At GTC, NVIDIA DLI offers an array of self-paced courses and instructor-led workshops for developers, data scientists, and researchers looking to solve the…
Overview
The article provides an overview of NVIDIA's GPU Technology Conference (GTC) 2019, highlighting various CUDA training sessions and research posters that focus on accelerated computing. It emphasizes the importance of the CUDA SDK in maximizing GPU processing potential and offers insights into hands-on training opportunities for developers and researchers.
What You'll Learn
1
How to accelerate applications using CUDA C/C++ and CUDA Python
2
Why CUDA is essential for maximizing GPU processing potential
3
When to use RAPIDS for accelerating data science workflows
Key Questions Answered
What training opportunities are available at GTC 2019 for CUDA?
At GTC 2019, NVIDIA offers hands-on training sessions on accelerating applications using CUDA C/C++ and CUDA Python, as well as workshops on executing CUDA code on DRIVE AGX and utilizing RAPIDS for data science workflows. These sessions are designed for developers, data scientists, and researchers.
What types of research posters can be found at GTC 2019?
GTC 2019 features over 150 research posters covering topics such as HPC, AI, computational physics, and quantitative risk management. Attendees can engage with the authors to explore how these ideas leverage GPU acceleration.
Technologies & Tools
Software
Cuda
Used for accelerating applications and enabling developers to maximize GPU processing potential.
Software
Rapids
Utilized for accelerating data science workflows.
Hardware
Drive Agx
Platform for executing CUDA code.
Key Actionable Insights
1Participate in hands-on CUDA training sessions to enhance your skills in GPU programming.These sessions are tailored for developers and researchers looking to tackle complex problems using accelerated computing, making them a valuable opportunity for professional development.
2Engage with research poster authors to gain insights into cutting-edge applications of CUDA.This interaction can provide unique perspectives on how various industries are utilizing GPU technology to solve real-world challenges.
Related Concepts
Cuda Programming
GPU Acceleration
Data Science Workflows
High-performance Computing (hpc)