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Distributed Training & Marlowe Multi-GPU Best Practices | Stanford HAI
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eventWorkshop

Distributed Training & Marlowe Multi-GPU Best Practices

Status
Past
Date
Wednesday, May 21, 2025 2:00 PM - 3:30 PM PST/PDT
Location
Computing and Data Science (CoDa), 389 Jane Stanford Way, Rm E401, 4th Floor, Stanford, CA 94305
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Event Contact
datascience@stanford.edu

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Distributed Training & Marlowe Multi-GPU Best Practices

Abstract: This training focuses on efficient strategies for using multiple GPUs and nodes. We will overview how to deploy strategies of data parallelism and model parallelism to scale to multiple GPUs, enabling faster training times and better model performance.

Speaker: Aastha Jhunjhunwala is a Solution Architect in the NVIDIA AI Enterprise team working with customers across different industries. She helps customers build optimized generative applications by leveraging NVIDIA hardware and software stack.

About the NVIDIA GPU Computing Workshop Series 

We are excited to announce a series of NVIDIA-led workshops designed to enhance your expertise in GPU computing. Whether you're a beginner or looking to deepen your skills, these sessions offer valuable insights and hands-on learning opportunities. Workshops are expected to be held on a monthly basis.  

NOTE: This event is open to Stanford and NVIDIA affiliates only.