Distributed ML @ W&M
  • Distributed ML @ W&M
  • Logging in and Setting up your HPC Account
    • πŸŽ‰Requesting an Account
    • πŸ‘‹Login & Basic Setup
    • πŸ—ΊοΈPBSTOP - Your Cluster Roadmap
    • 🐍Uploading Files
  • The Batch System
    • πŸ‘©β€πŸŒΎWhat is a batch system?
    • πŸ‘·Jobs
    • Interactive Jobs
    • Non-Interactive Jobs
    • Checking the status of your jobs
    • Deleting Jobs
  • Using Python & Batch
    • 🐍Conda Environments
    • Python + Conda in a Job
    • Python & MPI
    • Python & Dask
  • Distributed sklearn
    • Example Dataset
    • Random Search - Simple
    • Random Search - MPI
    • Random Forest
    • Dask & sklearn
  • Distributed PyTorch - Dask
    • Basics of Torch
    • PyTorch + DASK
  • Kubernetes
    • Basics of Kubernetes
    • Your First K8S Deployment
    • Persistence & Python
    • Setting up Torch
    • One Pod Torch with Data
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  1. The Batch System

Jobs

A job is basically a resource check-out. When we launch a job, we tell the computer a couple basic things:

  1. Which sub-cluster you would like to run on

  2. How many nodes and processors you would like to check out

  3. How long you want your resources for (i.e. the maximum amount of time you expect your program to take to run) - this is called the walltime

  4. The name of your job

You can run either non-interactive or interactive jobs.

PreviousWhat is a batch system?NextInteractive Jobs

Last updated 2 years ago

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