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100%
Using loop directives to improve performance
05.02.2019
Home »  Archive  »  2019  »  Issue 49: Anato...  » 
Lead Image © orson, 123RF.com
topologies to reduce latency, improve bandwidth, and improve scalability. Directives A popular X category is the directive [2], which includes OpenMP and OpenACC, both of which were formed to standardize ... OpenACC is a great tool for parallelizing applications for a variety of processors. In this article, I look at one of the most powerful directives, parallel loop. ... OpenACC
18%
Living with multiple and many cores
14.03.2013
Home »  Archive  »  2013  »  Issue 13: IPv6...  » 
considered "non-portable." One promising solution is the use of OpenACC comment directives [4] in existing Fortran and C/C++ code. The code still remains portable and can be compiled to run on a standard CPU
15%
Environment Modules Using Lmod
04.10.2018
Home »  Archive  »  2018  »  Issue 47: Findi...  » 
Lead Image © Federico Caputo, 123RF.com
applications. For example, someone might code with OpenACC [4] to target GPUs and Fortran for PGI compilers, along with Open MPI, whereas another person might use GNU Compiler Collection (GCC) 8.1 with MPICH
14%
Selecting compilers for a supercomputer
18.02.2018
Home »  Archive  »  2018  »  Issue 43: Real...  » 
Lead Image Photo by Michal Kmet on Unsplash
-core processors. Efficiently implementing these OpenMP concepts (or alternative models such as OpenACC) in the selected compiler suite is necessary for successful optimization. With the high complexity
13%
Modern Fortran for today and tomorrow
17.06.2017
Home »  Archive  »  2017  »  Issue 39: Conta...  » 
Lead Image © homestudio, 123RF.com
directives is that if the compiler is not HPF-aware, it views the directives as comments and just moves on. This is the same approach taken by OpenACC [12] and OpenMP [13]. The HPF extensions never seemed
13%
CPU affinity in OpenMP and MPI applications
03.02.2022
Home »  Archive  »  2022  »  Issue 67: syst...  » 
Lead Image © podfoto, 123RF.com
serial, OpenMP, OpenACC, and MPI code. I carefully watch the load on each core with GkrellM [3], and I can see the scheduler move processes from one core to another. Even when I leave one to two cores free

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