XSEDE14 Workshop Wrestles with Reproducibility

By Faith Singer-Villalobos

August 19, 2014

Imagine that you are trying to create a new sauce for a special dish, or the perfect adhesive for a new aircraft, or you’re flying a helicopter looking for victims of a natural disaster — and you succeed at each of these. This is wonderful news for your dinner guests, or the company that will use the new adhesive, and especially for the victims of the natural disaster. But the question is — Could you do it again and get the same results? Or, did you just get lucky the first time?

At the XSEDE14 conference in Atlanta, a roomful of computational veterans from inside and outside the NSF Extreme Science and Engineering Discovery Environment (XSEDE) participated in a full-day workshop on the topic of reproducibility, and clearly, there is a lot at stake.

“There is a growing awareness in the computational research community that this question of ‘can we do it again’ is becoming important for us in new ways, and the stakes are high — computational research is helping to save lives, answering policy questions, and making an impact on the world,” said Doug James, an HPC researcher at the Texas Advanced Computing Center, in his opening remarks for the workshop.

People have been thinking about reproducibility for a long time – it is one thing to reproduce a small scale lab experiment, or a computation on your desktop, but it is an entirely different matter to reproduce something that the Hubble Space Telescope did over five years at the cost of hundreds of millions of dollars, for example.

So, what is reproducibility? One working definition might resemble this: the ability to repeat an experiment to the degree necessary to assess the correctness and importance of the results. Practices that promote reproducibility include anything that makes a researcher more organized, provides a better audit trail, allows a researcher to track source code, and to know what data sources were used.

Victoria Stodden of Columbia University, who led a roundtable on the topic of reproducibility in 2009 and an ICERM workshop on Reproducibility in Computational and Experimental Mathematics in 2012, gave the keynote address at the XSEDE14 workshop. She raised the issue of a credibility crisis.

“Reproducibility has hit the popular press over the last several months,” Stodden said, citing recent coverage by The Economist (October 2013) and editorials in Nature and Science. Issues around the importance of reproducibility were catalyzed by the clinical trials scandal at Duke University in computational genomics where mistakes in the research were uncovered in 2010 in The Cancer Letter.

“This really goes to the heart of how important reproducibility issues are, and how we need to reconstruct the pipeline of thinking, reasoning and observation that a scientist does, but for the computational aspects, too, where many of these decisions are being manifest.”

Stodden also touched on separate discussions going on regarding different aspects of reproducibility such as statistical reproducibility, which questions the research decisions about the statistics and data analysis, and empirical reproducibility, which focuses on the reporting standards for the physical experiment, but does not focus on the computational steps.

Everyone in the room agreed that computational research is now in a position where complexity and mission criticality take on new import, and the community needs to develop confidence in the results of that research. But what should our priorities be? Training? Better tools? New steps in proposals and submissions?

NCSA Director Ed Seidel shared his view that there are three levels where things have to happen to get momentum moving in right direction: 1) campus level; 2) national level; and 3) publisher level.

Seidel said that local campuses have to think about how they can begin to support local data services, not just repositories, so there is a local structure. “This is a policy issue that vice chancellors for research and provosts need to take seriously…and there are organizations in place like Internet2 and Educause that span the research universities across the country that can help,” Seidel said. “It’s important to frame it not just as data but more around reproducibility; scope the problem beyond data and the data infrastructure.”

In addition, Seidel cited the XSEDE initiative as being a good organization for aiding the reproducibility process. XSEDE was instrumental in starting the National Data Service Consortium, aimed at organizing a number of individual efforts for data services around tools to create data collections to get Digital Object Identifiers or ‘DOIs’ associated with them and to provide linking services to publishers. While typically thought of as pointers to data collections, DOIs can also attach to code. This is a crucial part of reproducibility.

Professional societies and journals can play a part as well. Many are starting to require links to the data referenced in a publication. But reproducible practices must start in the research group.

Victoria Stodden, Assistant Professor, Department of Statistics, Columbia University and Lorena Barba, Assistant Professor, California Institute of Technology
Victoria Stodden, Assistant Professor, Department of Statistics, Columbia University and Lorena Barba, Assistant Professor, California Institute of Technology

Lorena Barba of George Washington University and a leading advocate of reproducible science said, “Conducting research reproducibly doesn’t mean someone else will reproduce the results, but that you are doing it as if someone would do this. By providing full documentation, access to input data and source code, the community will have confidence in your results and will label them as reproducible even if they are, in fact, not reproduced.”

Many other people added to the conversation including Mark Fahey of the National Institute of Computational Sciences. According to Fahey, the centers need to step up and take some responsibility for providing documentation about how users build and run their codes. Fahey said, “Centers can automatically collect information for each code built and each run of the code, and this information can be made available back to the researcher for publications if desired. There are already two prototypes (ALTD and Lariat) at a variety of computing centers around the world that collect a good portion of this information, and a new improved infrastructure is in development called XALT funded by NSF.”

Recommendations

At the outset of the workshop, the group committed to a key deliverable: recommendations in the form of priorities and initiatives for organizations and communities.

“It’s been implicit that ‘Of course, this is what people do, system administrators and researchers check to ensure that codes gets the same results after systems upgrades and when porting to new platforms’ but reproducibility has never been a formal enterprise,” said Nancy Wilkins-Diehr of the San Diego Supercomputer Center, who summarized the workshop and helped facilitate suggestions for moving forward.

“This is a good time to do this. Computational science is a respected contributor of the scientific knowledge base. Important decisions are now based on simulation. While this is gratifying, it has very real implications for our responsibilities as well,” she said.

The participants intend to move forward with humility, however. “The vision for the recommendations is to honor the reality of a diverse set of viewpoints and include ideas that might be outside of the box,” James concluded. Everyone agrees that there is a need to promote confidence-building tools and methodologies that do not adversely affect performance.

Recommendations will be ready in the September 2014 timeframe — please refer to xsede.org/reproducibility to read them. In addition, you can send comments and suggestions to [email protected]. The Help Desk will send any and all inquiries to the XSEDE team working on this initiative.

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