4 On-Ramps to AI & GPU Computing: Find Your Path with NVIDIA & WWT

Details

Event Overview

Join us at WWT’s Training Center for our monthly lunch and learn series on Artificial Intelligence to help Hawaii organizations consider, navigate and harness AI. In May we are featuring NVIDIA, a leader in AI hardware and software, along with WWT’s “AI Proving Grounds” lab environment.

Featured Speakers

Zoe Ryan

NVIDIA

Solutions Architect

Zoe is a Solutions Architect at NVIDIA working with higher education institutions and researchers. She helps them utilize their GPUs by acceleratin...

Steve Niemi

NVIDIA

Sr. Account Manager

Steve is a Senior Account Manager on the Hi-Ed & Research team covering universities and non-profit research centers in the Western US.

John Evans

World Wide Technology

Chief Technology Advisor

John Evans is a WWT Chief Technology Advisor. He consults on strategy, innovation, and transformation. His focus is on creating custom solutions th...

What to expect

In this session, we will discuss four ways you can start using NVIDIA GPUs to accelerate your computing work, as well as the basics of how GPU computing works, and the types of speed ups you can see across a variety of workloads when you parallelize with a GPU. The four paths to GPU utilization are:

1. GPU accelerated applications. A great way to get started with GPUs by utilizing existing models, frameworks, and toolkits.
2. Drop-in library replacements. This method offers GPU acceleration for a wide variety of workloads, with minimal code changes or in depth GPU knowledge.
3. Portable programming models. This method helps take your custom CPU code and port it to a GPU implementation.
4. GPU accelerated programming languages like NVIDIA's CUDA platform.
We will finish with a tour of WWT's AI Proving Ground – a unique lab environment, powered by our Advanced Technology Center, that accelerates your ability to learn about, test, train and implement innovative AI solutions. It provides unrivaled access to the world's leading AI technologies.

Goals and Objectives

Educate on GPU Computing: The session aims to explain the basics of GPU computing and illustrate the types of performance improvements that can be expected when tasks are parallelized using GPUs. Explore GPU Utilization Methods: It intends to introduce and discuss four specific methods for utilizing GPUs, ranging from using GPU-accelerated applications and libraries to adopting portable programming models and directly programming with GPU-accelerated languages like CUDA. Enable Practical Application: The goal is to equip attendees with the knowledge and tools necessary to start or enhance their use of GPUs in computing tasks, regardless of their current level of expertise in GPU technology. This includes understanding various entry points for GPU utilization based on their technical knowledge and project needs. Harbor Court parking validation provided. Lunch provided. 11:00 AM Arrival and Lunch 11:30 AM Discussion Begins 1:00 PM Departure

Who should attend?

Chief Information Officers, Chief Technology Officers, Chief Marketing Officers, Chief Information Security Officers, Architects, Engineers, Business Data Managers, Analysts