Modern software takes computational speed for granted. But modern microprocessors can only speed up by increasing the number of cores. To take full advantage of multiple cores, software developers ...

Recently, I had the good fortune to present a class at the ACM Conference for Computer Science Educators (SIGCSE). While I definitely shared my enthusiasm for parallel programming, I had two key goals ...

Multicore chip designs, large symmetrical multiprocessing (SMP) systems, and clustering can bring many processors to bear on an application. But without proper software, they're simply large ...

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 ...

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 ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

A hands-on introduction to parallel programming and optimizations for 1000+ core GPU processors, their architecture, the CUDA programming model, and performance analysis. Students implement various ...

Computer chips have stopped getting faster: The regular performance improvements we've come to expect are now the result of chipmakers' adding more cores, or processing units, to their chips, rather ...

From your smartphone to your laptop, today’s tech devices glean their computing power from multi-core processors. Supercomputers contain thousands of cores, and within three to four years a computer ...

One thing DDS systems do better than most parallel-programming environments is handle transient connections, because they support best-effort delivery. In many applications, it’s sufficient to retain ...