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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)。

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(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(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

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

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