ASC16 Kicks Off in Wuhan, China: 16 Teams, $40k in Prizes

By Tiffany Trader

April 18, 2016

The fifth annual Asia Student Supercomputer Challenge (ASC16) got off to an exciting start this morning at the Huazhong University of Science and Technology (HUST) in Wuhan, the capital of Hubei province, China. From an initial pool of 175 teams, representing 148 universities across six continents, 16 teams advanced through the preliminary rounds into the final round, including returning champion and “triple crown” team, Tsinghua University, and the only US team to make it into the competition, the Boston Green Team.

With each iteration of the Asian Student Competition and its “sister” events at SC and ISC, the roster of competitors becomes more formidable. Many of the teams have accumulated a number of wins already, but there are new entrants too, including Hong Kong Baptist University and Dalian University of Technology, which have earned their place in this final based on their high rankings  in the preliminary rounds. There’s also a steady influx of new students, as the competition torch gets passed on.

ASC16 Boston Green Team
Boston Green Team at ASC16

The teams that HPCwire spoke with who have been here before are aiming to put that experience to their advantage. Students from the Boston Green Team (team includes students from Boston University and Northeastern) gave a lot of consideration to the cluster design process. Some of the teams brought in Nvidia Tesla K80 GPUs at their own expense, but the Boston team opted to outfit their Inspur NF5280M4 server with the standard parts that Inspur and Intel supplied, including the Xeon E5-2650 v3 processor and the Intel Xeon Phi-31S1 coprocessor cards.

We also spoke with returning champs from Tsinghua University who had a somewhat different point of view. The team leader said that because the teams will all be using similar hardware with the same CPU, they will really be forced to focus on application testing and development. “There is not that large a difference in architecture, so I think we have to beat them by software and that’s a really big challenge.”

ASC16 Tsinghua University team
Tsinghua University team at ASC16

The purpose of the contest is for each team to design its cluster for the best application performance within the power consumption mandates. Per the contest regulations, power consumption must be kept under 3000W or the result of a given task becomes invalid (except for the e-Prize, which we’ll get to in a moment). While teams can build larger clusters — and indeed some teams on the contest floor have ten nodes, the hard power limit constrains how many of those nodes can be harnessed.

Boston Green Team members Winston Chen and John Smith pointed out that at five standard nodes (with two Xeon CPUs and a Phi coprocessor) that is right at the limit for 3,000 watts. Last year at ASC15, the team had an eight node straight-CPU cluster and it hit 3,000 watts. This year, they have six Phi-accelerated nodes — five to run their workloads and a spare.

In the five 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 16 teams at ASC16 will race to conduct real-world benchmarking and science workloads as they vie for a total of six prizes worth nearly $40,000.

The application set includes HPL, HPCG, MASNUM, Abinit, DNN and a mystery application; students also must deliver and are evaluated on a team presentation. The ASC program committee is dedicated to making the program as “life-like” as possible. “ASC provides a learning platform for students to get hands-on experience through the use of high performance computers,” observes Professor Pak-Chung Ching, Chinese University of Hong Kong. “But training supercomputing talents is more than that…they should be trained to understand a complex computational problem, break it down and then use computers to solve different types of problems from a professional perspective. ASC provides a platform for students to participate in practical projects as well as an opportunity to share experience and gain knowledge.”

The Applications

ASC16 Zhejiang University with Tesla K80 800x
Zhejiang University team with Tesla K80 GPU at ASC16

Students will be tasked with running two benchmarking applications. The High Performance LINPACK (HPL) benchmark — currently used to rank the TOP500 computing systems — plus the HPCG High Performance Conjugate Gradients (HPCG), an emerging international standard that exercises computational and data access patterns that are representative of a broad range of modern applications. The authors of the HPCG embrace both HPL and HPCG as bookends that enable application teams to assess the full balance of a system, including processor performance, memory capacity, memory bandwidth, and interconnection capability.

Teams will conduct three science applications: a surface wave numerical model MASNUM; a material simulation software ABINIT; and a mystery application, which will be announced on the day of the final.

e-Prize for Deep Learning Prowess

Even if teams have opted to forego using Phis in their cluster configuration, all teams get the chance to access the Phi MIC (Many Integrated Core) architecture when they compete for this year’s e-Prize, which requires that students set up and deploy a deep neural network (DNN). After developing the DNN on a Phi platform, teams will optimize the DNN algorithm using a remote login to Phi-based Tianhe-2 nodes.

The cluster has eight Phi nodes, each comprising two CPUs (Intel Xeon E5-2692 v2, 12 cores, 2.20GHz) and three Xeon Phi cards (Intel Xeon Phi 31S1P, 57 cores, 1.1GHz, 8GB memory). The Tianhe-2 network employs a custom high speed interconnect system with a bandwidth between nodes of 160 Gbps. There is no power consumption limit for this part of the contest.

The students will apply a data set comprising more than 100,000 pieces of speech data to the DNN with the objective of training the machine to be able to recognize speech as efficiently and effectively as the human brain.

The DNN performance optimization is given the highest weight in the contest, 25 percent of the total score. The ASC committee recognizes DNN as “one of the most important deep learning algorithms in artificial intelligence and the most popular cutting-edge emerging field in high-performance computing.” The organizers cite the recent “Man vs. Machine Battle” between AlphaGo and Lee Sedol for generating widespread interest in deep learning.

After the performance testing is concluded, the teams will present the results of their work to a panel of expert judges. The team presentation is worth ten percent of their final score. The winning teams will be announced during an awards ceremony on Friday, April 22.

HPC Workshop

The event will also be host to the 12th HPC Connection Workshop on April 21, 2016. The workshop features a roster of prominent HPC experts from around the world. Jack Dongarra, University of Tennessee professor and founder of the HPL benchmark, will discuss the current trends and future challenges in the HPC field. Depei Qian, chief leader of the “HPC and Core Software” Project in the China 863 Program, will share the vision of supercomputing mapped in China’s 2016-2020 Five-Year Plan. Yutong Lu, professor at National University of Defense Technology and deputy chief designer on the Tianhe-2 project, will discuss the convergence of big data and HPC on the Tianhe-2 supercomputer. The full listing of invited talks can be viewed here.

ASC16 entrance signage 1000x
ASC16 Welcome Sign

 

ASC16 scoreboard
ASC16 scoreboard awaits results
Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

Atos Outlines Plans to Get Acquired, and a Path Forward

May 21, 2024

Atos – via its subsidiary Eviden – is the second major supercomputer maker outside of HPE, while others have largely dropped out. The lack of integrators and Atos' financial turmoil have the HPC market worried. If Read more…

Core42 Is Building Its 172 Million-core AI Supercomputer in Texas

May 20, 2024

UAE-based Core42 is building an AI supercomputer with 172 million cores which will become operational later this year. The system, Condor Galaxy 3, was announced earlier this year and will have 192 nodes with Cerebras Read more…

Google Announces Sixth-generation AI Chip, a TPU Called Trillium

May 17, 2024

On Tuesday May 14th, Google announced its sixth-generation TPU (tensor processing unit) called Trillium.  The chip, essentially a TPU v6, is the company's latest weapon in the AI battle with GPU maker Nvidia and clou Read more…

ISC 2024 Student Cluster Competition

May 16, 2024

The 2024 ISC 2024 competition welcomed 19 virtual (remote) and eight in-person teams. The in-person teams participated in the conference venue and, while the virtual teams competed using the Bridges-2 supercomputers at t Read more…

Grace Hopper Gets Busy with Science 

May 16, 2024

Nvidia’s new Grace Hopper Superchip (GH200) processor has landed in nine new worldwide systems. The GH200 is a recently announced chip from Nvidia that eliminates the PCI bus from the CPU/GPU communications pathway.  Read more…

Europe’s Race towards Quantum-HPC Integration and Quantum Advantage

May 16, 2024

What an interesting panel, Quantum Advantage — Where are We and What is Needed? While the panelists looked slightly weary — their’s was, after all, one of the last panels at ISC 2024 — the discussion was fascinat Read more…

Atos Outlines Plans to Get Acquired, and a Path Forward

May 21, 2024

Atos – via its subsidiary Eviden – is the second major supercomputer maker outside of HPE, while others have largely dropped out. The lack of integrators Read more…

Google Announces Sixth-generation AI Chip, a TPU Called Trillium

May 17, 2024

On Tuesday May 14th, Google announced its sixth-generation TPU (tensor processing unit) called Trillium.  The chip, essentially a TPU v6, is the company's l Read more…

Europe’s Race towards Quantum-HPC Integration and Quantum Advantage

May 16, 2024

What an interesting panel, Quantum Advantage — Where are We and What is Needed? While the panelists looked slightly weary — their’s was, after all, one of Read more…

The Future of AI in Science

May 15, 2024

AI is one of the most transformative and valuable scientific tools ever developed. By harnessing vast amounts of data and computational power, AI systems can un Read more…

Some Reasons Why Aurora Didn’t Take First Place in the Top500 List

May 15, 2024

The makers of the Aurora supercomputer, which is housed at the Argonne National Laboratory, gave some reasons why the system didn't make the top spot on the Top Read more…

ISC 2024 Keynote: High-precision Computing Will Be a Foundation for AI Models

May 15, 2024

Some scientific computing applications cannot sacrifice accuracy and will always require high-precision computing. Therefore, conventional high-performance c Read more…

Shutterstock 493860193

Linux Foundation Announces the Launch of the High-Performance Software Foundation

May 14, 2024

The Linux Foundation, the nonprofit organization enabling mass innovation through open source, is excited to announce the launch of the High-Performance Softw Read more…

ISC 2024: Hyperion Research Predicts HPC Market Rebound after Flat 2023

May 13, 2024

First, the top line: the overall HPC market was flat in 2023 at roughly $37 billion, bogged down by supply chain issues and slowed acceptance of some larger sys Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Some Reasons Why Aurora Didn’t Take First Place in the Top500 List

May 15, 2024

The makers of the Aurora supercomputer, which is housed at the Argonne National Laboratory, gave some reasons why the system didn't make the top spot on the Top Read more…

Leading Solution Providers

Contributors

Eyes on the Quantum Prize – D-Wave Says its Time is Now

January 30, 2024

Early quantum computing pioneer D-Wave again asserted – that at least for D-Wave – the commercial quantum era has begun. Speaking at its first in-person Ana Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

The GenAI Datacenter Squeeze Is Here

February 1, 2024

The immediate effect of the GenAI GPU Squeeze was to reduce availability, either direct purchase or cloud access, increase cost, and push demand through the roof. A secondary issue has been developing over the last several years. Even though your organization secured several racks... Read more…

Intel Plans Falcon Shores 2 GPU Supercomputing Chip for 2026  

August 8, 2023

Intel is planning to onboard a new version of the Falcon Shores chip in 2026, which is code-named Falcon Shores 2. The new product was announced by CEO Pat Gel Read more…

The NASA Black Hole Plunge

May 7, 2024

We have all thought about it. No one has done it, but now, thanks to HPC, we see what it looks like. Hold on to your feet because NASA has released videos of wh Read more…

GenAI Having Major Impact on Data Culture, Survey Says

February 21, 2024

While 2023 was the year of GenAI, the adoption rates for GenAI did not match expectations. Most organizations are continuing to invest in GenAI but are yet to Read more…

How the Chip Industry is Helping a Battery Company

May 8, 2024

Chip companies, once seen as engineering pure plays, are now at the center of geopolitical intrigue. Chip manufacturing firms, especially TSMC and Intel, have b Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire