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1
Introduction
2
Outline
3
Cloud Infrastructure
4
GPU jobs
5
GPU types
6
GPU deployment models
7
GPU deployment overview
8
GPU provisioning
9
Virtual GPUs
10
A100s
11
Puppet module
12
Use cases
13
Stability issues
14
Future plans
15
Conclusions
16
Questions
17
Recommendation
Description:
Learn about CERN's implementation of Multi Instance GPU (MIG) capabilities in a 28-minute conference talk that explores the deployment of NVIDIA A100 GPUs in their private cloud infrastructure. Discover various deployment models including PCI passthrough and virtual GPUs, understanding their advantages and challenges in supporting diverse applications from machine learning to proton beam simulations. Gain insights into how CERN manages centrally managed GPU resources to serve their user community, with detailed explanations of different deployment approaches and their final chosen model. Follow along as speaker Ulrich Schwickerath breaks down the technical aspects of GPU provisioning, stability considerations, and future development plans for CERN's cloud infrastructure.

Multi-Instance GPU Deployment for Machine Learning and Particle Beam Simulations at CERN

OpenInfra Foundation
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