Introduction to parallel computing for scientists and engineers. Shared memory parallel architectures and programming, distributed memory, message-passing data-parallel architectures, and programming.

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 ...

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 ...

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 ...

Intel's James Reinders presents some recurring themes for developers looking to improve their game when it comes to programming parallel systems... I'm James Reinders and, as I've travelled around ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...

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 ...

HAVE computers stopped getting faster? If you looked only at the clock speeds of microprocessor chips, you might well think so. A modern PC typically has a processor running at 3.0GHz (3 billion clock ...

PARALLEL DEBUGGING Debugging needs to be addressed regardless of the parallel programming approach. Existing debuggers are simply the starting point, because most don’t address many of the features ...

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 ...