Engineering focus
Hardware selection and complete workload performance requirements.
Amazon EC2 GPU
GPU compute for training and inference workloads. Hardware selection and complete workload performance requirements.
Discuss a Amazon EC2 GPU programmePlatform engineering programme
Amazon EC2 GPU: GPU compute for training and inference workloads.
Engineering on this platform.
Commissioned scope
GPU cluster integration · Cloud model training platforms · GPU inference optimisation
Engineering focus
Commission Amazon EC2 GPU engineering for gPU compute for training and inference workloads. The contribution centres on hardware selection and complete workload performance requirements.
Programmes to commission
- GPU cluster integration: Connect model workloads to distributed GPU scheduling, storage and network resources.
- Cloud model training platforms: Connect training workflows to scalable compute, data and release management.
- GPU inference optimisation: Profile and tune inference workloads against defined serving objectives.
Operating context
Workload resources and service operation around the enterprise information boundary. The engagement identifies the selected components, interfaces and acceptance evidence. Relevant vendor terms and access arrangements follow the actual platform scope. A useful result connects platform behaviour to the enterprise task.
Platform context.
Bring the next
requirement.