Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 21 hours
Course Outline
Introduction to GPU-Accelerated Containerization
- The role of GPUs in deep learning workflows
- How Docker facilitates GPU-based workloads
- Critical performance factors to consider
Installing and Configuring the NVIDIA Container Toolkit
- Establishing driver and CUDA compatibility
- Verifying GPU access within containers
- Setting up the runtime environment
Creating GPU-Enabled Docker Images
- Leveraging CUDA base images
- Packaging AI frameworks into GPU-ready containers
- Handling dependencies for training and inference
Executing GPU-Accelerated AI Workloads
- Running training jobs on GPUs
- Orchestrating multi-GPU workloads
- Tracking GPU utilization
Optimizing Performance and Resource Allocation
- Constraining and isolating GPU resources
- Refining memory usage, batch sizes, and device placement
- Conducting performance tuning and diagnostics
Containerized Inference and Model Serving
- Constructing containers optimized for inference
- Serving high-throughput workloads on GPUs
- Integrating model runners and APIs
Scaling GPU Workloads with Docker
- Approaches to 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 for security
- Managing updates, versioning, and compatibility
Summary and Next Steps
Requirements
- A solid grasp of deep learning fundamentals
- Practical experience with Python and prevalent AI frameworks
- Working knowledge of basic containerization principles
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.
