Course Outline
Introduction to GPU-Accelerated Containerization
- Comprehending GPU utilization in deep learning workflows
- Understanding how Docker facilitates GPU-based workloads
- Essential performance considerations
Installation and Configuration of the NVIDIA Container Toolkit
- Configuring drivers and ensuring CUDA compatibility
- Verifying GPU access within containers
- Setting up the runtime environment
Creating GPU-Enabled Docker Images
- Utilizing CUDA base images
- Packaging AI frameworks into GPU-ready containers
- Handling dependencies for training and inference
Executing GPU-Accelerated AI Workloads
- Running training jobs leveraging GPUs
- Overseeing multi-GPU workloads
- Tracking GPU utilization metrics
Performance and Resource Allocation Optimization
- Controlling and isolating GPU resources
- Optimizing memory usage, batch sizes, and device placement
- Performance tuning and diagnostic techniques
Containerized Inference and Model Serving
- Creating inference-ready containers
- Handling high-load workloads on GPUs
- Integrating model runners and APIs
Scaling GPU Workloads with Docker
- Approaches for distributed GPU training
- Scaling inference microservices
- Coordinating multi-container AI systems
Security and Reliability for GPU-Enabled Containers
- Safeguarding GPU access in shared environments
- Hardening container images
- Managing updates, versions, and compatibility
Summary and Next Steps
Requirements
- Knowledge of deep learning fundamentals
- Proficiency with Python and common AI frameworks
- Familiarity with basic containerization concepts
Target Audience
- Deep learning engineers
- Research and development teams
- AI model trainers
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 4800 € + VAT*
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Testimonials (2)
As i said before , for a person like me (no exp. ) this was a gateway to understanding features and functions with these programs/tools & etc. .
Patrick V. Duylovski - UBB + DZI (KBC GROUP)
Course - Docker and Kubernetes
multi-tiered, structured course programme.
