openfaas/faas

Research: show GPU attached to a function

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#639 opened on Apr 12, 2018

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area/kubernetesenhancementhelp wantedpriority/middleskill/intermediate

Description

Description

Show a GPU attached to an OpenFaaS function in Kubernetes

Background

We have several users using Python for data-science where GPU acceleration is available. From the investigation I've done so far we should be able to make a few minor changes to faas-netes and then be able to mount a GPU into a function.

Tasks

  • List compatible GPUs
  • Write some code to mount a GPU
  • Produce a short list of steps to document how to test the patches/PR
  • Document any specific requirements / limitations

Other notes

GKE has GPUs available pre-configured under Kubernetes - I think this would be the easiest way to test - https://thenewstack.io/getting-started-with-gpus-in-google-kubernetes-engine/

Otherwise you'll need an Nvidia GPU and the process for configuring your kubelet is not trivial

Documentation page from Kubernetes:

https://kubernetes.io/docs/tasks/manage-gpus/scheduling-gpus/

Contributor guide

Tech stack
gokubernetes
Domain
infrastructure
Issue type
research
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
4
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
3-5 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
clear
Prerequisites
KubernetesOpenFaaSGPU schedulingGo
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
35
Research direction
Investigate the faas netes repository to understand how Kubernetes deployments for functions are handled. Review the Kubernetes GPU scheduling documentation linked in the issue. Explore how to add resource requests for NVIDIA GPUs to function deployments and test on GKE if available. Document findings and produce a minimal code change to mount a GPU.