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 ...

Programming languages are evolving to bring the software closer to hardware. As hardware architectures become more parallel (with the advent of multicore processors and FPGAs, for example ...

This fundamental change in cost model may require algorithms to beredesigned: how we map work to different processors, how we place datain the machine's memory relative to processors, and how we ...

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.

In “ ParaSail: less is more with multicore, ” Taft takes another approach to migrating to a more efficient parallel programming environment. He says Parasail will allow embedded developers to stick ...

The team designed a fully dynamic APSP algorithm in the MPC model with low round complexity that is faster than all the existing static parallel APSP algorithms. The proposed parallel fully ...

Chain-of-experts chains LLM experts in a sequence, outperforming mixture-of-experts (MoE) with lower memory and compute costs.