A record-breaking twenty student teams plus scores of company representatives, media professionals, staff and student volunteers transformed a formerly empty hall inside the Wuxi Supercomputing Center into a bustling hub of HPC activity, kicking off day one of the 2017 Asia Student Supercomputer Challenge (ASC17) on Monday, April 24, 2017, in Wuxi, China.

As the sun rose higher in the sky over the beautiful Taihu Lake and with the world’s fastest TaihuLight supercomputer under the same roof, the students worked diligently through the day and into the evening to unbox their equipment and build their clusters.

From an initial pool of 230 teams, representing schools from around the globe, these 20 teams earned their spots in the final round. Among them are former champions, such as Huazhong University of Science and Technology, Shanghai Jiao Tong University, and “triple crown” winners Tsinghua University, but for seven of the teams, ASC17 marks their first time as competition finalists. Contest officials are particularly proud of the event’s reach to cultivate young talent.

In the six years since its inception, ASC has developed into the largest student supercomputing competition and is also one with the highest award levels. During the four days of the competition, the 20 teams at ASC17 will race to conduct real-world benchmarking and science workloads as they vie for a total of six prizes worth nearly $35,000.

Inspur provides the teams with a rack and NF5280M4 servers, outfitted with two Intel Xeon E5-2680v4 (2.4Ghz, 14 cores) CPUs. The primary event sponsor also supplies DDR4 memory, SATA storage, Mellanox InfiniBand networking (card, switch and cables), as well an Ethernet switch and cables.

Teams can substitute or add other componentry (except the servers) at their own expense or through sponsorship opportunities. Most of the teams we spoke with were able to forge a relationship with Nvidia, whose GPU gear is now widely used at all three major cluster challenges (at SC, ISC and ASC). We saw mostly P100 cards getting snapped into server trays this morning, but at least two teams had acquired the K40 parts with the hopes that they would offer a more optimal energy profile conducive to staying within the 3,000 watt contest power threshold. On everyone’s mind was how much of the available compute power they would be able to leverage without exceeding the power budget.

Days one and two of the competition are devoted to cluster set up and testing. The team-built clusters are used for an application set that includes the High Performance Linpack (HPL), the High Performance Conjugate Gradient (HPCG), the mystery application (to be announced Wednesday), the genome analysis code Falcon and a traffic prediction problem to be solved with the Baidu deep learning framework, Paddle Paddle. The teams report different levels of experience with Paddle Paddle and with scaling to multiple GPUs, a skill that will be critical for achieving optimum performance.

Two other platforms will be used in the competition: the homegrown TaihuLight and a Knights Landing (KNL) machine with the 64-core Intel Xeon Phi-7210 1.3Ghz CPU. Students will use TaihuLight to run and optimize the China-developed numerical wave modeler MASNUM application. The Inspur NF6248 KNL server (there’s a 20-node rack of these inside the contest hall) will be used for the molecular dynamics simulator LAMMPS. The 3,000 watt power limit does not apply for these workloads.

One of the most exciting parts of this year’s competition is the inclusion of the Sunway TaihuLight machine, which teams have have had access to since January. Each team will be allowed to use at most 64 SW CPUs with 256 CGs (for more details on the machine, see “China Debuts 93-Petaflops Sunway”). According to the rules: “Every team is allowed to design and implement proper parallel algorithm optimization and many-core optimization for the MASNUM source code. Each team needs to pass the correctness checking of each workload, and the goal is to achieve the shortest runtime of each workload.”

ASC17 is set up so teams can receive a total of 100 points: 90 points for performance optimizations and 10 points for the presentation that they deliver to the judges after the conclusion of the testing.

Rising to the AI Challenge

The addition of the Paddle Paddle framework continues the contest’s focus on AI and deep learning that was begun last year with the incorporation of a deep neural network program under the e-Prize category.

Wang Endong, founder of the ASC challenge, academician of the Chinese Academy of Engineering and chief scientist at Inspur, believes that with the convergence of HPC, big data and cloud computing, intelligent computing as represented by artificial intelligence will become the most important and significant component for the coming computing industry, bringing new challenges in computing technologies.

The AI thread has also been woven into the HPC Connection Workshop, which will be held in Wuxi on Thursday. The theme for the 15^th HPC Connection Workshop is machine intelligence and supercomputing. The impressive lineup of speakers includes Jack Dongarra (ASC Advisory Committee Chair, University of Tennessee, Oak Ridge National Laboratory), Depei Qian (professor, Beihang University, Sun Yat-sen University; director of the Key Project on HPC, National High-Tech R&D program); Simon See (chief solution architect, Nvidia AI Technology Center and Solution Architecture and Engineering), and Haohuan Fu (deputy director, National Supercomputing Center in Wuxi, Associate Professor, Tsinghua University).

The ASC17 winners will be announced at an awards ceremony Friday afternoon.

The 20 ASC17 Teams (asterisk indicates first-time finalist):

Tsinghua University

Beihang University

Sun Yat-sen University

Shanghai Jiao Tong University

Hong Kong Baptist University

Southeast University*

Northwestern Polytechnical University

Taiyuan University of Technology

Dalian University of Technology

The PLA Information Engineering University*

Ocean University of China*

Weifang University*

University of Erlangen-Nuremberg*

National Tsing Hua University

Saint Petersburg State University

Ural Federal University

University of Miskolc

University of Warsaw*

Huazhong University of Science and Technology

Zhengzhou University*