Domino at NVIDIA GTC Replay

Democratize GPU Access with Enterprise MLOps
Originally Aired November 8-11, 2021

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Catch our sessions from November, 2021 GTC On-Demand here!

Domino Data Lab recently announced an expanded partnership with NVIDIA, one of our newest investors. Why?

So we can help customers build competitive advantage with NVIDIA-accelerated computing solutions. What does this mean for customers? 

Full-stack, joint solutions to run GPU-accelerated data science on a broad and widely accessible range of NVIDIA GPUs. 

At GTC, we announced our expanded collaboration with NVIDIA and TCS to bring Enterprise MLOps to even more customers. 

See Domino's on-demand sessions from, November 8-11, 2021, at NVIDIA GTC, the conference for AI innovators, technologists, and creators to learn about how Domino and NVIDIA can democratize GPU access for unfettered data science innovation!

GTC Speakers

Stig Pedersen
Head of Machine Learning, Topdanmark
John Ashley
General Manager, Financial Services & Technology, NVIDIA
Dr. Revati Kulkarni
Dr. Revati Kulkarni
Technology Head, High Performance Computing, AI Group at Tata Consultancy Services (TCS)
Nick Elprin
Founder & CEO, Domino
Thomas Robinson
VP, Strategic Partnerships, Domino
Nikolay Manchev
Head of Data Science, EMEA, Domino
Josh Poduska
Chief Data Scientist, Domino

See our On-Demand GTC Sessions!


Scaling MLOps in the Enterprise: How Leading Insurer Topdanmark’s Machine Learning Center of Excellence infuses a model-driven competitive advantage [A31741]
TopDanmark’s Head of Machine Learning, Stig Pederson, and Domino CEO, Nick Elprin, discuss how Topdanmark, one of Denmark’s largest insurers, is infusing models throughout operations for fraud detection, policy approvals, and risk management - improving customer experience for a competitive advantage using leading-edge technology like Natural Language Processing (NLP). They’ll discuss what it takes to become model-driven by removing process and technology bottlenecks for unobstructed data science innovation.
Breaking Down Silos Across Simulation, Analytics, and AI to Scale Innovation [A31665]
The convergence of analytics and AI workloads with simulation or classical High Performance Computing (HPC) workloads in the cloud are becoming requirements for the model-driven businesses of the future. For many companies today, these siloed environments limit performance at the production scale necessary for truly transformative data science innovation. In this session, Dr. Revati Kulkarni, Technology Head of the HPC and AI group at TCS, along with Thomas Robinson, VP of Strategic Partnerships at Domino, discuss role-based use cases they’ve seen in enterprise customers. Learn best practices for building a heterogeneous platform to unite analytics and AI workloads, backed by the HPC technology for production level workflows.
Beyond Spark: Dask and Ray as Multi-node Accelerated Compute Frameworks - [A31670]
Apache Spark has been the incumbent distributed compute framework for the past 10+ years. But the overhead and complexity of Spark have been eclipsed by new frameworks like Dask and Ray. In this talk we will discuss trade offs of these frameworks, explore choosing the appropriate framework and demonstrate the ease of using Dask or Ray. Additionally, we'll present an integrated solution based on the Domino Data Science Platform, and NVIDIA NGC containers, which enables data scientists to easily provision a Spark/Ray/Dask cluster with an arbitrary number of GPU-accelerated workers, and access it through their favorite integrated development environment.
NVIDIA & Domino Partner Panel
[Featuring Domino] Mastering Data Science Workloads with MLOps tools: A Panel with NVIDIA DGX-Ready Software Partners [A31321]
Domino's own Chief Data Scientist, Josh Poduska, joins a panel of NVIDIA DGX-certified partners to discuss best practices, trends, and recommendations for managing data science teams, data, and optimizing and accelerating data science workloads and running heavy training workloads.

See our sessions at NVIDIA GTC!

Brilliant Minds. Breakthrough Discoveries. November 8-11, 2021