Interactive Q&A with authors of CUDA Fortran for Scientists and Engineers

Agenda:

General Discussion:
6:15-7:10pm: What’s new and first-time attendee intros

Main Program:
7:15-8:00pm Interactive Q&A with authors of CUDA Fortran for Scientists and Engineers

About the Book:

CUDA Fortran for Scientists and Engineers, published in Sept. 2013, shows how high-performance application developers can leverage the power of GPUs using Fortran, the familiar language of scientific computing and supercomputer performance benchmarking. The authors presume no prior parallel computing experience, and cover the basics along with best practices for efficient GPU computing using CUDA Fortran.

In order to add CUDA Fortran to existing Fortran codes, they explain how to understand the target GPU architecture, identify computationally-intensive parts of the code, and modify the code to manage the data and parallelism and optimize performance - all in Fortran, without having to rewrite in another language. Each concept is illustrated with actual examples so you can immediately evaluate the performance of your code in comparison.

About the Authors:

Greg Ruetsch is a Senior Applied Engineer at NVIDIA, where he works on CUDA Fortran and performance optimization of HPC codes. He holds a Bachelor's degree in mechanical and aerospace engineering from Rutgers University and a Ph.D. in applied mathematics from Brown University. Prior to joining NVIDIA he held research positions at Stanford's Center for Turbulence Research and Sun Microsystems Laboratories.

Massimiliano Fatica is the manager of the Tesla HPC Group at NVIDIA where he works in the area of GPU computing (high-performance computing and clusters). He holds a laurea in Aeronautical Engineering and a Phd in Theoretical and Applied Mechanics from the University of Rome "La Sapienza”. Prior to joining NVIDIA, he was a research staff member at Stanford where he worked at the Center for Turbulence Research and Center for Integrated Turbulent Simulations on applications for the Stanford Streaming Supercomputer.