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 ...

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 ...

To see how you might apply the methods outlined in Part 1 to a practical computingproblem, consider the error diffusionalgorithm that is used in manycomputer graphics ...

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 ...

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 ...

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 ...

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 ...