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

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 ...

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 ...

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 ...

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 ...

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 ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

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 monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...