GPU Performance Analysis -- Part 8 of 9 CUDA Training Series, August 18, 2020

Introduction

CUDA^® is a parallel computing platform and programming model that extends C++ to allow developers to program GPUs with a familiar programming language and simple APIs.

NVIDIA will present a 9-part CUDA training series intended to help new and existing GPU programmers understand the main concepts of the CUDA platform and its programming model. Each part will include a 1-hour presentation and example exercises. The exercises are meant to reinforce the material from the presentation and can be completed during a 1-hour hands-on session following each lecture (for in-person participants) or on your own (for remote participants).  OLCF and NERSC will both be holding in-person events for each part of the series. Please see the topics of each part and dates here.

Part 8 of 9:  GPU Performance Analysis

Date and Time: 10 am - 12 pm (Pacific time), Tuesday, August 18, 2020

The format of this event will be online only. Performance optimization on GPUs should be done in an analysis-driven manner, where insights from performance measurements guide changes made to your code. This module introduces the analysis-driven optimization workflow and demonstrates how to use the NVIDIA developer tools Nsight Systems and Nsight Compute to profile your code and determine what optimizations to make.

After the presentation, there will be a hands-on session where participants can complete example exercises meant to reinforce the presented concepts and get help from the experts.

Registration

Please register here.  This event is online only.

Presentation Materials 

• Slides
• Recording: TBA (to be posted shortly after the event)
• Exercises: The example exercises for this module can be found in the "exercises/hw8" folder of this GitHub repo. 
• Survey: Please help us to provide feedback by completing a 3-min short survey (access via the "Survey" tab located in the middle of this page)