Hosting a Credit-Bearing Course
Information
Texas A&M High Performance Research Computing often receives requests to support courses at Texas A\&M which require the use of High Performance Research Computing Resources. Professors are strongly encouraged to reach out to High Performance Research Computing for assistance in the administration of accounts for students enrolled in such classes. For more in-depth information on who can apply which type of accounts, as well as information pertaining to different types of accounts, please refer to the Resource Allocation Policy on our website. For information regarding the TAMU HPRC clusters and guides for configuring your SSH client, see the Detailed Access page.
Procedure
Application for Accounts
Instructors teaching the courses should instruct their students to individually apply for Basic accounts via the Account Management System on our website. When applying, students should list the instructor as their PI and indicate that the account will be used in connection with that specific course. A research summary is required on the application. Instructors should provide students needed information for the research summary. Basic accounts typically take 2-3 business days to process and approve.
As with all Basic accounts, students will be allocated 5,000 SU's. If additional SU's are required by a student, their PI will be responsible for sub-allocating SU's from an eligible Startup or Research Account.Per policy, HPRC cannot allocate additional SU's to Basic accounts.
Instructor Responsibilities
Instructors are highly encouraged to apply for a Startup account.
Please provide students with a research summary statement for their basic applications. Instructors should, as early as possible, supply High Performance Research Computing with a list of students enrolled in their class to be used for validation of student applications.
Instructors are also responsible for supplying additional SU's to students who deplete their Basic allocation of 5,000 SU's. These additional SU's must be sub-allocated from a Startup or Research Account in the name of the Instructor who was listed as the PI of the student.
It is also the responsibility of the Instructor to provide HPRC, by the official census date for the corresponding semester, with a list of students who have dropped the course.
Instructors are also highly encouraged to inform HPRC of any critical dates for class projects that need a particular cluster (to help us schedule cluster maintenance accordingly).
Student Responsibilities
Students are encouraged to read the appropriate system guide.
Each student must apply for their own individual Basic account. Each student should mention in their application that this Basic account is for use with their corresponding class.
NOTE: A student may only have ONE basic account per fiscal year. If a student already has a basic account with HPRC, there is no need to apply for an account for use with their class.
Students should familiarize themselves with the basic usage policies of the machines.
List of Classes that have used HPRC Resources
• AERO 402: Aerospace Vehicle Design II
• AERO 643: High-Performance Computational Fluid Dynamics
• ASTR 420: Advanced Astrophysical Research
• BCBP 689: Big Data Fundamentals
• BICH 414: Biochemical Techniques I
• BIMS 491: Research
• BIOL 647-600: Digital Biology
• BIOL 650-600: Genomics (Galaxy)
• BMEN 443/689: Biomolecular and Cellular Engineering Laboratory
• CHEM 326: Physical Chemistry Laboratory II
• CHEM 641: Structural Inorganic Chemistry
• CHEM 658: Introduction to Molecular Modeling
• CHEN 491: Undergraduate Research
• CSCE 435: Parallel Computing
• CSCE 482: Senior Capstone Design
• CSCE 620: Computational Geometry
• CSCE 636: Deep Learning
• CSCE 659: Parallel and Distributed Numerical Algorithms
• CSCE 678: Distributed Systems and Cloud Computing
• CSCE 689: SPTP: Reinforcement Learning
• CSCE 735: Parallel Computing
• ECEN 689: Special Topics in Scientific Machine Learning
• GENE 689-600: Bioinformatics Command Line
• GENE 689-601: Metagenomics Data Analysis
• MARB 433: Applied Bioinformatics
• MATH 647: Mathematical Modeling
• MEEN 399: Mathematical Modeling
• MSEN 655: Materials Design Studio
• PHYS 619: Modern Computational Physics
• STAT 624: Databases and Computational Tools Used in Big Data
• STAT 689: Large-Scale Inference & Covariance Estimation
• PHEB 602: Biostatistics I (Spring 2019)
• PHEB 606: Survival Analysis (Spring 2019)
• PHEB 609: Categorical Data Analysis (Spring 2019)
• PHEB 614: Analysis of Longitudinal and Multilevel Data (Spring 2019)
• VLCS 689: Metagenomics Sequencing Informatics