In data-parallel programming, the user specifies the distribution of arrays among processors, and then only those processors owning the data will perform the computation. In OpenMP’s master / slave ...

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 ...

Often the same large data structures are used by long sequences of kernels ... And programming GPUs will be no more – or less – difficult than parallel programming for multicore CPUs. Michael Wolfe ...

This means multiple parts of the code execute at the same time and have access to same set of shared data. However, parallel programming using threads is complicated and hard to debug. When a thread ...

In 2003, a team of researchers led by Ian Buck unveiled Brook, the first widely adopted programming model to extend C with data-parallel constructs ... reports the same speed boosts, and that ...

Students taking the course for COMP_ENG/COMP_SCI-368 credit will work on labs that utilize advanced parallel programming, data layout, and algorithm decomposition concepts. Students taking the course ...

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 ... while at the same ...

In Part 2 of this three-part series on dataflow programming with the Task Parallel Library, Eric Vogel shows you how to create a Windows 8 application that uses a composite parallel data flow. In Part ...

What do you plan for the immediate future in parallel programming? We will remain focused on C and C++, so that we can make data parallel programming a reality that developers can use to build ...

This online research computing specialization introduces learners to the fundamentals of high performance and parallel computing and includes big data analysis, machine learning, parallel programming, ...