Course Outline
Overview of GPU-Accelerated Containerization
- The role of GPUs in deep learning workflows
- How Docker facilitates GPU-based operations
- Essential performance factors to consider
Setup and Configuration of the NVIDIA Container Toolkit
- Installing drivers and ensuring CUDA compatibility
- Verifying GPU availability within containers
- Setting up the runtime environment
Creating GPU-Enabled Docker Images
- Leveraging CUDA base images
- Encapsulating AI frameworks in GPU-ready containers
- Handling dependencies for training and inference tasks
Executing GPU-Accelerated AI Tasks
- Running training jobs with GPU support
- Handling workloads across multiple GPUs
- Monitoring GPU usage and performance
Performance Optimization and Resource Management
- Restricting and isolating GPU resources effectively
- Tuning memory, batch sizes, and device assignment
- Performance analysis and diagnostic techniques
Containerized Inference and Model Serving
- Constructing containers optimized for inference
- Serving high-volume workloads on GPUs
- Integrating model execution engines and APIs
Scaling GPU Operations with Docker
- Approaches for distributed GPU training
- Scaling inference microservices
- Orchestrating multi-container AI architectures
Security and Reliability for GPU-Enabled Containers
- Securing GPU access in shared environments
- Hardening container images against vulnerabilities
- Overseeing updates, versioning, and compatibility
Conclusion and Future Steps
Requirements
- A solid grasp of deep learning fundamentals
- Proficiency in Python and widely used AI frameworks
- Knowledge of fundamental containerization principles
Intended Audience
- Deep learning engineers
- Research and development teams
- AI model specialists
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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
