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Duration 21 hours
Course Outline
Introduction to GPU-Accelerated Containerization
- Exploring the role of GPUs in deep learning workflows
- The mechanism by which Docker facilitates GPU-based workloads
- Essential performance factors to consider
Installing and Configuring the NVIDIA Container Toolkit
- Establishing driver and CUDA compatibility
- Verifying GPU accessibility within containers
- Setting up the runtime environment
Creating GPU-Enabled Docker Images
- Leveraging CUDA base images
- Packaging AI frameworks into GPU-ready containers
- Managing dependencies for both training and inference
Executing GPU-Accelerated AI Workloads
- Running training jobs utilizing GPU resources
- Handling multi-GPU workload management
- Tracking GPU utilization metrics
Optimizing Performance and Resource Management
- Restricting and isolating GPU resources effectively
- Enhancing memory usage, batch sizes, and device placement
- Tuning performance and diagnosing issues
Containerized Inference and Model Serving
- Developing inference-ready containers
- Managing high-load workloads on GPUs
- Integrating model runners and API interfaces
Scaling GPU Workloads with Docker
- Implementing strategies for distributed GPU training
- Scaling inference microservices
- Orchestrating multi-container AI systems
Security and Reliability for GPU-Enabled Containers
- Ensuring secure GPU access in shared environments
- Strengthening container image security
- Oversight of updates, versions, and compatibility
Summary and Next Steps
Requirements
- A solid grasp of deep learning principles
- Proficiency in Python and standard AI frameworks
- Basic knowledge of containerization concepts
Target Audience
- Deep learning engineers
- Research and development teams
- AI model trainers
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.
