mpsgraph.md3.1 KB
  • references/mps/mpsimage.md1.8 KB
  • references/mps/mpskernel.md2.0 KB
  • references/mps/mpsmatrix.md1.9 KB
  • references/mps/mpsndarray.md1.9 KB
  • references/mps/mpsnngraph.md1.9 KB
  • references/mps/ray-tracing.md3.3 KB
  • references/mps/README.md2.1 KB
  • references/msl/address-spaces.md3.3 KB
  • references/msl/argument-attributes.md4.0 KB
  • references/msl/atomic-functions.md3.3 KB
  • references/msl/data-types.md4.6 KB
  • references/msl/function-qualifiers.md3.2 KB
  • references/msl/math-functions.md3.2 KB
  • references/msl/numerical-compliance.md3.9 KB
  • references/msl/README.md1.8 KB
  • references/msl/simdgroup-functions.md4.2 KB
  • references/msl/tensor-operations.md10.8 KB
  • references/msl/tensor-types.md9.0 KB
  • samples/blit-and-compute-single-pass.md4.3 KB
  • samples/compute-kernel-dispatch.md4.6 KB
  • samples/cpu-encoded-indirect-compute.md4.0 KB
  • samples/mlx-array-lazy-evaluation.md2.0 KB
  • samples/mlx-function-transforms.md2.6 KB
  • samples/mlx-mlp-training-loop.md3.0 KB
  • samples/mlx-unified-memory.md2.1 KB
  • samples/mps-image-filter.md2.1 KB
  • samples/mpsgraph-matrix-multiplication.md3.0 KB
  • samples/mpsgraph-training-loop.md4.0 KB
  • samples/nonuniform-threadgroup-dispatch.md2.6 KB
  • samples/README.md2.5 KB
  • samples/resource-group-argument-buffer.md2.8 KB
  • samples/shared-storage-mode-buffer.md2.8 KB
  • scripts/metal-binary-archives.md1.8 KB
  • scripts/metal-compile.md835 B
  • scripts/metal-debug-env.md1.7 KB
  • scripts/metal-dynamic-libraries.md1.2 KB
  • scripts/metal-performance-hud.md930 B
  • scripts/metal-symbols.md1.8 KB
  • scripts/mlx-distributed.md1.5 KB
  • scripts/mlx-install.md1.8 KB
  • scripts/README.md1.5 KB
  • scripts/toolchain-setup.md1.3 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

apple-silicon

Apple Silicon 上の GPU コンピュートと数値計算スタック。Metal Shading Language (MSL) の言語仕様、 compute dispatch のエンコーディングと unified memory 最適化、MPS/MPSGraph による行列演算・ニューラルネットワーク推論、 Apple 研究チーム発の配列フレームワーク MLX をカバーする。

ディレクトリ構成

skills/apple-silicon/
  SKILL.md
  references/
    metal-compute/
      README.md
      compute-pass-encoding.md
      threadgroup-sizing.md
      compute-pipeline-configuration.md
      indirect-command-buffers.md
      indirect-compute-commands.md
      gpu-counters.md
      counter-sample-buffers.md
      argument-buffers.md
      unified-memory.md
      tensors.md
      machine-learning-passes.md
    msl/
      README.md
      data-types.md
      address-spaces.md
      function-qualifiers.md
      argument-attributes.md
      atomic-functions.md
      simdgroup-functions.md
      math-functions.md
      numerical-compliance.md
      tensor-types.md
      tensor-operations.md
    mps/
      README.md
      mpskernel.md
      mpsimage.md
      image-filters.md
      mpsmatrix.md
      matrix-arithmetic.md
      matrix-decomposition-solve.md
      mpsndarray.md
      mpsnngraph.md
      cnn-kernels.md
      mpsgraph.md
      mpsgraph-tensor.md
      mpsgraph-executable.md
      mpsgraph-operations.md
      ray-tracing.md
    mlx/
      README.md
      array.md
      lazy-evaluation.md
      unified-memory-model.md
      function-transforms.md
      compilation.md
      nn-module.md
      optimizers.md
      nn-layers.md
      nn-losses-activations.md
      indexing.md
      saving-loading.md
      random.md
      linalg.md
      devices-streams.md
      memory-management.md
      fast-custom-kernels.md
      distributed.md
      tree-utils.md
      data-types.md
      operations.md
      fft.md
      export.md
      kv-cache.md
      precision.md
      environment-variables.md
      metal-backend.md
  samples/
    README.md
    compute-kernel-dispatch.md
    nonuniform-threadgroup-dispatch.md
    shared-storage-mode-buffer.md
    resource-group-argument-buffer.md
    cpu-encoded-indirect-compute.md
    blit-and-compute-single-pass.md
    mpsgraph-matrix-multiplication.md
    mpsgraph-training-loop.md
    mps-image-filter.md
    mlx-array-lazy-evaluation.md
    mlx-unified-memory.md
    mlx-mlp-training-loop.md
    mlx-function-transforms.md
  scripts/
    README.md
    toolchain-setup.md
    metal-compile.md
    metal-symbols.md
    metal-binary-archives.md
    metal-dynamic-libraries.md
    metal-debug-env.md
    metal-performance-hud.md
    mlx-install.md
    mlx-distributed.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:

  1. 下記マッピング表でタスクに対応するカテゴリを探す
  2. そのカテゴリの references/{category}/README.md(samples/ scripts/ は直下の README.md)を参照して目的のページを特定する
  3. 該当ページの .md を Read して詳細を確認する

Metal のレンダリングパイプライン(MTLRenderCommandEncoder / MTLRenderPipelineState)・Core Animation・ Core Graphics・Core Image・SpriteKit・SceneKit は apple-graphics を参照。本スキルは Metal のコンピュート (MTLComputeCommandEncoder 以下)・MSL 言語仕様・MPS/MPSGraph・MLX を担当する。 Core ML / Create ML による .mlmodel のオンデバイス推論・Vision・Natural Language・Speech、および Core AI (iOS 27, NDArray / ComputeUnitKind) は apple-ml を参照。 Compute Graph (RealityKit) は apple-spatial、MetalFX denoising は apple-graphics を参照。 MLX のみ出典が developer.apple.com ではなく、Apple 研究チームが公開する OSS ドキュメント (ml-explore.github.io)である点に注意する。

タスク → カテゴリ マッピング

タスクカテゴリ参照 README
compute pass のエンコーディング・threadgroup/grid サイズ計算・compute pipeline 設定を知りたいmetal-computereferences/metal-compute/README.md
argument buffer・indirect command buffer・GPU counter・unified memory (storage mode) を調べたいmetal-computereferences/metal-compute/README.md
MSL のデータ型・address space・kernel 関数属性・引数バインディング属性を調べたいmslreferences/msl/README.md
MSL の atomic 関数・SIMD-group/quad-group 関数・数学関数・数値精度 (IEEE 754) 準拠を調べたいmslreferences/msl/README.md
MPSKernel/MPSImage/MPSMatrix/MPSNDArray による画像フィルタ・行列演算・分解を調べたいmpsreferences/mps/README.md
MPSGraph/MPSNNGraph によるグラフ構築・実行・CNN 推論・ray tracing を調べたいmpsreferences/mps/README.md
Metal 4 の MTLTensor 作成・ML pass (MTL4MachineLearningCommandEncoder) のエンコードを調べたいmetal-computereferences/metal-compute/README.md
MSL の tensor / cooperative_tensor / TensorOps (matmul2d, convolution, execution scope) を調べたいmslreferences/msl/README.md
MLX の array/dtype・lazy evaluation・indexing・保存/読み込みを調べたいmlxreferences/mlx/README.md
MLX の dtype 一覧・演算一覧・FFT (stft)・関数 export (.mlxfn) を調べたいmlxreferences/mlx/README.md
MLX の環境変数・数値精度 (TF32, Winograd)・KV cache・Metal capture を調べたいmlxreferences/mlx/README.md
MLX の grad/vmap 等の関数変換・mx.compile・unified memory model・distributed を調べたいmlxreferences/mlx/README.md
mlx.nn のレイヤー/損失関数・mlx.optimizers・tree utils を調べたいmlxreferences/mlx/README.md
典型的な使い方を知りたい(compute kernel dispatch, argument buffer, MPSGraph 学習ループ, MLX 学習ループ等)samplessamples/README.md
Metal Toolchain セットアップ・.metal のコンパイル/リンク・デバッグ環境変数・MLX インストールを知りたいscriptsscripts/README.md

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

AMD ROCm / HIP GPU コンピューティングリファレンス。 hipMalloc, hipLaunchKernelGGL, HIP Graph, hipGreenCtx, HIPRTC, hipify, rocBLAS, MIOpen, RCCL, hipThreads, libhipcxx, rocprofv3, amd-smi, rocminfo, TheRock / Core SDK 10, CDNA1-4 / RDNA1-4, MI300 / MI350 / MI350P, gfx942, Matrix Core, wave32/64。

The English summary is being prepared. Showing the original description.

Fandhe-AI/agent-reference-skills4Updated Oct 20, 2026

Android アプリ開発 (Kotlin) の推奨アーキテクチャリファレンス。 Jetpack, androidx, UI layer, Domain layer, Data layer, state holder, UDF, SSOT, オフラインファースト, モジュール化, ViewModel, viewModelScope, SavedStateHandle, Lifecycle, repeatOnLifecycle, collectAsStateWithLifecycle, LiveData, Hilt による DI, Paging 3 によるページング処理。

The English summary is being prepared. Showing the original description.

Fandhe-AI/agent-reference-skills4Updated Oct 20, 2026

Android アプリ開発 (Kotlin) のバックグラウンド・非同期処理リファレンス。 Jetpack androidx WorkManager: Worker, CoroutineWorker, WorkRequest, Constraints, WorkInfo, WorkContinuation, expedited work, テスト。 Service: フォアグラウンドサービス, バウンドサービス, AIDL, Messenger。 AlarmManager, PendingIntent, BroadcastReceiver, JobScheduler, Doze。 Kotlin コルーチン, Flow, StateFlow, SharedFlow, Channel。

The English summary is being prepared. Showing the original description.

Fandhe-AI/agent-reference-skills4Updated Oct 20, 2026

Android アプリ開発 (Kotlin) の Gradle ビルドシステムリファレンス。 Android Gradle Plugin (AGP), Kotlin DSL (build.gradle.kts), version catalog, KSP, R8/ProGuard, App Bundle, baseline profile。

The English summary is being prepared. Showing the original description.

Fandhe-AI/agent-reference-skills4Updated Oct 20, 2026

Android Jetpack Compose (Kotlin) の androidx Material3 コンポーネントリファレンス。 Button, IconButton, FloatingActionButton, Checkbox, Switch, Slider, TextField, SearchBar, DropdownMenu, Chip, DatePicker, TimePicker, Card, Scaffold, Dialog, BottomSheet, TopAppBar, NavigationBar, NavigationRail, Tab, Snackbar, ProgressIndicator, Badge, Icon, MaterialTheme, ColorScheme, Typography, Shapes。

The English summary is being prepared. Showing the original description.

Fandhe-AI/agent-reference-skills4Updated Oct 20, 2026

Android Jetpack Compose (Kotlin) のアニメーション・描画リファレンス。 androidx.compose.animation / graphics API。 AnimatedVisibility, AnimatedContent, animate*AsState, Animatable, AnimationSpec, Canvas, DrawScope, Brush, Path, Color, Image。

The English summary is being prepared. Showing the original description.

Fandhe-AI/agent-reference-skills4Updated Oct 20, 2026

See all skills by Fandhe-AI

Report a problem with this skill