C++ Accelerated Massive Parallelism (C++ AMP) is a new open specification heterogeneous programming model, which builds on the established C++ language. Developed for heterogeneous platforms C++ AMP is designed to accelerate the execution of C++ code by taking advantage of the data-parallel hardware that is commonly present as a GPU. These courses are aimed at programmers who are looking to develop comprehensive skills in writing and optimizing applications using C++ AMP. Read the rest of this entry »

Partnering with NVIDIA and Microsoft, this four-day CUDA training course is designed for GPU Programmers in the oil-and-gas industry who are looking to develop comprehensive skills in writing and optimizing applications that fully leverage the many-core processing capabilities of the GPU.

Partnering with NVIDIA and Microsoft, this four-day CUDA training course is designed for GPU Programmers who are looking to develop comprehensive skills in writing and optimizing applications that fully leverage the many-core processing capabilities of the GPU.

Microsoft has announced that the next version of Visual Studio will contain technology labeled C++ Accelerated Massive Parallelism (C++ AMP) to enable C++ developers to take advantage of the GPU for computation purposes. More information is available in the MSDN blog posts here and here.

In Silicon Valley? Interested in C++? Join in an evening with Microsoft & NVIDIA to discuss new C++ technology for parallel computing. Register here: http://vnextmsvc.eventbrite.com/

• 5:45 PM Welcome & Registration
• 6:00 PM Heterogeneous Parallelism in General, C++ in AMP in Particular, presented by Herb Sutter, Principal Architect for Windows C++, Microsoft
• 7:15 PM ALM tools for C++ in Visual Studio V.NEXT, presented by Rong Lu, Program Manager C++, Microsoft
• 8:00 PM The Power of Parallel, presented by the NVIDIA Team;
  • Parallel Nsight: Programming GPUs in Visual Studio, Stephen Jones, NVIDIA;
  • CUDA 4.0: Parallel Programming Made Easy, Justin Luitjens, NVIDIA;
  • Thrust: C++ Template Library for GPGPUs, Jared Hoberock, NVIDIA

Refreshments provided.