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 ...

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 ...

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

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

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 ...

For example, an engineer may develop a real-time embedded control system at the same time as its human-machine interface. Maybe the system also has a computation-intensive task such as high-speed ...

In this video, Michael Wolfe from PGI continues his series of tutorials on parallel programming. “The second in a series of short videos to introduce you to parallel programming with OpenACC and the ...

One size does not fit all, and it never will. Parallel programming looks to level the playing field by leveraging multicore hardware. It was easy to program applications in the days when one chip, one ...

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 ...

In case you don’t read the sidebar (you really should, you know), I’ve written a review of Calvin Lin and Larry Snyder’s relatively new book, “Principles of Parallel Programming” (we’ve never met, but ...