OpenMP Training in Minnesota

OpenMP Training in Minnesota

Online or onsite, instructor-led live OpenMP training courses demonstrate through interactive hands-on practice how to develop parallel applications for platforms from desktops to non-shared memory systems.

OpenMP training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Minnesota onsite live OpenMP trainings can be carried out locally on customer premises or in NobleProg corporate training centers.

NobleProg -- Your Local Training Provider

MN, Eagan - Grand Oak I

Grand Oak
860 Blue Gentian Road Suite 200
Eagen, ME 55121
United States
,
See map: Google Maps
Maine US
MN, Eagan - Grand Oak I
Learn OpenMP in our training center in Minnesota. The venue is located in the Grand Oak I in the neighboorhood of Canon Solutions America, MN Society of Professional Engineers, Learners Edge and Mendota Insurance Company. Read more

MN, Minneapolis - Fifth Street Towers

Fifth Street Towers
100 South Fifth Street 19th Floor
Minneapolis, MN 55402
United States
,
See map: Google Maps
Minnesota US
MN, Minneapolis - Fifth Street Towers
Learn OpenMP in our training center in Minnesota.

Fifth Street Towers is a LEED Gold, Energy Star® certified, two-tower Class A office complex conveniently located at the confluence of bus and light rail transit systems in downtown Minneapolis, just across the street from Soo Line Building City Apartments. 

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OpenMP Course Events - Minnesota

OpenMP Course Outlines in Minnesota

Course Name
Duration
Overview
Course Name
Duration
Overview
14 hours
This instructor-led, live training in Minnesota (online or onsite) is aimed at software engineers who wish to develop parallel applications using OpenMP.

By the end of this training, participants will be able to:

- Understand and use parallel programming with Fortran in OpenMP.
- Calculate fractals in parallel to render multiple pixels and characters.
- Implement vector programming with SIMD extensions for HPC systems.
- Add parallel blocks for specifying shared memory parallelism.

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