CUDA finance course Dec 2-5, 2014, New York

October 22nd, 2014

Developed in partnership with NVIDIA, this hands-on four day course will teach you how to write and optimize applications that fully leverage the multi-core processing capabilities of the GPU. This course will have a finance focus. Commonly used algorithms such as random number generation and Monte Carlo simulations will be used and profiled in examples. A background in finance is not necessary. For more information please visit: http://acceleware.com/training/988

CUDA Course Sept 23 – 26, 2014, Frankfurt

August 20th, 2014

This hands-on four day course teaches how to write and optimize applications that fully leverage the multi-core processing capabilities of the GPU. More details and registration: http://acceleware.com/training/986

Acceleware OpenCL Training June 2-5, 2014

March 5th, 2014

This hands-on four day course will teach you how to write applications in OpenCL that fully leverage the multi-core processing capabilities of the GPU. Taught by Acceleware developers who bring real world experience to the class room, students will benefit from:

  • Hands-on exercises and progressive lectures
  • Individual laptops with AMD Fusion APU for student use
  • Small class sizes to maximize learning
  • 90 days post training support

For more information please visit: http://acceleware.com/training/1028

Virtual School of Computational Science and Engineering

July 20th, 2012

The Virtual School of Computational Science and Engineering (VSCSE) helps graduate students, post-docs and young professionals from all disciplines and institutions across the country gain the skills they need to use advanced computational resources to advance their research. The VSCSE deploys conventional collaboration technologies in unconventional ways to create a national-scale virtual classroom that provides multiple high-quality audio and video channels for speakers, remote audiences, and various forms of content of immediate educational value to students.

Read the rest of this entry »

2 Day CUDA Workshop, May 5-6 2012, Berlin, Germany

April 21st, 2012

A 2 day CUDA workshop is taking place in Berlin, Germany on May 5 and 6 2012. Course details, outline and prices are available at http://cuda.eventbrite.com.

2-day CUDA workshop in Berlin

September 24th, 2011

The second 2-day CUDA programming workshop in Berlin takes place November 5-6. Course details, outline and prices are available at http://cuda.eventbrite.com.

Proven Algorithmic Techniques for Manycore Processors Summer School

July 20th, 2011

The Virtual School of Computational Science and Engineering (VSCSE) will offer a hands-on course for graduate students August 15-19:

Proven Algorithmic Techniques for Manycore Processors

This course will be delivered to a number of sites nationwide—including the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign—using high-definition video conferencing technologies. Students at all sites will be able to work with a cohort of fellow computational scientists, have access to local teaching assistants, and interact virtually with course instructors.

Registration for the weeklong course is $100. Please visit www.vscse.org for more information or hub.vscse.org to register.

Read the rest of this entry »

nCore Design Debuts New Training Course for GPU Processors

October 4th, 2009

nCore Design announces the immediate availability of the NCT-300 Programming GPU Processors course. Conceived with the experienced C/C++ programmer in mind, NCT-300 covers concepts and approaches related to programming GPU processors using both CUDA and OpenCL. The course covers GPU hardware, memories, data transport, CUDA and OpenCL APIs, programming methods and performance optimization. It will enable students to understand the fundamental aspects of GPU programming and become proficient in a relatively short time. Extensive hands-on laboratories demonstrate how to apply common numerical methods using both native APIs and open source libraries. Other topics covered in the course include integrating the Intel Threading Building Blocks (TBB) abstraction layer with native GPU software APIs in addition to a GPU debugging primer.

The class brochure is available for download. To register, schedule an on-site session or contact nCore Design, go to http://www.ncoredesign.com/company/contact_us.

Webinar: Jacket: Accelerating MATLAB using CUDA-Enabled GPUs

February 3rd, 2009

February 5, 2009, 11am PST / 2pm EST

Are you looking for ways to improve your productivity by accelerating MATLAB functions? Now you can with the unprecedented performance of GPU computing.

By attending this webinar, you will learn:

  • What is GPU computing
  • What is NVIDIA CUDA parallel computing architecture
  • What is the Jacket engine for MATLAB from AccelerEyes
  • How to get 10x to 50x speed-up for several MATLAB functions

Date: Thursday, February 5, 2009
Time: 11:00am PST / 2:00pm EST
Duration: 45 Minute Presentation, 15 Minute Q&A
Register Here
Presented By: Sumit Gupta, Ph.D., Sr Product Manager of Tesla GPU Computing at NVIDIA and John Melonakos, Ph.D., CEO at AccelerEyes LLC

“Parallel Computing for Graphics: Beyond Programmable Shading” SIGGRAPH Asia 2008 Course

December 23rd, 2008

The complete course notes from the “Parallel Computing for Graphics: Beyond Programmable Shading” SIGGRAPH Asia 2008 course , are available online. The course gives an introduction to parallel programming architectures and environments for interactive graphics and explores case studies of combining traditional rendering API usage with advanced parallel computation from game developers, researchers, and graphics hardware vendors. There are strong indications that the future of interactive graphics involves a programming model more flexible than today’s OpenGL and Direct3D pipelines. As such, graphics developers need a basic understanding of how to combine emerging parallel programming techniques with the traditional interactive rendering pipeline. This course gives an introduction to several parallel graphics architectures and programming environments, and introduces the new types of graphics algorithms that will be possible. The case studies in the class discuss the mix of parallel programming constructs used, details of the graphics algorithms, and how the rendering pipeline and computation interact to achieve the technical goals. The course speakers are Jason Yang and Justin Hensley (AMD), Tim Foley (Intel), Mark Harris (NVIDIA), Kun Zhou (Zhejiang University), Anjul Patney (UC Davis), Pedro Sander (HKUIST), and Christopher Oat (AMD) (Complete course notes.)