The Graduate Certificate in High-Performance Computing is intended for students with interest in applying computational and data science approaches that require parallel and/or high-performance computing to their research problems, or who generally desire broad training in parallel computational methodology.
Requirements for the Graduate Certificate in High-Performance Computing
Students must complete a minimum of 9 credits from the following:
	
		
		
		
		
		
		
		
		
	
	
		
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			| 1.   | 
			The following core course (3 credits): | 
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			CMSE | 
			822 | 
			Parallel Computing | 
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			3 | 
		
		
			| 2. | 
			Two or more additional courses selected from the following: | 
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			AST | 
			911 | 
			Numerical Techniques in Astronomy | 
			2 | 
		
		
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			CEM | 
			883 | 
			Computational Quantum Chemistry | 
			3 | 
		
		
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			CEM | 
			888 | 
			Computational Chemistry | 
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			3 | 
		
		
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			CSE | 
			836 | 
			Probabilistic Models and Algorithms in Computational Biology | 
			3 | 
		
		
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			CSE | 
			845 | 
			Multi-disciplinary Research Methods for the Study of Evolution | 
			3 | 
		
		
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			CSE | 
			881 | 
			Data Mining | 
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			3 | 
		
		
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			ECE | 
			837 | 
			Computational Methods in Electromagnetics | 
			3 | 
		
		
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			ME | 
			835 | 
			Turbulence Modeling and Simulation | 
			3 | 
		
		
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			ME | 
			840 | 
			Computational Fluid Dynamics and Heat Transfer | 
			3 | 
		
		
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			ME | 
			872 | 
			Finite Element Method | 
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			3 | 
		
		
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			MTH | 
			850 | 
			Numerical Analysis I | 
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			3 | 
		
		
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			MTH | 
			851 | 
			Numerical Analysis II | 
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			3 | 
		
		
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			MTH | 
			852 | 
			Numerical Methods for Ordinary Differential Equations | 
			3 | 
		
		
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			MTH | 
			950 | 
			Numerical Methods for Partial Differential Equations I | 
			3 | 
		
		
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			MTH | 
			951 | 
			Numerical Methods for Partial Differential Equations II | 
			3 | 
		
		
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			MTH | 
			995 | 
			Special Topics in Numerical Analysis and Operations Research | 
			3 to 6 | 
		
		
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			PHY | 
			915 | 
			Computational Condensed Matter Physics | 
			2 | 
		
		
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			PHY | 
			919 | 
			Modern Electronic Structure Theory | 
			2 | 
		
		
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			PHY | 
			950 | 
			Data Analysis Methods for High-Energy and Nuclear Physics | 
			2 | 
		
		
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			PHY | 
			998 | 
			High Performance Computing and Computational Tools for Nuclear Physics | 
			2 | 
		
		
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			PLB | 
			810 | 
			Theories and Practices in Bioinformatics | 
			3 | 
		
		
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			QB | 
			826 | 
			Introduction to Quantitative Biology Techniques | 
			1 | 
		
		
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			STT | 
			802 | 
			Statistical Computation | 
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			3 | 
		
		
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			STT | 
			874 | 
			Introduction to Bayesian Analysis | 
			3 | 
		
		
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			Additional courses at the 800-level or above may be used to fulfill this requirement if approved by the CMSE graduate advisor. Students must have a minimum 3.0 grade-point average in courses applied to the certificate in order for it to be awarded. |