High Performance Computing

 

 

Additional Research Computing Services

 

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SHAMU is one of UTSA's high performance computational clusters and is maintained by University Technology Solutions (UTS) Research Computing Support Group (RCSG). RCSG provides performance solutions to Shamu that includes:

 

  • Support hardware, operating system, and applications
  • Troubleshoot performance issues, system errors, etc 

 

   Requesting Accounts on Shamu

  


 

About SHAMU:

 

SHAMU specs

 

HPC can be used to:

  • Develop and redesign products
  • Optimize production and delivery processes
  • Analyze or develop large datasets
  • Conduct large-scale research projects
  • Store large amounts of data for future analysis
  • Perform consumer trend monitoring, searching or profiling
  • Create computer visualizations that explain research results
  • Carry out simulations and / or modelling of complex processes

Available Software on SHAMU

ShamuSoftwareimage.png

Major applications include:

  • Data storage and analysis
  • Data mining
  • Simulations
  • Modelling
  • Software development
  • Visualization of complex data
  • Rapid mathematical calculations 

      * additional software can be installed by contacting RCSG *

 


 

 

Publications:

 

Please remember to acknowledge the use of Shamu in any publications, papers, reports, etc. Wording should be as stated below:

"This work received computational support from UTSA’s HPC cluster SHAMU, operated by the Office of Information Technology."

 

second harmonic generation theory figure           figure of a hybrid metallic semiconductor nano structure
 Figure representing the second harmonic generation polarization dependence for two gold nanocrescents by Dr. Nicholas Large    Figure showing a hybrid metallic-semiconductor nanostructure (gold nanodisks covered by a monlayer of MoSe2) by Dr. Nicholas Large.

   

Publications Using SHAMU:

Olufunso, O., Giacomoni, M. (2017). Enhancing the performance of multiobjective evolutionary algorithm for sanitary sewer overflow reduction.  Journal of Water Resources Management and Planning, 143(7). doi:10.1061/(asce)wr.1943-5452.0000774

Itaquy, B., Olufunso, O., Giacomoni, M. (2017). Application of multi-objective genetic algorithm to reduce wet weather sanitary sewer overflows and surcharge. Journal of Sustainable Water in the Built Environment, 3. doi:10.1061/jswbay.0000826

Maiti, A., Maity, A., Satpati, B., Large, N., & Chini, T.K. (2016). Efficient excitation of higher order modes in the plasmonic response of individual concave gold nanocubes. Journal of Physics and Chemistry, 12, 731-740. doi:10.1021/acs.jpcc.6b11018

 

 

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