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

  • Supporting hardware, operating system, and applications
  • Troubleshooting performance issues, system errors, etc

Requesting Accounts on Arc

To request a new HPC Account on Arc please click here to submit your support ticket. 

About ARC

 

HPC can be used to:

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

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 entering a request via the ServiceNow Self-Service Portal.  

Publications:

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

"This work received computational support from UTSA’s HPC cluster Arc, operated by Tech Solutions."

computer visualization
Figure representing the second harmonic generation polarization dependence for two gold nanocrescents by Dr. Nicholas Large
rough disks
Figure showing a hybrid metallic-semiconductor nanostructure (gold nanodisks covered by a monlayer of MoSe2) by Dr. Nicholas Large.

Publications Using the previous HPC cluster, 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
  • Bigdely-Shamlo, N.,Touryan, J., Ojeda, A., Kothe, C., Mullen, T., & Robbins, K. (2019). Automated EEG mega-analysis I: Spectral and amplitude characteristics across studies. Neuroimage, 203, pp. 116361. doi: 10.1016/j.neuroimage.2019.116361
  • Bigdely-Shamlo, N.,Touryan, J., Ojeda, A., Kothe, C., Mullen, T., & Robbins, K. (2019). Automated EEG mega-analysis II: Cognitive aspects of event related features. NeuroImage, 203, pp. 116054. doi: 10.1016/j.neuroimage.2019.116054