Nvidia GPU Workshop
|Nvidia GPU Workshop||June 1 - 2 2016||800 AM - 500 PM||BEC ROOM 1615|
NVIDIA and LSU Research Computing and HPC are pleased to be organizing a 2-day High Performance Computing and Programming event on June 1-2, 2016 in Business Education Complex, Room 1615 at LSU, Baton Rouge, LA.
Why you should attend
NVIDIA GPUs are the world’s fastest and most efficient accelerators delivering world record scientific application performance. NVIDIA’s CUDA Technology is the most pervasive parallel computing model, used by over 250 scientific applications and over 150,000 developers worldwide. This Programming Workshop will focus on introducing scientific computing programming utilizing NVIDIA GPUs to accelerate applications across a diverse set of domains.
Presented by NVIDIA instructor Dr. Jonathan Bentz, the workshop will introduce programming techniques using CUDA and OpenACC paradigms as well as optimization, profiling and debugging methods for GPU programming. An introduction to Deep Learning using GPUs will also be covered.
Who it's for
Undergraduate/Graduate Students, Postdocs, Researchers, and Professors
- June 1st | Day 1
|9:00 AM - 4:30 PM||Introduction to GPU programming
- June 2nd | Day 2
|9:00 AM - 4:30 PM||
Performance and Optimization
- Coffee and Lunch will be provided.
About the Instructor
Dr. Jonathan Bentz is a Solution Architect with NVIDIA, focusing on Higher Education and Reasearch customers. In this role he works as a technical resource to customers and OEMs to support and enable adoption of GPU computing. He delivers GPU training such as workshops to train users and help raise awareness of GPU computing. He also works with ISV and customer applications to assist in optimization for GPUs through the use of benchmarking and targeted code development efforts. Prior to NVIDIA, Jonathan worked for Cray as a software engineer where he developed and optimizaed high performance scientific libraries such as BLAS, LAPACK, and FFT specifically for the Cray platform. Jonathan obtained his PhD in physical chemistry and his MS in computer science from Iowa State University.
Please bring your laptop to participate in hands-on exercises. A GPU in your laptop is not required. No previous GPU programming experience is required. However, beginner-level C and Linux experience will be expected.
In preparation, you may watch a few short (approx. 5 min) YouTube videos on introductory GPU programming topics. These CUDACasts can be found at this link. Also, please take time to register at CUDA developer site: link here.
Please register through this link.