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GPU computing in MATLAB webinar (in Russian)

August 29, 2013 at 10:00 Moscow time

Softline and MathWorks invite you to participate in a free webinar, “GPU Computing in MATLAB”, which will be held on August 29 at 10:00 Moscow time.

In this webinar, you will learn how to use the NVIDIA CUDA GPUs in your calculations in MATLAB with minimal code changes.

Opportunities to work with MATLAB GPU is well suited in many areas, including data analysis, signal and image processing, financial engineering, seismic data processing, etc. Functionality available in the Parallel Computing Toolbox, allows for powerful computing on the GPU, using the familiar language of MATLAB without complex programming.

In the webinar will cover the following topics:
The use of overloaded MATLAB functions for GPU
Calling CUDA kernels directly from MATLAB
Development of applications and software components that use the GPU

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Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

The platforms are

Node 1
  • GPU device 0: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
  • CPU: AMD Phenom II X6 @ 2.8GHz 1055T
  • RAM: 12GB
  • OS: OpenSUSE 13.1
  • SDK: AMD APP SDK 2.9
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.2
  • SDK: nVidia CUDA Toolkit 6.0.1, AMD APP SDK 2.9

Completed OpenCL project should be uploaded via User dashboard (see instructions and example there), compilation and execution terminal output logs will be provided to the user.

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