The Importance of Team Science at XSEDE15

By Faith Singer-Villalobos, Communications Manager, Texas Advanced Computing Center

August 7, 2015

“I’m continuously inspired by her passion, her commitment and her innovative approaches for advancing research, education and the recruitment and retention for a larger and more diverse community of practitioners,” said Scott Lathrop, XSEDE director of Education and Outreach, as he introduced Dr. Ann Quiroz Gates to the podium at the 4th annual XSEDE15 conference.

First and foremost, Dr. Gates is a professor and chair of the Computer Science Department at The University of Texas at El Paso (UTEP). Importantly, she also directs the NSF-funded Cyber-ShARE Center of Excellence established in 2007. The mission of Cyber-ShARE is as follows:

To advance and integrate cyber-enhanced, collaborative, and interdisciplinary education and research through technologies that support the acquisition, exchange, analysis, integration of data, information and knowledge to solve complex problems.

Among her many other accomplishments, Dr. Gates leads the Computing Alliance for Hispanic Serving Institutions, which focuses on the recruitment, retention and advancement of Hispanics in computing; is a founding member of the National Center for Women in Information Technology; won the 2015 A. Nico Habermann Award and the 2010 Anita Borg award for Social Impact; and she was named by Hispanic Business Magazine as one of the Top 100 Influential Hispanics in 2006.

Her passions are clearly collaborative research and diversity.

“In the last two decades, there has been a surge in investments in large scale team science projects,” Gates said. “The term team science denotes a team of diverse members who conduct research in an interdisciplinary manner. The term convergent research is also often used in this context. The success of working in large, diverse teams are influenced by a variety of factors that impact efficiency, productivity and overall effectiveness.”

In her plenary talk at the XSEDE15 conference, Gates discussed what some of the experts are researching in this exciting and growing field. Her project, Cyber-ShARE, is an example of team science (aka collaborative science). “Cyber-ShARE is an interdisciplinary team across computer science, geological and environmental science. We support interdisciplinary research and collaborations across campus (at UTEP) that broaden interdisciplinary research.”

More and more research is being conducted on the importance of team science. When talking about team science Dr. Gates refers to the National Research Council’s definition of bringing together small teams and larger groups of diverse members to conduct research in an interdependent manner. There are a number of approaches in which team science can be done that can work within and across disciplines; there are also a number of terms to describe what level a team can be at in this continuum, including:

  • Transdisciplinary: integrate and transcend disciplinary approaches to generate fundamentally new conceptual frameworks, theories, models and applications
  • Interdisciplinary: integrate information, data, techniques, tools, perspectives, concepts and theories across disciplines, working jointly
  • Multidisciplinary: incorporates two or more disciplines working independently

“A team science approach is needed because of the complexity of the scientific and social challenges we’re facing in this world,” Gates said. “Addressing complex problems requires contributions from different disciplines, communities and professions.”

There is evidence in the form of publications and patents that large, diverse team efforts result in greater productivity, reach, innovation and scientific impact. “Certainly this arises from the ability of the members to draw on each other’s diverse expertise. Diversity influences how decisions are made and can positively impact the group’s effectiveness.”

However, diversity also brings challenges. Gates broke them down into three major groups: 1) Knowledge negotiation and communication; 2) Shared resources; and 3) Team effectiveness.

“Problems exist around knowledge negotiation and communication such as lack of a common vocabulary and inability to communicate about research goals and integrate the solutions around the research problem. Also, oftentimes the teams are geographically dispersed so shared resources or lack thereof must be considered. In addition, being able to identify expertise and organizational boundaries brings about challenges. Misalignment of goals can also lead to conflict. Disciplinary boundaries evolve reflecting the changing nature of goals over time,” Gates said.

So, how do you work in a group with a large number of team members?

It requires communication, coordination and high positive interdependence — members working together to accomplish a shared task. As a result, there has to be strong leadership that can assign and facilitate interdependent tasks that integrate the unique talents of the individual members to accomplish shared goals.

The NSF Extreme Science and Engineering Discovery Environment (XSEDE) project is a great example of team science. The project supports the ability of a very large team dispersed around the world to use advanced digital resources and services that are critical to the success of science.

Gates points to the XSEDE Industry Challenge program as an example.

The XSEDE Industry Challenge program brings together researchers, scientists and engineers from academia and industry with interdisciplinary backgrounds, deep knowledge in disciplines, and technical and professional skills. The program is intended to establish a new model for cooperative and collaborative research between industry and academia that transcends traditional disciplinary boundaries.

XSEDE believes with inter-industry research there is potential for future economic and societal benefit within both the industrial and academic worlds.

Gates agrees with XSEDE’s view and notes the need for more support of organizations such as XSEDE that have invested in promoting virtual, interdisciplinary communities and projects.

Team science is crucial for the success of projects that involve students, particularly those from underrepresented groups, who wish to become researchers or computer scientists. The Affinity Research Group (ARG) Model identifies students who have the capability but maybe not the competence to be involved in research. The model focuses on developing the social and team building skills needed to be successful researchers and encompasses many of the best practices recommended by experts in team science.

“The premise here is to change the culture by preparing students to effectively work in teams. Students are our future workforce — this work has been published in the Journal of Engineering Education.”

The essential elements of the ARG model are as follows:

  • Establish core purpose
  • Structure positive interdependence
  • Practice promotive interaction
  • Teach professional skills
  • Ensure individual accountability
  • Reflect on how well or poorly the group performs

“You have to work on teaching the skills,” Gates explained. “You can’t assume that students know what they need to know to work effectively. Members of a team must know what their individual role is and how it maps back to the bigger goals and sub-goals.”

In essence, to learn is to become a member of a practicing community imparting tools, language, knowledge and skills and to develop a deep commitment to the work and each other’s success. “Learning takes place in meaningful and authentic activity,” according to Gates. “The work of each individual makes a local contribution as well as a global contribution. Expert participants serve as models for professional practice for novices imparting the community’s values, tools, language and knowledge and skills through the everyday work and interaction. They develop a deep commitment to the work and each other’s development and success.”

Team science is about how the national science community can become more inclusive in what it does, and there is a lot of work being done in the science of team science. Gates concluded by emphasizing that the role of diversity in team science is extremely important and extends to age, gender, ethnicity and culture.

A PDF on “Enhancing the Effectiveness of Team Science” is available for download at http://www.nap.edu/catalog/19007/enhancing-the-effectiveness-of-team-science.

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!

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

March 18, 2024

Nvidia's latest and fastest GPU, code-named Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from its predecessors, including the red-hot H100 and A100 GPUs. Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. While Nvidia may not spring to mind when thinking of the quant Read more…

2024 Winter Classic: Meet the HPE Mentors

March 18, 2024

The latest installment of the 2024 Winter Classic Studio Update Show features our interview with the HPE mentor team who introduced our student teams to the joys (and potential sorrows) of the HPL (LINPACK) and accompany Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the field was normalized for boys in 1969 when the Apollo 11 missi Read more…

Apple Buys DarwinAI Deepening its AI Push According to Report

March 14, 2024

Apple has purchased Canadian AI startup DarwinAI according to a Bloomberg report today. Apparently the deal was done early this year but still hasn’t been publicly announced according to the report. Apple is preparing Read more…

Survey of Rapid Training Methods for Neural Networks

March 14, 2024

Artificial neural networks are computing systems with interconnected layers that process and learn from data. During training, neural networks utilize optimization algorithms to iteratively refine their parameters until Read more…

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

March 18, 2024

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

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the fi Read more…

Survey of Rapid Training Methods for Neural Networks

March 14, 2024

Artificial neural networks are computing systems with interconnected layers that process and learn from data. During training, neural networks utilize optimizat Read more…

PASQAL Issues Roadmap to 10,000 Qubits in 2026 and Fault Tolerance in 2028

March 13, 2024

Paris-based PASQAL, a developer of neutral atom-based quantum computers, yesterday issued a roadmap for delivering systems with 10,000 physical qubits in 2026 a Read more…

India Is an AI Powerhouse Waiting to Happen, but Challenges Await

March 12, 2024

The Indian government is pushing full speed ahead to make the country an attractive technology base, especially in the hot fields of AI and semiconductors, but Read more…

Charles Tahan Exits National Quantum Coordination Office

March 12, 2024

(March 1, 2024) My first official day at the White House Office of Science and Technology Policy (OSTP) was June 15, 2020, during the depths of the COVID-19 loc Read more…

AI Bias In the Spotlight On International Women’s Day

March 11, 2024

What impact does AI bias have on women and girls? What can people do to increase female participation in the AI field? These are some of the questions the tech Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. 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…

Analyst Panel Says Take the Quantum Computing Plunge Now…

November 27, 2023

Should you start exploring quantum computing? Yes, said a panel of analysts convened at Tabor Communications HPC and AI on Wall Street conference earlier this y 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…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a 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…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia 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…

Leading Solution Providers

Contributors

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Training of 1-Trillion Parameter Scientific AI Begins

November 13, 2023

A US national lab has started training a massive AI brain that could ultimately become the must-have computing resource for scientific researchers. Argonne N Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t 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…

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…

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…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire