DGX Technical Sessions

As our valued NVIDIA DGX customer, we’re giving you direct access to our best practices and AI expertise through a series of live technical sessions. Get answers to your questions about DGX systems, with topics ranging from planning to deployment to ongoing optimization. The sessions are led by NVIDIA DGXperts — AI-fluent professionals who have deployed thousands of DGX systems like yours. These sessions are exclusive to DGX users, and registration links to upcoming sessions will be posted here.

Make sure you get communications on future sessions by signing up for an account on our enterprise support portal. Your NVIDIA enterprise account manager can easily add you to our portal or you can contact us dgx_info@nvidia.com

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Due to overwhelming interest in the new Multi-Instance GPU (MIG) feature of DGX A100, we had three sessions that explored it in more detail. DGX A100 with MIG enables your team to support more AI workloads, right-size resources for every job, and increase overall system utilization. Check out the replay here:

MIG Technical Series (Part 1 of 3): Overview of MIG on DGX
MIG Technical Series (Part 2 of 3): MIG Use and Configuration on DGX
MIG Technical Series (Part 3 of 3): MIG in a Cluster

Make sure you all sign up for our future monthly sessions! We’d love to see you there!

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Our next technical session is on Friday, Oct 8 at 10am PDT. Register here . Note: Registration is required and will only be approved for customers that have an active support contract.

Your Own GPT-3: How to Build and Deploy to Production
The last two years have seen unprecedented progress in Natural Language Processing with models such as BERT, RoBerta, Electra and now GPT-3 transforming countless NLP based applications.

The goal of this session is not only to provide an end-to-end demonstration of how to train custom large language models (from obtaining the training data, its cleaning/quality assessment to distributed training and evaluation) but also to show how to efficiently deploy them to production (including an overview of technologies to compress the models and do distributed/model parallel inference). This talk will discuss technologies such as Megatron LM, DGX SuperPOD, and for inference TensorRT, Faster Transformer and Triton Inference Server.

Speaker: Adam Henryk Grzywaczewski, Senior Deep Learning Data Scientist