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Course Outline
Introduction to GPU-Boosted Containerization
- Exploring the role of GPUs in deep learning pipelines
- The way Docker facilitates GPU-based operations
- Essential performance factors to consider
Installation and Setup of the NVIDIA Container Toolkit
- Establishing drivers and ensuring CUDA compatibility
- Verifying GPU accessibility within containers
- Setting up the runtime environment
Creating GPU-Ready Docker Images
- Leveraging CUDA base images
- Encapsulating AI frameworks in GPU-capable containers
- Handling dependencies for training and inference tasks
Executing GPU-Accelerated AI Workloads
- Running training jobs utilizing GPU resources
- Overseeing multi-GPU operations
- Tracking GPU utilization metrics
Enhancing Performance and Resource Management
- Restricting and separating GPU resources
- Improving memory usage, batch sizes, and device placement
- Conducting performance tuning and diagnostics
Containerized Inference and Model Delivery
- Assembling inference-optimized containers
- Handling high-demand workloads on GPUs
- Incorporating model runners and APIs
Scaling GPU Workloads via Docker
- Approaches for distributed GPU training
- Expanding inference microservices
- Synchronizing multi-container AI architectures
Security and Dependability for GPU-Powered Containers
- Guaranteeing secure GPU access in shared environments
- Strengthening the security of container images
- Oversight of updates, versions, and compatibility
Conclusion and Future Directions
Requirements
- A solid grasp of deep learning core concepts
- Proficiency with Python and standard AI frameworks
- Basic knowledge of containerization principles
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