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16 -20 May
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Wednesday, May 18 • 15:25 - 16:00
How Cookpad Leverages Triton Inference Server To Boost Their Model Serving - Jose Navarro & Prayana Galih, Cookpad

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The adoption of MLOps practices and tooling by organizations has considerably reduced the pain points to productionise Machine Learning models. However, with the increase of the number of models available by a company to deploy, the diversity of frameworks used to train those models and the different infrastructure required to run each model, new challenges arise for Machine Learning Platform teams e.g: How can we deploy new models from the same or different frameworks concurrently? How can we improve throughput and optimize resource utilization in our serving infrastructure, especially GPUs? Cookpad ML Platform Engineers will talk in this session how Triton Inference Server, an open-source model serving tool from Nvidia, can simplify the process of model deployment and optimise the resource utilisation by efficiently supporting concurrent models on single GPU or CPU, and multi-GPU servers.

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Jose Navarro

ML Platform Lead Engineer, Cookpad
Jose Navarro is Machine Learning Platform Lead Engineer making everyday cooking fun at Cookpad. He is passionate about empowering Machine Learning teams with tools and practices that allow them to own their systems end to end. Jose has talked in MLOps conferences before about the... Read More →

Prayana Galih

Machine Learning Infrastructure Engineer, Cookpad
Pray is interested in general software engineering and architecture, with a current focus in machine learning tools and infrastructure. Outside of working hours he enjoys spending time with his family, a lot of coffee, and video games.

Wednesday May 18, 2022 15:25 - 16:00 CEST
Pavilion 4, Room B | Level 2 | Central Forum