feat: add little_kernel

[KnowingNothing]

LittleKernel

LittleKernel is a Python DSL for writing CUDA kernels with full PTX-level
control. It generates CUDA source code from Python functions and compiles
them at runtime using nvcc.

Overview

LittleKernel bridges the gap between high-level frameworks (PyTorch, Triton)
and hand-written CUDA/PTX. You write kernels as decorated Python functions
using explicit types and intrinsics, and LittleKernel:

1. Parses the Python AST,
2. Runs compiler passes (type inference, memory allocation, constant
   folding, inlining),
3. Generates CUDA C++ source with inline PTX assembly,
4. Compiles via nvcc and wraps the result in a callable that
   interoperates with PyTorch tensors.

Architecture

python/little_kernel/
├── language/        # DSL types, decorators, intrinsics
│   └── intrin/      # Per-feature intrinsic modules
│       ├── wgmma.py     # SM90 Tensor Core (WGMMA)
│       ├── tma.py       # Tensor Memory Accelerator
│       ├── barrier.py   # MBarrier & cluster sync
│       └── ...
├── core/            # IR, passes, type system
│   └── passes/      # Compiler pipeline
├── codegen/         # CUDA code generation
├── runtime/         # nvcc compilation, TMA descriptors, kernel launch
├── atom/            # High-level building blocks (MMA, TMA, barriers)
└── benchmark/       # GPU micro-benchmarks and GEMM kernels

Supported Architectures

• SM90 (Hopper) -- WGMMA, TMA, MBarrier, Cluster, async pipelines