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 ...

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

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 ...

When Donald Becker introduced the idea of a Beowulf cluster while working at NASA in the early 1990s, he forever changed the face of high-performance computing. Instead of institutions forking out ...

Two Google Fellows just published a paper in the latest issue of Communications of the ACM about MapReduce, the parallel programming model used to process more than 20 petabytes of data every day on ...

Intel Parallel Studio XE and Cluster Studio brings parallel computing tools to Linux and Microsoft Visual Studio developers. The compilers support Intel's Parallel Building Blocks and the Fortran ...

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I just finished reading the new book by David Kirk and Wen-mei Hwu called Programming Massively Parallel Processors. The generic title notwithstanding, readers should not come to this book expecting ...

In the task-parallel model represented by OpenMP, the user specifies the distribution of iterations among processors and then the data travels to the computations. In data-parallel programming, the ...