### Run MetaXuda Demos

Source: https://github.com/perinban/metaxuda/blob/main/README.md

Execute example scripts from the demos directory to test MetaXuda's functionality. These can be run directly after installation.

```bash
python -m metaxuda.demos.add
python -m metaxuda.demos.pipeline
```

--------------------------------

### Install MetaXuda in Editable Mode

Source: https://github.com/perinban/metaxuda/blob/main/README.md

Clone the repository and install the package in editable mode using pip. This makes the shim libraries available within the Python package.

```bash
git clone https://github.com/perinban/MetaXuda.git
cd MetaXuda

pip install -e .
```

--------------------------------

### Numba CUDA Kernel Execution with MetaXuda

Source: https://github.com/perinban/metaxuda/blob/main/README.md

Demonstrates running a standard Numba CUDA kernel for element-wise addition. MetaXuda transparently dispatches this execution to Metal on Apple Silicon.

```python
from numba import cuda
import numpy as np

@cuda.jit
def add(a, b, out):
    i = cuda.grid(1)
    if i < out.size:
        out[i] = a[i] + b[i]

n = 1024
a = np.arange(n, dtype=np.float32)
b = np.arange(n, dtype=np.float32)
out = np.zeros_like(a)

add[32, 32](a, b, out)
print(out[:5])
```

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