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Get Started with CV Model Training
using PyTorch & Alluxio on Kubernetes
Lu Qiu, Shawn Sun
1
Machine Learning Engineer
Alluxio PMC
lu@alluxio.com
Software Engineer
shawn.sun@alluxio.com
Lu Qiu Shawn Sun
Agenda
● Introduction of Alluxio in AI/ML stack
● CV model training demo
● CV data loading demo
● Alluxio on Kubernetes demo
3
Alluxio in the AI Generation
4
Storage - Data/Model storage
Alluxio - High performance data access layer
ML Framework - Model training/inference
Unified Compute - ML pipeline orchestration
Architecture Overview
Online ML platform
Alluxio
Inference cluster
Models
Models
Training Data
Models
1
2
3
4
5
Offline training platform
Alluxio
Training cluster
Training Data
2
5
AI Training with Alluxio
6
POSIX API (FUSE)
RESTful API
S3 API
Alluxio
GPU (CV, NLP)
Dataset Storage
Kubernetes
Interactive
Notebook
Alluxio
Operator
Visualization
Dashboard
Alluxio
Dashboard
AI Training Demo (CV)
● Algorithm - ResNet
● Dataset - ImageNet (subset)
● Dataset loading
○ POSIX API (FUSE)
7
10
After using Alluxio
- Reduce Data Loader Rate from 82% to 1% (82X)
- Increase GPU Utilization Rate from 17% to 93% (5X)
10
CV Data Loading Demo (CV)
● CV data loading performance between
○ Alluxio POSIX API (FUSE)
○ S3FS-FUSE
○ Boto3
11
12
Alluxio is 5 times faster than S3FS-FUSE
And > 10 times faster than Boto3 S3 API
Alluxio on Kubernetes Live Demo
● Alluxio Kubernetes deployment
● Alluxio POSIX API utilization
● Alluxio Dashboard
15
16
Q & A

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AI Infra Day | Hands-on Lab: CV Model Training with PyTorch & Alluxio on Kubernetes

  • 1. Get Started with CV Model Training using PyTorch & Alluxio on Kubernetes Lu Qiu, Shawn Sun 1
  • 2. Machine Learning Engineer Alluxio PMC lu@alluxio.com Software Engineer shawn.sun@alluxio.com Lu Qiu Shawn Sun
  • 3. Agenda ● Introduction of Alluxio in AI/ML stack ● CV model training demo ● CV data loading demo ● Alluxio on Kubernetes demo 3
  • 4. Alluxio in the AI Generation 4 Storage - Data/Model storage Alluxio - High performance data access layer ML Framework - Model training/inference Unified Compute - ML pipeline orchestration
  • 5. Architecture Overview Online ML platform Alluxio Inference cluster Models Models Training Data Models 1 2 3 4 5 Offline training platform Alluxio Training cluster Training Data 2 5
  • 6. AI Training with Alluxio 6 POSIX API (FUSE) RESTful API S3 API Alluxio GPU (CV, NLP) Dataset Storage Kubernetes Interactive Notebook Alluxio Operator Visualization Dashboard Alluxio Dashboard
  • 7. AI Training Demo (CV) ● Algorithm - ResNet ● Dataset - ImageNet (subset) ● Dataset loading ○ POSIX API (FUSE) 7
  • 8.
  • 9.
  • 10. 10 After using Alluxio - Reduce Data Loader Rate from 82% to 1% (82X) - Increase GPU Utilization Rate from 17% to 93% (5X) 10
  • 11. CV Data Loading Demo (CV) ● CV data loading performance between ○ Alluxio POSIX API (FUSE) ○ S3FS-FUSE ○ Boto3 11
  • 12. 12
  • 13.
  • 14. Alluxio is 5 times faster than S3FS-FUSE And > 10 times faster than Boto3 S3 API
  • 15. Alluxio on Kubernetes Live Demo ● Alluxio Kubernetes deployment ● Alluxio POSIX API utilization ● Alluxio Dashboard 15