Click to learn more about the events on April 9-10th, 2018 at Torg. 1100 and the Inn at Virginia Tech.
At the upcoming 2018 IEEE VR Conference, Dr. Nicholas Polys is leading a Web3D Visualization Tutorial, where these and other techniques will be presented: http://ieeevr.org/2018/program
The Visionarium Lab (Torgersen Hall 3050) is open for drop-in hours M W F 12:00-1:00 pm.
A COMSOL batch job can run in parallel, using multiple nodes or processors. Information on how to automatically set the appropriate COMSOL command line parameters for parallel execution is available, including an example script, athttps://secure.hosting.vt.edu/www.arc.vt.edu/userguide/comsol/.
ARC will offer many free classes on scientific computing, sponsored by Network Learning Initiatives (NLI) and held in room 1100 Torgersen. NLI encourages you to register for these classes through their web site https://nli.tlos.vt.edu, but unregistered auditors are welcome to sit in.
For a list of dates, times, and titles for the classes, refer to
Instructors who wish to introduce their class to high performance computing are welcome to request a class account.
The process for BlueRidge, Cascades, DragonsTooth and NewRiver, is described in https://secure.hosting.vt.edu/www.arc.vt.edu/userguide/get-an-arc-account-for-your-class/ .
Instructors interested in arranging access to Huckleberry for their students can find out how to get a class account at
Some information on how to prepare and compile a FORTRAN program for use on the ARC GPU’s is available in https://secure.hosting.vt.edu/www.arc.vt.edu/userguide/cuda_fortran/
A short discussion of licensed software installed on ARC clusters has been posted at :
Many user programs reference the LAPACK (Linear Algebra PACKage) library. The ARC software library does not include a standalone compiled version of this library. However, a highly tuned version of the LAPACK library is included in the ATLAS library (along with the BLAS, FFT functions, and many others). The optimized versions of LAPACK functions available through the MKL library typically offer better performance than a user could get from a source code library of LAPACK. For details, refer to https://secure.hosting.vt.edu/www.arc.vt.edu/userguide/lapack_mkl/ .
Many user programs reference the LAPACK (Linear Algebra PACKage) library. The ARC software library does not include a standalone compiled version of this library. However, some of the most useful LAPACK functions are available in the ATLAS library, which contains automatically tuned versions of those functions, as well as every BLAS function. Automatic tuning typically offers better performance than a user could get from a source code library of LAPACK. For details, refer to https://secure.hosting.vt.edu/www.arc.vt.edu/userguide/lapack_atlas/ .