Parallel programming, and OpenACC, is used in high-performance computing in the fields of bioinformatics, quantum chemistry, astrophysics and more. “The model was made to ensure that scientists spend ...

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 ...

Whether modifying an existing application or writing entirely new code, parallel applications can be much more challenging to work with than their sequential counterparts. Without a doubt, the ...

As hardware architectures become more parallel (with the advent of multicore processors and FPGAs, for example), sequential programming languages are forced to deal with representing parallelism ...

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.

2) We can abandon automaticparallelization and extend our existing sequential languages withexplicit constructs to initiate parallel activities and to coordinatetheir interactions. There are a large ...

The authors of my Editor’s Top Picks for this week – Atego’s Kelvin Nilsen and Adacore’s S. Tucker Taft – believe that despite all the tools that allow embedded systems developers to maintain ...

The proposed parallel fully dynamic APSP algorithm is based on a sequential dynamic APSP algorithm, whose direct implementation in the MPC model can result in a large round complexity which is ...