High Performance Computing (HPC) and parallel programming techniques underpin many of today’s most demanding computational tasks, from complex scientific simulations to data-intensive analytics. This ...

Parallel programming exploits the capabilities of multicore systems by dividing computational tasks into concurrently executed subtasks. This approach is fundamental to maximising performance and ...

Aater Suleman at the Future Chips blog looks at how to choose the best task size at run-time for parallel programming. He analyzes the trade-offs and explains some recent advances in work-queues that ...

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 ...

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 ...

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 ...

A technical paper titled “Scalable Automatic Differentiation of Multiple Parallel Paradigms through Compiler Augmentation” was published by researchers at MIT (CSAIL), Argonne National Lab, and TU ...

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.

Two Google Fellows just published a paper in the latest issue of Communications of the ACM about MapReduce, the parallel programming model used to process more than 20 petabytes of data every day on ...

For those trying to keep track of the myriad Microsoft efforts in the parallel programming/distributed computing space, here's a new language to add to your list ...