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Course Outline
Introduction to GPU-Accelerated Containerization
- Understanding GPU usage in deep learning workflows
- How Docker supports GPU-based workloads
- Key performance considerations
Installing and Configuring NVIDIA Container Toolkit
- Setting up drivers and CUDA compatibility
- Validating GPU access inside containers
- Configuring the runtime environment
Building GPU-Enabled Docker Images
- Using CUDA base images
- Packaging AI frameworks in GPU-ready containers
- Managing dependencies for training and inference
Running GPU-Accelerated AI Workloads
- Executing training jobs using GPUs
- Managing multi-GPU workloads
- Monitoring GPU utilization
Optimizing Performance and Resource Allocation
- Limiting and isolating GPU resources
- Optimizing memory, batch sizes, and device placement
- Performance tuning and diagnostics
Containerized Inference and Model Serving
- Building inference-ready containers
- Serving high-load workloads on GPUs
- Integrating model runners and APIs
Scaling GPU Workloads with Docker
- Strategies for distributed GPU training
- Scaling inference microservices
- Coordinating multi-container AI systems
Security and Reliability for GPU-Enabled Containers
- Ensuring safe GPU access in shared environments
- Hardening container images
- Managing updates, versions, and compatibility
Summary and Next Steps
Requirements
- An understanding of deep learning fundamentals
- Experience with Python and common AI frameworks
- Familiarity with basic containerization concepts
Audience
- Deep learning engineers
- Research and development teams
- AI model trainers
21 Hours
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from €6840 online delivery, based on a group of 2 delegates, €2160 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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Public Training
Please see our public courses
Testimonials (5)
OC is new to us and we learnt alot and the labs were excellent
sharkey dollie
Course - OpenShift 4 for Administrators
Very informative and to the point. Hands on pratice
Gil Matias - FINEOS
Course - Introduction to Docker
Labs and technical discussions.
Dinesh Panchal - AXA XL
Course - Advanced Docker
It gave a good grounding for Docker and Kubernetes.
Stephen Dowdeswell - Global Knowledge Networks UK
Course - Docker (introducing Kubernetes)
I mostly enjoyed the knowledge of the trainer.
