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Engineering GPU performance: Design choices for training & inference
This session took place on November 6, 2025
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Engineering GPU performance: Design choices for training & inference
This episode is available to stream on-demand.
This episode discusses the technical nuances of GPU performance and system design for AI and HPC. Expert speakers will compare hosted cloud and on-prem strategies for both training and large-scale inference, examining elasticity, queue times, latency, and cost predictability, while exploring how software-stack maturity and orchestration shape throughput and iteration speed. Join this episode to uncover:
- What factors are driving hybrid inference strategies?
- Measuring and monitoring GPU performance
- Thermal and serviceability trade-offs for outcome-driven GPU systems
- GPU optimization: monitoring, placement, and ROI
- Speakers
- Charlotte Trueman , DatacenterDynamics
- Ted Marena , AMD
- Tharun Kumar Kuppireddy , Supermicro
- Brought to You by
- Supermicro