TeraGrid 2010 Keynote: The Physics of Black Holes with Cactus

By Michael Schneider

August 11, 2010

Opening a new window on the universe — that’s the promise of gravitational wave astronomy, and its fulfillment presents a scientific computing challenge that might almost be akin to pulling light out of a black hole, if that were possible. Or maybe the more appropriate analogy is water in a desert, where sometimes the solution is cactus.
Make that a capital “C” — as in Cactus, an open, collaborative software framework for numerical relativity that since 1997 has enabled research that underlies more than 200 scientific papers and 30 student theses. That and more than that, in a fast-moving, information-packed presentation, was the topic of Gabrielle Allen’s keynote talk, Tuesday, August 3 at TeraGrid ’10, the fourth annual conference of the TeraGrid, in Pittsburgh, Pa.

Allen is associate professor in Computer Science at Louisiana State University, and a faculty member at LSU’s Center for Computation & Technology. Before moving there in 2003, she led the computer science area of the Max Planck Institute for Gravitational Physics (Albert Einstein Institute) in Potsdam, Germany. At AEI, she was a PI for the European GridLab project, and led the initial development of Cactus.

She began her talk, “Cyberinfrastructure for Numerical Relativity,” by noting that she’s been a TeraGrid user since 2001. “Accurately modeling astrophysical systems that are governed by Einstein’s Equations of General Relativity, such as black holes, stellar core collapse or gamma ray bursts,” she added, “requires the use of cutting-edge computational resources and software.”

Solving the problems of this field of science, Gravitational Wave Physics, depends on interactions between modern theory, observation and computation, and all three aspects, says Allen, are leading to new discoveries. Gravitational waves are one of the startling aspects of Einstein’s predictions from general relativity. Measurements of the decaying orbits of binary pulsars agree with Einstein’s prediction of gravity waves, yet even now these waves haven’t been directly observed.

Two large projects have mounted gravity wave detectors — the U.S. LIGO (Laser Interferometer Gravitational Wave Observatory) project and GEO 600 in Germany — to test Einstein’s theory, but these extremely sensitive instruments need to be precisely tuned and use complex data analysis to recognize the delicate signatures of gravity waves from events in deep space. For this the physicists need numerical simulations.

The numerical problem is finding ways to solve the Einstein equations that govern gravity-wave phenomena. “There are thousands of terms on the right-hand side,” says Allen, “and these equations are very difficult to work with.” The initial challenge has been modeling binary black holes — two black holes in orbit around each other — a relatively “simple” system with relatively few parameters, as a test case for LIGO.

Recent work using TeraGrid resources at multiple sites, a project of an international team that included Allen’s LSU colleague Erik Schnetter, a research professor in the Department of Physics and Astronomy, modeled the binary black hole problem with unprecedented detail. Allen describes this work, featured on the cover of the 2009 TeraGrid Science Highlights publication, as an outcome of what has so far been a 40-year plus effort to model gravity waves from binary black holes, which has only now arrived at numerically generated waveforms. “We still can’t do extreme mass ratios or very fast spins,” she says, “but this has opened the door to modeling more complex scenarios, such as general relativistic hydrodynamics.”

Allen went on to describe the essential elements of cyberinfrastructure needed to move this work forward, and elaborated on the Cactus framework — so-called from its design of a central core (“flesh”) which connects to application modules (“thorns”) through an extensible interface. It’s a modular system, with thorns that are defined by parameters, variables and methods, and the flesh binds it together.

Cactus derived originally, Allen explained, from a mid-90s Black Hole Grand Challenge project, with multiple groups collaborating. “This came out of the vision of Ed Seidel,” she said. Seidel, who recently ended a term as director of NSF’s Office of Cyberinfrastructure, worked during this period at AEI in Germany, and recognized needs — that have been implemented through Cactus — for modularity, for easy code reuse, community sharing and development.

A recent set of Cactus thorns, Allen pointed out, has implemented adaptive mesh-refinement (AMR). Developed by Schnetter, this has allowed many groups to have access to AMR with little code change. “We can scale the AMR up to around 16,000 processors,” noted Allen. Cactus also implements automatic code generation through “Kranc” — a Mathematica tool to generate Cactus thorns from PDEs. “Your turn the Kranc and it spits out complete thorns of Cactus.”

Cactus interfaces with the Einstein Toolkit, a consortium that develops and supports open software for relativistic astrophysics. “Our aim,” said Allen, “is to provide the core computational tools than can enable new science, broaden our community, facilitate interdisciplinary research and take advantage of emerging petascale computers and advanced cyberinfrastructure.” The consortium includes 55 members at 17 sites in nine countries.

Among many challenges to be faced, Allen observed that changes in academic culture are needed to support the model of open collaboration versus competition among research teams. “We need incentives for faculty to encourage postdocs and students to use and contribute to community software.”

“Everything is a challenge,” she added, “in this kind of work. Nothing works as well as you’d like. The TeraGrid has been a big friend of numerical relativity, and has helped us to develop the kind of community we need — especially for students, it has been amazingly helpful. It provides access for students to the hardware we use, and the software and best practices. All these things are crucial.”

The biggest challenge ahead, she added, is how to handle tremendous amounts of data. “Everything is going to be about data very soon. We need to be ready for that. It is changing the world of science. There is a whole sociology of how data is going to be used in academia. We have a big chance to do this properly.”

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