NVIDIA WEBINAR
Accelerate Spark 3.0 with Google Cloud Dataproc and NVIDIA GPUs
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Date: July 16, 2020
Time: 10:00am – 11:00am PT
Duration: 1 hour
Time: 10:00am – 11:00am PT
Duration: 1 hour
Open source is a key pillar to enterprise data strategies as teams look to accelerate data science and data engineering workloads to power everything from autonomous vehicles, to fraud detection, to personalized advertising. Apache Spark has emerged as a standard data analytics processing engine for enterprises looking to advance machine learning, SQL, and streaming and batch data pipelines. With the new release of Spark 3.0, enterprises can now accelerate and scale Spark workloads with new capabilities around GPU integration, Kubernetes support, query performance, and more.
- Apache Spark use cases
- What’s new in Spark 3.0
- How Dataproc and NVIDIA GPUs support Spark workloads
- Live demo on Google Cloud
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DGX Station Whitepaper
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Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
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Speakers
Mikhail Chrestkha
Machine Learning Solutions Engineer, Google CloudMikhail Chrestkha is a machine learning solutions engineer with Google Cloud. He focuses on data science workflows and end-to-end machine learning platforms.
Dong Meng
Senior Solutions Architect, NVIDIADong Meng is a Senior Solutions Architect at NVIDIA. He works with cloud service provider customers to deploy cloud-based GPU accelerated solutions on machine learning, deep learning and data analytics.
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