Special topic: GPU-Accelerated Business Intelligence Analytics ( by Ren Wu , Ph.D.) Exchange ideas, meet experts, share code, lectures ... all HPC & GPU, all practical, all cutting-edge.

Agenda:

General Discussions:

6:15-6:30pm    What’s new in HPC & GPU Supercomputing

6:30-6:50pm    Member self-intros: 30 seconds for each member

Main Program:

6:50-7:50pm    GPU-Accelerated Business Intelligence Analytics (Ren Wu, Ph.D.)

7:50-8:00pm  Discussions

8:00-8:15pm  Short Topic: The Impact of Bitcoin Mining and Hash Cracking on HPC & GPU Supercomputing (Glen Evan)

8:15-8:20pm  Discussions

Book Review: GPU Computing Gems

8:20-8:25pm Chapter 17: Monte Carlo Photon Transport on the GPU (Mark Cheung)

8:25-8:30pm  Chapter 18: High-Performance Iterated Function Systems (Michael Everest)

Refreshments sponsored by Life Technologies, Inc.

GPU-Accelerated Business Intelligence Analytics
GPUs have been used in many different domains with great success. In this talk I will share some of the work we did at HP Labs on using GPUs as accelerator for deep analytics, a relatively less explored area but full of potential. Our results show that GPUs can bring tremendous performance advantage over CPU only approaches.

Biography:
Dr. Ren Wu is a Research Scientist at HP Labs, Palo Alto. His research interests include data-intensive high-performance computing, massively parallel algorithms and computational intelligence. In recent years he has been focusing on GPU acceleration of large-scale analytics, and is well known for his work on GPU-accelerated clustering algorithms. He is also the PI of the CUDA Research Center at HP Labs.

Location:

Room 109/110; 
Carnegie Mellon Silicon Valley; 
NASA Research Park Bldg 23; 
Mountain View, CA 94043; 

Directions to Carnegie Mellon Silicon Valley; 

Google Map showing parking, check point, and building entrance; 

NOTE: You will need a government issued ID (e.g. Driver's License) to enter NASA Research Park