Monday at GTC: Learn Something New

by Julia Levites

Our GPU Technology Conference is coming up in less than a week – and this year’s get-together is packed with more than 500 talks in just four days. That means it’s time to start planning.

The first piece of your plan should be to decide what you want to learn. Monday, March 24, the first day of GTC, offers a variety of 80 minute tutorials for any level of GPU expertise, as well as a full day of talks on big data analytics and programming languages.

Don’t forget. Register for our GPU Technology Conference today. 

Don't miss the wide range of talks at GTC.
Don’t miss the wide range of talks at GTC.

Talks will start early in the morning and continue throughout the day. All speakers presenting their research on Monday are recipients of funding from the U.S. Defense Advanced Research Projects Agency’s (DARPA) Small Business Technology Transfer program, a program designed to help small businesses and academia advance in their research.

Chris White, the project manager of DAPRA’s XDATA program, will open the day with an introduction of XDATA program and challenges the Department of Defense faces with processing increasing amounts of data.

The talks that follow will cover graph analytics, speech recognition, program languages and more:

  • Zhisong Fu, CUDA researcher from SYSTAP, will introduce a library for efficient graph analytics that can be used for a large spectrum of applications.
  • Stanford Ph.D. candidate  HyoukJoong Lee will go over details on how to build a new high level GPU language for easier GPU programming.
  • Techniques on how leverage multiple GPUs for graph analytics and achieve acceleration will be presented by Vishal Vaidyanathan, a partner at Royal Caliber.
  • Performance of automatic transcription of TED talks or deep network back propagation in a large-vocabulary speech recognition task will be compared on GPU and CPU systems by Jessica Raycomputer scientist from MIT Lincoln Lab.
  • Siu Kwan Lam, a software engineer from Continuum Analytics will share his research on how to make Python run faster on GPUs.
  • Yangzihao Wang, a Ph.D. student from UC Davis will present an open source library for development of high-performance GPU graph primitives.

Get more details on our GTC website, and don’t forget to add Monday talks to your calendar:

Don’t forget. Register for our GPU Technology Conference today.