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[farmshare-discuss] Register Now for GPU Computing 101 Workshop, Jan 11 2013 @ Stanford University

Alex Chekholko chekh at stanford.edu
Mon Jan 7 12:52:12 PST 2013


What:
GPU COMPUTING 101

When:
January 11th, 2013
1pm to 5pm

Where:
Turing Auditorium,
Stanford Campus
255 Panama Street,
Stanford, CA

Please visit
http://www.nvidia.com/content
/event_registration/2012/gpu-computing/101/rsvp.asp
to RSVP




----- Forwarded Message -----
From: "Kimberly Powell" <kpowell at nvidia.com>

We are coming to campus on a quarterly basis for GPU computing training. 
These will be hands on classes using the on campus resources. This 
invitation is one of two occurring in January. The next invitation will 
be an Advanced course on January 18.

Please do forward this invitation to your groups and encourage them to 
register as space is limited.

Also please feel free to reach out to me with any additional questions.

Sincerely,

Kimberly






Subject: Register Now for GPU Computing 101 Workshop, Jan 11 2013 @ 
Stanford University


JOIN US FOR OUR HANDS ON WORKSHOP SERIES


EVENT DETAILS
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.

Stanford and NVIDIA are collaborating to host two, 4 hour, hands-on 
workshops to survey the broad range of GPU accelerated applications 
across all domains of scientific research and engineering.

GPU COMPUTING 101 - An Introduction with Hands on Exercises
Participants will learn how to program GPUs via the use of libraries, 
OpenACC compiler directives, and CUDA programming. The workshop will 
incorporate hands-on exercises so that the participants can become more 
familiar with GPU programming techniques.

This workshop is recommended for:
• Developers to get hands-on experience how to program
GPUs in any of their native languages like C, Fortran,
Python etc
• Domains scientists to realize the power of GPU
computing by taking advantage of the GPU enabled
applications
• HPC/IT staff to enable scientists and developers with
parallelizing compilers

Speaker Bio:
Jonathan Bentz , Solution Architect, NVIDIA. Jonathan focuses on Higher 
Education and Research customers supporting and enabling adoption of GPU 
computing. Prior to NVIDIA, Jonathan worked as a software engineer where 
he developed and optimized scientific libraries such as BLAS, LAPACK, 
and FFT. Jonathan has a PhD in physical chemistry and an MS in computer 
science from Iowa State University.

Sponsors

ICME	

When:
GPU COMPUTING 101
January 11th, 2013
1pm to 5pm

Where:
Turing Auditorium,
Stanford Campus
255 Panama Street,
Stanford, CA

Register

If the RSVP button doesn’t work, please visit
http://www.nvidia.com/content
/event_registration/2012/gpu-computing/101/rsvp.asp
to RSVP



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