The enormous growth in artificial intelligence (AI) and Internet of Things (IoT) is fueling a growing demand for high-efficiency computing to perform real-time analysis on massive amounts of data. In ...

The difference between distributed computing and concurrent programming is a common area of confusion as there is a significant amount of overlap between the two when you set out to accomplish ...

There is always the promise of using more computing power for a single task. Your computer has multiple CPUs now, surely. Your video card has even more. Your computer is probably networked to a slew ...

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.

In this slidecast, Torsten Hoefler from ETH Zurich presents: Data-Centric Parallel Programming. The ubiquity of accelerators in high-performance computing has driven programming complexity beyond the ...

Write program to run in parallel? Yes. Did you remember to use a Scalable Memory Allocator? No? Then read on … In my experience, making sure “memory allocation” for a program is ready for parallelism ...

Graphics processing units (GPUs) are traditionally designed to handle graphics computational tasks, such as image and video processing and rendering, 2D and 3D graphics, vectoring, and more.

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 ...

Microsoft has purchased the assets of Interactive Supercomputing (ISC), a desktop parallel-computing vendor, according to a blog post on the Windows Server Division Weblog. The move fits in with ...