Daemon Deacons
Primary Advisor
Event Type
Student Cluster Competition
Career Development
Diversity Equity Inclusion (DEI)
Education and Training and Outreach
HPC Training and Education
System Administration
Workforce
TP
XO / EX
TimeMonday, 15 November 20217pm - 9pm CST
LocationBooth 133
DescriptionWake Forest University is a liberal arts university with a predominantly undergraduate population currently listed on US World News Reports with a National Rank of #28. Located in North Carolina, Wake Forest University has about 5,000 undergraduate and 3,000 graduate students and prides itself on its low faculty-student ratio (1:10). In 2018, we were the first school from North Carolina to participate in the SC Student Cluster Competition (SCC), and we have now competed for three consecutive years.
To prepare for the competition, the Computer Science Department created a brand new High Performance Computing class in Fall 2017. It has been taught for 12 consecutive semesters by Prof. Samuel Cho (Associate Prof., Depts. Computer Science & Physics), who is the primary advisor for this team. Prof. Cho has extensive experience performing research and teaching classes in GPU Programming, Parallel Algorithms, Computational Biophysics, and Machine Learning. He has received funding from the National Science Foundation, National Institutes of Health, and NVIDIA, Inc. for research in those subjects. In addition, our team has three secondary advisors, Adam Carlson (Senior UNIX Systems Administrator), Cody Stevens (HPC UNIX Systems Administrator), and Dr. Sean Anderson (HPC UNIX System Administrator); together, they comprise the High Performance Computing Team at our university’s DEAC Supercomputing Facility (4K CPU and 12K+ GPU cores). All advisors have extensive practical experience in compiling, running, benchmarking, and maintaining a variety of HPC applications and hardware. To date, 41 unique undergraduate students have taken the High Performance Computing class over the past 5 years. In addition, the Department of Computer Science has committed to funding the travel of our team and transport hardware if our team competes in person. If our team competes virtually, they have committed to provide Azure Cloud credits until our team receives credit from the SCC organizers, and they will also provide a dedicated space in the department for the team to compete.
Our current undergraduate student team consists of Junior (5) and Senior (2) students with majors in Computer Science, Mathematics, Mathematical Statistics, and Politics & International Affairs (half are double-majors), and minors in Mathematics, Japanese, and Neuroscience. Our team will will consist of six students, but we will switch one student if we compete virtually. Two of the students are returning veterans who participated in the previous SC20 SCC, and five are new students. Our students have taken a wide range of relevant prerequisite classes, including Data Structures I and II, Databases, Parallel Computing, GPU Programming, Numerical Linear Algebra, and Machine Learning and code in C/C++, Java, Python, MATLAB, R, CUDA, and SQL.
All team members want to receive a deeper hands-on experience on high performance computing hardware and software than their other classes, develop their problem solving and teamwork skills, and apply those skills to their research projects involving HPC and big data, and broaden their career prospects in areas such as machine learning, artificial intelligence, and data analytics. They also enjoyed their last competing experience or heard from other students how much they enjoyed it.
To prepare for the competition, the Computer Science Department created a brand new High Performance Computing class in Fall 2017. It has been taught for 12 consecutive semesters by Prof. Samuel Cho (Associate Prof., Depts. Computer Science & Physics), who is the primary advisor for this team. Prof. Cho has extensive experience performing research and teaching classes in GPU Programming, Parallel Algorithms, Computational Biophysics, and Machine Learning. He has received funding from the National Science Foundation, National Institutes of Health, and NVIDIA, Inc. for research in those subjects. In addition, our team has three secondary advisors, Adam Carlson (Senior UNIX Systems Administrator), Cody Stevens (HPC UNIX Systems Administrator), and Dr. Sean Anderson (HPC UNIX System Administrator); together, they comprise the High Performance Computing Team at our university’s DEAC Supercomputing Facility (4K CPU and 12K+ GPU cores). All advisors have extensive practical experience in compiling, running, benchmarking, and maintaining a variety of HPC applications and hardware. To date, 41 unique undergraduate students have taken the High Performance Computing class over the past 5 years. In addition, the Department of Computer Science has committed to funding the travel of our team and transport hardware if our team competes in person. If our team competes virtually, they have committed to provide Azure Cloud credits until our team receives credit from the SCC organizers, and they will also provide a dedicated space in the department for the team to compete.
Our current undergraduate student team consists of Junior (5) and Senior (2) students with majors in Computer Science, Mathematics, Mathematical Statistics, and Politics & International Affairs (half are double-majors), and minors in Mathematics, Japanese, and Neuroscience. Our team will will consist of six students, but we will switch one student if we compete virtually. Two of the students are returning veterans who participated in the previous SC20 SCC, and five are new students. Our students have taken a wide range of relevant prerequisite classes, including Data Structures I and II, Databases, Parallel Computing, GPU Programming, Numerical Linear Algebra, and Machine Learning and code in C/C++, Java, Python, MATLAB, R, CUDA, and SQL.
All team members want to receive a deeper hands-on experience on high performance computing hardware and software than their other classes, develop their problem solving and teamwork skills, and apply those skills to their research projects involving HPC and big data, and broaden their career prospects in areas such as machine learning, artificial intelligence, and data analytics. They also enjoyed their last competing experience or heard from other students how much they enjoyed it.