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Course Outline
Foundations of GPU-Accelerated Containerization
- The role of GPUs in deep learning pipelines
- Docker’s support for GPU-based workloads
- Essential performance factors to consider
Installation and Setup of the NVIDIA Container Toolkit
- Installing drivers and ensuring CUDA compatibility
- Verifying GPU access within container environments
- Setting up the required runtime environment
Creating GPU-Ready Docker Images
- Utilizing CUDA-based images
- Packaging AI frameworks into GPU-capable containers
- Handling dependencies for training and inference phases
Executing GPU-Accelerated AI Tasks
- Running training jobs using GPU resources
- Handling workloads across multiple GPUs
- Tracking and monitoring GPU usage
Performance Optimization and Resource Management
- Restricting and isolating GPU resources effectively
- Tuning memory usage, batch sizes, and device placement
- Conducting performance tuning and diagnostics
Containerized Inference and Model Serving
- Developing containers optimized for inference
- Handling high-volume workloads on GPUs
- Integrating model runners and APIs
Scaling GPU Operations with Docker
- Approaches for distributed GPU training
- Scaling inference microservices
- Orchestrating multi-container AI systems
Security and Reliability in GPU-Enabled Containers
- Safeguarding GPU access in shared environments
- Strengthening container image security
- Overseeing updates, version control, and compatibility
Recap and Future Directions
Requirements
- Foundation in deep learning principles
- Practical experience with Python and popular AI frameworks
- Basic knowledge of containerization concepts
Target Audience
- Deep learning engineers
- Research and development teams
- AI model trainers
21 Hours
Testimonials (3)
How trainer deliver knowledge so effectively
Vu Thoai Le - Reply Polska sp. z o. o.
Course - Certified Kubernetes Administrator (CKA) - exam preparation
the trainer had a lot of knowledge and patience to share with us
Bogdan Olaru
Course - Introduction to Docker
The knowledge and exchanges with Augustin