It was 6am, and a team of six students from Department of Computer Science and Technology, Tsinghua, finally breathed a sigh of relief after an arduous 72 hours of competition.
While it might not have been physically challenging in the traditional sense, the nonstop testing, calculating and computer work can still take a huge toll.
Fortunately, it was all worth the sore necks, aching wrists and depleted mental resources as they were announced the winner of the 2020 Student Cluster Competition.
It was the third consecutive year they had won in the same international competition.
In 2007, the US-based International Conference for High Performance Computing, Networking, Storage and Analysis launched the Student Cluster Competition to provide an immersive, high-performance computing experience to undergraduate and high school students around the world.
Due to the COVID-19 pandemic, the 2020 competition took place "in the cloud" in November, attracting 19 teams of 114 students from different countries, including the Massachusetts Institute of Technology in the United States, the University of Warsaw in Poland, Friedrich-Alexander University in Germany, and Singapore's Nanyang Technological University, alongside China's Peking University and Tsinghua University, among others.
Participants were required to design and build virtual "clusters" in the cloud and apply optimization techniques for their chosen cloud configurations to complete a set of benchmark tests and real-world scientific workloads against the clock.
A "cluster" is a collection of high-performance computing devices, linked together to utilize their combined resources to complete complex and high-volume data-based tasks quickly and accurately.
According to Han Wentao, the tutor of Tsinghua’s supercomputing team, the previous on-site competitions where all teams gathered together, bringing their own hardware, lasted 48 hours.
"Each team needed to assemble their own cluster on-site with a maximum power of 3,000 watts. It's like Formula 1, where you need to spend a lot of money on buying the best engines and parts," Han explains.
For the 2020 iteration of the contest, however, the rules were different. All preparations and computing were done in the cloud. Participating teams had a $3,200 initial budget to buy hardware and services online. Unbeknown to the competitors, however, 12 hours before the end of the competition, they would receive a windfall of $500 additional budget.
"This time, all teams were on the same starting line with a limited budget," Han says.
Another challenge in the virtual competition was the time difference. The competition started at 6am in Beijing and the judges, who would be answering questions during the competition, were only online between 10pm and 4am.
Taking up tasks
The teams had to complete a number of tasks, including Linpack, or linear software package, benchmarks.
Linpack is basically using the computer to solve a linear equation with one million unknowns. Because many practical problems can be converted into this equation, so it is fundamental functions that need to be tested.
Another challenge was the Gromacs molecular dynamics application, which is relevant to the COVID-19 pandemic. Molecular dynamics simulations offer accurate approximations of real molecular behavior, which is useful in the different stages of drug development.
Song Zeyu, a member of the team, was tasked with running that application with another teammate.
The 20-year-old spent the first day learning about the topic and started to run the application on the second day of the competition. He and his teammate took turns to sleep so that one of them was always monitoring the application.
"When the competition was held on-site, we got the chance to talk with the other teams, which was a great experience," recalls Zhang Chen, who joined team in 2018 and was the team leader for the 2020 competition.
"Obviously, I have much more responsibility. I need to keep an eye on the progress of all the team members during the competition and make final decisions and some tough choices, including how to assign our resources and budget," says the 21-year-old.
During the competition, she would regularly gather the team together to discuss budgetary constraints and how to best distribute the resources.
"The budget is definitely not enough to finish running all of the application challenges, so we needed to decide how to assign the money," she says.
Zhang didn't get much sleep during the 72-hour competition－as the event wore on, her nights became more restless.
It was not in vain, though, as the team didn't only end up winning the whole thing, but also achieved the highest score in the Linpack benchmark.
Ability to calculate
What supercomputing is trying to achieve is the highest speed of computational power and ideally suited to any subject that requires a massive amount of calculating ability.
Take weather forecasts as an example. To calculate future weather patterns, the map is separated into grid boxes and there are various data points within them that are taken into consideration, including temperature, humidity, wind direction and wind power.
There are two ways of making the forecast more accurate: one way is to make the grid boxes smaller and the other is to calculate with greater levels of iteration, that's when supercomputing comes to the fore, when massive amounts of calculation are required in an increasingly limited time.
Han began tutoring the supercomputing team in 2016. In his opinion, the team aims to be the champion of each competition entered, but is not result-oriented.
“The competition is a good practice for the students, whether for scientific research or solving practical problems in the future. We hope our students can actually learn something from the competition, learn what supercomputing is, and maybe inspire them to pursue a career in supercomputing," Han says.
In order to prepare for each supercomputing competition, Zhang Chen needs to embark on additional study of related subjects to the applications she will be running, allowing her an insight into a varied array of other fields.
"Each time I compete, I gain a little more knowledge about different applications and techniques, so it's a continuous process of learning. The competition also points to the direction I want to take in my future research," Zhang says.
Source: Li Yingxue, China Daily
