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Kerangka Materi
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
Persyaratan
- 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 Jam
Testimoni (5)
OC is new to us and we learnt alot and the labs were excellent
sharkey dollie
Kursus - OpenShift 4 for Administrators
Very informative and to the point. Hands on pratice
Gil Matias - FINEOS
Kursus - Introduction to Docker
Labs and technical discussions.
Dinesh Panchal - AXA XL
Kursus - Advanced Docker
It gave a good grounding for Docker and Kubernetes.
Stephen Dowdeswell - Global Knowledge Networks UK
Kursus - Docker (introducing Kubernetes)
I mostly enjoyed the knowledge of the trainer.
