# TinyTorch Module Metadata
# Essential system information for CLI tools and build systems

name: "11_kernels"
title: "Kernels - Hardware-Aware Optimization"
description: "Custom operations, performance optimization, and hardware-aware computing for ML systems"

# Dependencies - Used by CLI for module ordering and prerequisites
dependencies:
  prerequisites: [
    "00_setup", "01_tensor", "02_activations", "03_layers", 
    "04_networks", "05_cnn", "06_dataloader", "07_autograd", 
    "08_optimizers", "09_training", "10_compression"
  ]
  enables: ["12_benchmarking", "13_mlops"]

# Package Export - What gets built into tinytorch package
exports_to: "tinytorch.core.kernels"

# File Structure - What files exist in this module
files:
  dev_file: "kernels_dev.py"
  readme: "README.md"
  tests: "inline"

# Educational Metadata
difficulty: "⭐⭐⭐⭐"
time_estimate: "8-10 hours"

# Components - What's implemented in this module
components:
  - "matmul_custom"
  - "relu_custom"
  - "conv2d_custom"
  - "matmul_vectorized"
  - "matmul_cache_optimized"
  - "matmul_parallel"
  - "quantized_matmul"
  - "sparse_matmul"
  - "pruned_conv2d"
  - "KernelProfiler"
  - "PerformanceBenchmark"
  - "HardwareProfiler"