Implementation of the High-Performance Computing Summer Institute at Jackson State University

Shuang Z. Tu, Chao Jiang
99 39

Abstract


Between May 25, 2023 and June 21, 2023, we hosted the inaugural four-week High-Performance Computing Summer Institute at Jackson State University. This endeavor was made possible through the support of a three-year NSF CISE-MSI grant. The primary objective of this Summer Institute revolved around the engagement, education, and empowerment of minority and underrepresented students in the realm of High-Performance Computing (HPC) within the field of engineering. Nine undergraduate students with diverse background were recruited to participate in this program.  Throughout the program, we immersed these students in a comprehensive curriculum that covered various critical facets of HPC. This curriculum encompassed hands-on instruction in Linux operating system command-line operations, C programming within the Linux environment, fundamental HPC concepts, parallel computing utilizing the Message Passing Interface (MPI) library, and GPU computing through OpenCL. Additionally, we delved into foundational aspects of fluid mechanics, geometric modeling, mesh generation, flow simulation via our in-house flow solvers, and the visualization of solutions. At the end of the program, every participant was tasked with delivering an oral presentation and submitting a written report encapsulating their acquired knowledge and experiences during the program. We are excited to share a detailed overview of our program's implementation with our audience. This includes insights into our utilization of ChatGPT to enhance C programming learning and our suggestion of the NSF ACCESS resources to gain access to HPC systems. We are proud to announce that the program has achieved remarkable success, as evidenced by the positive feedback we received from the participants.

Keywords


Engineering education, High performance computing, Summer institute, ChatGPT

Full Text:

PDF

References


ACCESS. https://access-ci.org/

ChatGPT. https://chat.openai.com.

Geuzaine, C. & Remacle, J.-F. A three-dimensional finite element mesh generator with built-in pre- and post-processing facilities, http://gmsh.info.

Gnuplot. http://www.gnuplot.info/.

Johnson, A., & Tezduyar, T. (1997). Parallel computation of incompressible flows with complex geometries, Int. J. Numer. Meth. Fluids 24, 1321.

Karypis, G. (n.d.). ParMETIS — parallel graph partitioning and fill-reducing matrix ordering, https://github.com/KarypisLab/ParMETIS.

Kitware. ParaView, https://www.paraview.org.

Rao, S.S. (2002). Applied Numerical Methods for Engineers and Scientists, published by Prentice Hall, ISBN-10: 0-13-089480-X, ISBN-13: 978-0-13-089480-9.

Schafer, M, Turek, S. (1996). Benchmark computations of laminar flow around a cylinder, in: E.H. Hirschel, (Ed), Flow Simulation with High-performance Computers II, Notes on Numerical Fluid Mechanics, Vieweg, 547-566.

TOP500, https://www.top500.org/statistics/details/osfam/1/

Tu, S., Aliabadi, S., Johnson, A., & Watts, M. (2005). A robust parallel implicit finite volume solver for high-speed compressible flows, AIAA Paper 2005-1396.

Tu, S. & Aliabadi, S. (2007). Development of a Hybrid Finite Volume/Element Solver for Incompressible Flows on Unstructured Meshes, International Journal of Numerical Methods in Fluids, Vol. 55, No. 2, pp. 177-203.




DOI: https://doi.org/10.46328/ijonest.200

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 International Journal on Engineering, Science and Technology

Abstracting/Indexing


 

 


International Journal on Engineering, Science and Technology (IJonEST)-ISSN: 2642-4088

 


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
 
 
.