resource-config.md

Hardware Resource Configuration

Marin uses Fray for scheduling and resource management (dispatching to Iris on shared clusters, or to a local backend for laptop runs). The fray library provides unified resource configuration types that translate to concrete cluster resource requests.

ResourceConfig

The main entry point for resource configuration. Use the static factory methods to create configurations:

from fray.cluster import ResourceConfig

# TPU configuration
tpu_config = ResourceConfig.with_tpu("v4-8")
tpu_multislice = ResourceConfig.with_tpu("v4-8", slice_count=2)

# GPU configuration
gpu_config = ResourceConfig.with_gpu("H100", count=8)
gpu_auto = ResourceConfig.with_gpu()  # auto-detect GPU type

# CPU-only configuration
cpu_config = ResourceConfig.with_cpu()

::: fray.types.ResourceConfig

Device Configurations

These are the underlying device types wrapped by ResourceConfig:

CPU

::: fray.types.CpuConfig

GPU

::: fray.types.GpuConfig

TPU

::: fray.types.TpuConfig