Modern personal computing devices feature multiple cores. This is not only true for desktops, laptops, tablets and smartphones, but also for small embedded devices like the Raspberry Pi. In order to ...

NVIDIA’s CUDA is a general purpose parallel computing platform and programming model that accelerates deep learning and other compute-intensive apps by taking advantage of the parallel processing ...

Hi, I’m James Reinders, and today we’re going to talk about threading building blocks. In fact, this is part one of a look at threading building blocks, which is an interesting template library for ...

Programmers have been interested in leveraging the highly parallel processing power of video cards to speed up applications that are not graphic in nature for a long time. Here, I explain how to do ...

Programming languages are evolving to bring the software closer to hardware. As hardware architectures become more parallel (with the advent of multicore processors and FPGAs, for example), sequential ...

This week is the eighth annual International Workshop on OpenCL, SYCL, Vulkan, and SPIR-V, and the event is available online for the very first time in its history thanks to the coronavirus pandemic.

As modern .NET applications grow increasingly reliant on concurrency to deliver responsive, scalable experiences, mastering asynchronous and parallel programming has become essential for every serious ...

In the task-parallel model represented by OpenMP, the user specifies the distribution of iterations among processors and then the data travels to the computations. In data-parallel programming, the ...

Dr. Guy Blelloch of Carnegie Mellon University has written an article for the folks at CilkArts analyzing why parallel programming seems to be more difficult than sequential programming. He quickly ...

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