Hardware Setup
Different jobs may require different amounts of resources to execute. Some jobs may have specific hardware requirements, such as GPU. This page describes how to specify hardware requirements for your job.
Please bear in mind that each executor is implemented independently and these docs might be slightly out of date. Double check the man page for the executor you are using with bacalhau [executor] --help.
Docker Executor
The following table describes how to specify hardware requirements for the Docker executor.
| Flag | Default | Description |
|---|---|---|
| 500m | Job CPU cores (e.g. 500m, 2, 8) |
| 1Gb | Job Memory requirement (e.g. 500Mb, 2Gb, 8Gb). |
| 0 | Job GPU requirement (e.g. 1). |
How it Works
When you specify hardware requirements, the job will be offered out to the network to see if there are any nodes that can satisfy the requirements. If there are, the job will be scheduled on the node and the executor will be started.
GPU Setup
Bacalhau supports GPU workloads. Learn how to run a job using GPU workloads with the Bacalhau client.
Prerequisites
The Bacalhau network must have an executor node with a GPU exposed
Your container must include the CUDA runtime (cudart) and must be compatible with the CUDA version running on the node
Usage
Use following command to see available resources amount:
To submit a request for a job that requires more than the standard set of resources, add the --cpu and --memory flags. For example, for a job that requires 2 CPU cores and 4Gb of RAM, use --cpu=2 --memory=4Gb, e.g.:
To submit a GPU job request, use the --gpu flag under the docker run command to select the number of GPUs your job requires. For example:
Limitations
The following limitations currently exist within Bacalhau.
Maximum CPU and memory limits depend on the participants in the network
For GPU:
NVIDIA, Intel or AMD GPUs only
Only the Docker Executor supports GPUs
