Accelerating your C++ on GPU with SYCL—Simon Brand

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A post on writing GPGPU code in C++ using the SYCL standard from the Khronos group.

Accelerating your C++ on GPU with SYCL

By Simon Brand

From the article:

Leveraging the power of graphics cards for compute applications is all the rage right now in fields such as machine learning, computer vision and high-performance computing. Technologies like OpenCL expose this power through a hardware-independent programming model, allowing you to write code which abstracts over different architecture capabilities. The dream of this is “write once, run anywhere”, be it an Intel CPU, AMD discrete GPU, DSP, etc. Unfortunately, for everyday programmers, OpenCL has something of a steep learning curve; a simple Hello World program can be a hundred or so lines of pretty ugly-looking code. However, to ease this pain, the Khronos group have developed a new standard called SYCL, which is a C++ abstraction layer on top of OpenCL. Using SYCL, you can develop these general-purpose GPU (GPGPU) applications in clean, modern C++ without most of the faff associated with OpenCL.

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