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Thursday, November 21 • 5:20pm - 5:55pm
Supercharge Kubeflow Performance on GPU Clusters - Meenakshi Kaushik & Neelima Mukiri, Cisco

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AI/ML applications on Kubernetes can be optimized for performance at many levels.

This presentation provides an overview of the optimizations such as:
- Distributed training on multiple GPUs with optimal selection of interconnects between the GPUs and CPUs.
- Utilizing different types of GPUs/Servers for different workloads like training and inference.
- OS level optimizations to get optimal performance on the hardware.
- Usage of GPU Passthrough for optimal utilization and performance.

This presentation will also cover how the selection of machine learning framework, like Kubeflow, can impact performance and hardware utilization.
Speakers
MK

Meenakshi Kaushik

Product Manager, Cisco
Meenakshi is a product manager for Cisco Container Platrform, an enterprise grade kubernetes offering that supports GPU/Kubeflow for hybrid AI/ML workloads. Meenakshi has interest in AI/ML space and is excited how the technology can enhance human well being and productivity.
NM

Neelima Mukiri

Principal Engineer, Cisco
Neelima Mukiri is a Principal Engineer in Cisco's Cloud Platform Solutions group working on the architecture and development of Cisco's Container Platform. Prior to this she worked on core virtualization layer at VMware and systems software in Samsung Electronics.

Kubecon Kubeflow Distributed ML pdf
Thursday November 21, 2019 5:20pm - 5:55pm PST
Room 11AB - San Diego Convention Center Upper Level
  Machine Learning + Data