StreamComputing focuses on making the concepts of OpenCL™ clear in order to give developers the skills needed to embed OpenCL™ into their code. Lab sessions are done using a unique top-down method to speed up understanding and to be able to focus on the important parts. After training, developers are able to select the algorithms that can best be tackled by a GPU and optimize C, C++ or Java-code to get the full potential out of the processors.
Personlized OpenCL Training Throughout Europe
StreamComputing trains IT-experts in OpenCL™ world-wide. All training can be given in English or Dutch, and on-request printed materials can be translated into your local language. All courses are adapted to the specific needs of the group by focusing on porting existing GPGPU-code to OpenCL™, optimizing code to maximize performance, and assessing HPC architectures. Learn more.
Sample Training Modules
Introduction to OpenCL programming: host-side
This is mostly a lab-session and you will learn how to integrate kernels in your favourite programming-language: C, C++, Java, Python, Clyther and more. All solutions will be compared to the long official initialisation of OpenCL-software. Also caching kernels are described.
Introduction to OpenCL programming: kernels
This is mostly a lab-session and you will learn the basics of kernel-programming for chosen platforms, including AMD APU and GPU. This is excluding architecture specific optimizations, but you will learn by example for existing solutions.
Integrating into existing software
While porting to OpenCL is a much requested option, actually embedding the code into your software is somewhat more difficult. Say you found the calculation bottle-neck in your software, is the rest of your software able to handle the extra speed?
Developing on Android (ARM)
Learn how to program OpenCL-on-ARM and RenderScript Compute.
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