Quick Start Guide
=================

This guide will help you get started with Serverless GPU API quickly.

Basic Usage
-----------

Here's a simple example of how to use Serverless GPU API:

.. code-block:: python

    from serverless_gpu.launcher import distributed
    from serverless_gpu.compute import GPUType

    @distributed(gpus=8, gpu_type=GPUType.H100, remote=True)
    def my_function(**kwargs):
        # Your code here
        pass

    my_function.distributed(x=5)

For parameter sweeps, here's another example:

.. code-block:: python

    from serverless_gpu import distributed

    @distributed(
        gpus=2,
        gpu_type='a10',
        remote=True, # Uses remote gpus, not the gpus that are attached to your notebook
        run_async=True, # Enables multiple async workloads at once
    )
    def my_training_function(learning_rate: float):
      # TRAINING CODE HERE
    
    # Launch multiple async executions
    calls = []
    
    for lr in [1e-3, 1e-4, 1e-5]
        # Launches the training code in my_training_function with different learning rates!
        calls.append(my_training_function.distributed(lr))
    
    # Wait for completion
    wait(calls)

    # Your distributed computation code here
    # Serverless GPU API will handle the multi-GPU orchestration


Next Steps
----------

* Read the :doc:`overview` to understand Serverless GPU API's architecture
* Check out the :doc:`api/modules` for detailed API documentation
* Explore other examples in the repository