Support reservation when provisioning VM/ accelerators on Google Batch

New feature

Google Cloud supports provisioning Compute Engine instances using reservations (e.g. dedicated compute resources CPUs/GPUs/Memory etc).
https://cloud.google.com/compute/docs/instances/reservations-consume

This is a configuration available via Google LifeSciences API and Google Batch.

• Google Batch: https://cloud.google.com/batch/docs/reference/rest/v1alpha/projects.locations.jobs#InstancePolicy

• Google Lifesciences API: https://cloud.google.com/life-sciences/docs/reference/rest/v2beta/projects.locations.pipelines/run#virtualmachine

Usage scenario

For example a user may configure a reservation for GPU resources to ensure dedicated resources are available to be provisioned (instead of waiting for GPUs to be available on demand).

Reservations can be made and applied automatically but it can be useful to be able to explicitly specify a reservation in case it's only used by a certain user or for a certain project.

Then the nextflow user would want to be able to configure a particular Nextflow process to use that dedicated reservation when provisioning a task that uses a GPU.

Suggest implementation

Allow for a Nextflow process to specify reservation configuration along with machineType/accelerators etc.

process foo {
    accelerator 4, type: 'nvidia-tesla-k80'
    reservation: 'userx-gpu-reservation'

    script:
    """
    your_gpu_enabled --command --line
    """
}

Start by tracing the existing Google Cloud configuration for process machineType and accelerators, then compare the Google Batch InstancePolicy and Life Sciences VirtualMachine reservation fields linked in the issue. Define how a process-level reservation value should be represented and passed to the selected provisioning API. Done means a configured reservation is honored for the relevant VM or accelerator task, with coverage for the supported Google Cloud path.