In this slidecast, Torsten Hoefler from ETH Zurich presents: Data-Centric Parallel Programming. "To maintain performance portability in the future, it is imperative to decouple architecture-specific ...

Have a broad understanding of data parallel architectures and programming. Design a data parallel program for a given parallel algorithm using High Performance Fortran (HPF), measure real speedups, ...

Adding these types of parallel computing services illustrates how programming languages are changing. Continue to page 4 In scatter-gather, a typical parallel-programming pattern, data is ...

COMP_ENG 358: Intro to Parallel Computing. This course is not currently offered. Prerequisites COMP_SCI 211 Description Introduction to parallel computing for scientists and engineers. Shared memory ...

“The Landscape of Parallel Computing Research: A View from Berkeley,” Technical Report No. UCB/EECS-2006-183, University of California, Berkeley, Dec. 18, 2006 ...

In the past few years, more and more systems with a parallel architecture have been released. They are orders of magnitude faster and can handle significantly more data than their serial counterparts.

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 ...

Writing parallel code, programming efficiency, translation, ... According to the study, the average median-sized data set used in a technical computing application today ranges from 10 to 45 gigabytes ...

In OpenMP’s master / slave approach, all code is executed sequentially on one processor by default. In data-parallel programming, all code is executed on every processor in parallel by default. The ...