YoVDO

Is Sharing GPU to Multiple Containers Feasible?

Offered By: CNCF [Cloud Native Computing Foundation] via YouTube

Tags

Conference Talks Courses Machine Learning Courses Kubernetes Courses Prometheus Courses Parallel Computing Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore the feasibility of sharing GPUs across multiple containers in this 27-minute conference talk from the Cloud Native Computing Foundation (CNCF). Dive into cost-effective strategies for maximizing GPU utilization in ML workloads, particularly for inference tasks. Learn how to provision and attach GPUs using Kubernetes device plugins, and discover techniques for extending the NVIDIA device plugin to schedule multiple ML workloads on a single GPU. Gain insights into collecting GPU information with Prometheus and understand the native GPU sharing capabilities in Kubernetes without relying on additional technologies like VMware's vGPUs.

Syllabus

Is Sharing GPU to Multiple Containers Feasible? - Samed Güner, SAP


Taught by

CNCF [Cloud Native Computing Foundation]

Related Courses

Introduction to Cloud Infrastructure Technologies
Linux Foundation via edX
Scalable Microservices with Kubernetes
Google via Udacity
Google Cloud Fundamentals: Core Infrastructure
Google via Coursera
Introduction to Kubernetes
Linux Foundation via edX
Fundamentals of Containers, Kubernetes, and Red Hat OpenShift
Red Hat via edX