In this deck, Radio Free HPC Previews the SC18 Student Cluster Competition. "The Student Cluster Competition (SCC) was developed in 2007 to provide an immersive high performance computing experience to undergraduate and high school students. With sponsorship from hardware and software vendor partners, student teams design and build small clusters, learn designated scientific applications, apply optimization techniques for their chosen architectures, and compete in a non-stop, 48-hour challenge at the SC conference to complete a real-world scientific workload, showing off their HPC knowledge for conference attendees and judges. Teams are composed of six students, at least one advisor, and vendor partners. The advisor provides guidance and recommendations, the vendor provides the resources (hardware and software) and the students provide the skill and enthusiasm. Students work with their advisors to craft a proposal that describes the team, the suggested hardware, and their approach to the competition. The SCC committee reviews each proposal and provides comments for all submissions received before the deadline." Watch the video: https://wp.me/p3RLHQ-jgS Learn more: https://sc18.supercomputing.org/experience/studentssc/student-cluster-competition/ Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter

1. 2018 Student Cluster
Competition: RF-HPC

2. 11th Annual Competition
• 14 teams total
• Variety of benchmarks/applications
• Benchmarks: LINPACK

3. Benchmark: HPCG

4. Deep Learning App: Horovod
• Deep learning is a class of machine learning algorithms in which layers
of nonlinear processing units are used for feature extraction and
transformation, with each successive layer taking the output from the
previous layer as input. TensorFlow is one of the popular deep
learning frameworks with parallel training functionality. Horovod acts
as the communication layer of TensorFlow to accelerate the training
process. Documentation and code examples of Horovod are
at: https://github.com/uber/horovod .

5. OpenMC
• OpenMC is an open source Monte Carlo particle transport code.
OpenMC simulates neutrons moving stochastically through an
arbitrarily defined model that represents a real-world experimental
setup. The experiment could be as simple as a sphere of metal or as
complicated as a full-scale nuclear reactor. Modern, portable
input/output file formats are used in OpenMC: XML for input, and
HDF5 for output. High performance parallel algorithms in OpenMC
have demonstrated near-linear scaling to over 100,000 processors on
modern supercomputers. Documentation of OpenMC can be found
at: https://openmc.readthedocs.io/en/stable/ .

6. Reproducibility Challenge
• Once again, students in the cluster competition will be asked to replicate the results of a publication from the
previous year's Supercomputing conference. For this challenge, you will take on the role of reviewing an SC18
paper that contains an Artifact Description appendix to see if its results are replicable.
• For the past three years, SC has promoted the adoption of the Artifact Description (AD) policy endorsed by ACM.
The conference has selected one of the papers from the past edition to become the benchmark for the SC SCC
reproducibility challenge. The competitive selection includes the review of all the past edition SC papers with AD
and the in-person interview of the finalist papers' authors.
• SeisSol
• This year, the SCC committee is proud to announce the winning paper for the reproducibility challenge at this
year’s SCC at SC18: "Extreme scale multi-physics simulations of the tsunamigenic 2004 sumatra megathrust
earthquake". The paper is co-authored by Carsten Uphoff, Sebastian Rettenberger, and Michael Bader from
Technical University of Munich and Elizabeth H. Madden, Thomas Ulrich, Stephanie Wollherr amd Alice-Agnes
Gabriel from Ludwig-Maximilians-Universität München.
• In the paper the authors describe the end-to-end optimization of the simulation code SeisSol
(http://www.seissol.org/) that become necessary to run the extreme size of a high-resolution simulation of the
2004 Sumatra-Andaman earthquake. You will find the code that was used in this paper:
https://github.com/SeisSol/SeisSol/tree/scc18 . Please make sure to take the scc18 branch.

7. Reproducibility Challenge 2
• The challenge will consist of two parts. One part will consist of a short interview with
each team as in the other challenges. The other part will consist of a report describing
your attempt to replicate the results from the paper. The report must be written in
English, using a page size of US Letter, in PDF format, with 1 inch margins, and using a 12
point font size. You will also need to be able to create graphs and tables similar to those
from the paper.
Most importantly, in the report, you will need to explain how you got your results and
compare your results to the results of the authors. Your scores will not depend on
whether your results match the results in the paper. The goal of the report is to state if
you can or cannot replicate the results in the paper. If you cannot replicate the paper's
results, you can still obtain full points by presenting your data and explaining why you
cannot replicate the paper's results.
As a last note, you will only be required to report results for one compute architecture. If
your cluster contains both a CPU and an accelerator, results for either one may be used
for this part of the competition.

8. Mystery Application
At the start of the competition, teams will be given an application and
datasets for a mystery application. Students will be expected to build,
optimize and run this mystery application all at the competition.

9. Power Shutoff Activity
• Some time during the 45 and 1/2 hours of the general competition
the power will be shut-off at least once. The exact timing of the
shutdown(s) are secret and may happen day or night.
• You and your team will need to know how to bring the hardware and
software back from a full unscheduled power outage and how to
resume any workload you were processing at that time. This exercise
is designed to simulate real world events that system staff must
respond to. This activity will allow your team to demonstrate their
systems skills by recovering the system.

10. SC18 Field & Experience
Team
Appearances (ASC,
ISC, SC combined)
Gold
medals
Silver
Medals
Bronze
Medals LINPACK HPCG
Friedrich-Alexander University Erlangen-Nuremberg, Germany
8 1 2
Laney College, United States 0
Monash University, Australia 0
Nanyang Technological University, Singapore (The winning team from
the SC17 Student Cluster Competition) 9 1 1 1
National Tsing Hua University, Taiwan 13 2 1 2 4
Northeastern University, United States 4 0 0 0 0 1
Purdue University, United States 12 1
Telkom University, Indonesia 0
Texas A&M University, United States 1
Tsinghua University, China (The winning team from the ASC18
Student Supercomputer Challenge and the ISC18 Student Cluster
Competition) 15 9 2 2 1
University of Illinois at Urbana-Champaign, United States 2
University of Massachusetts, Boston, United States 0
University of Warsaw/Warsaw University of Technology/Lodz
University of Technology/University of Wroclaw, Poland 3
Wake Forest University, United States 0