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 ...

One of the best features of using FPGAs for a design is the inherent parallelism. Sure, you can write software to take advantage of multiple CPUs. But with an FPGA you can enjoy massive parallelism ...

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 ...

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 ...

This course focuses on developing and optimizing applications software on massively parallel graphics processing units (GPUs). Such processing units routinely come with hundreds to thousands of cores ...

Multicore processors have been around for many years, and today, they can be found in most devices. However, many developers are doing what they've always done: creating single-threaded programs. They ...

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 ...

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 ...

Most notably, the chipmaker announced a compiler source code enabling software developers to add new languages and architecture support to Nvidia’s CUDA parallel programming model. The new ...

The ubiquitous field-programmable gate array (FPGA) is finding use as a software accelerator in many applications, including the communications, image processing, biomedical, and scientific computing ...