HAL, Summit and the Songs of Black Holes

By Oliver Peckham

October 6, 2020

The idea of gravitational waves rippling through the fabric of spacetime had been proposed for nearly a century before lightless waves from a collision between two black holes finally appeared on detectors at the Laser Interferometer Gravitational-Wave Observatory (LIGO) in 2015. Since then, the astrophysics community has been racing to identify more gravitational waves, better understand them and use the resulting data to make inferences about other elements of the universe. Now, a team from the National Center for Supercomputing Applications (NCSA) is using supercomputers to train neural networks to understand gravitational waves at a fraction of the computational cost.

At NCSA, Dr. Eliu Huerta leads the Gravity Group and the Center for Artificial Intelligence Innovation. Huerta and his colleagues have spent the last several years using innovative techniques to process the massive amount of data that is produced by each of LIGO’s fifty-plus gravitational wave observations since 2015.

The songs of black holes

“We have been exploring the use of AI to study black hole noises,” Huerta said in an interview with HPCwire. “You can think of these as songs or music that are very contaminated by noise. The question that we have now is: … what can we learn from these signals? One of the big things is where they come from – were they originated by the explosion of a star … or are these black holes formed by mergers with other black holes? And one way to figure this out is by measuring how fast they rotate.”

Scientific visualization of the collision of two black holes, numerically simulated by the open source, numerical relativity, community software, the Einstein Toolkit. Video courtesy of Roland Haas and Eliu Huerta.

“This is a computational challenge, to study this parameter,” he continued. “You … need a ton of waveforms to describe different scenarios, like ‘the two black holes have the same mass,’ ‘one is heavier than the other,’ ‘one is rotating faster than the other,’ et cetera. So you need a lot of different modal signals to study this type of scenario. Now, using traditional approaches, this is very computationally intensive. So we started a program in NCSA where we combine AI and high-performance computing for an accelerated type of analysis.”

Since 2017, Huerta’s team had been suggesting that neural networks were ideal for gravitational wave reconstruction due to their scalability and high dimensional parameter space. With the advent of GPU-accelerated computing, Huerta said, “it was a great opportunity to show that our claims were true.”

Testing the limits of scalability

Setting out to train a neural network to determine the properties of merging black holes, the team began their work on HAL, an in-house NCSA cluster with 16 IBM nodes, each equipped with two IBM Power9 CPUs, 256 GB of memory and four Nvidia V100 GPUs. Huerta estimates that the team spent “thousands” of node hours on HAL, eventually scaling their implementation to all 64 of the cluster’s GPUs and training the model over the course of 12 hours.

The Summit supercomputer.

Then, the team took a step up – to Summit, the most powerful supercomputer in the U.S. Summit’s 4,608 IBM nodes each host two IBM Power9 CPUs and six Nvidia Volta GPUs, delivering 148.6 Linpack petaflops of computing power. Receiving around 10,000 node hours of time on Summit through a Director’s Discretionary allocation from Oak Ridge National Laboratory (ORNL), the team began scaling up their work on the massive supercomputer – first on 128 nodes, then on 256 nodes.

“Using over 1,500 GPUs, we finished the training of these neural networks in about one hour,” Huerta said. “Why is this exciting, you may think? Number one: we show that we can effectively use large-scale systems that are tailored for AI research.” Further, he explained, “the models we are proposing are no longer naive models where you just propose an architecture and hope for the best; we now encode domain knowledge into the architecture of the neural nets and how we train them – this is very unique. And on top of that, we are able to constrain how fast the two black holes rotate in a way that no other algorithm can achieve right now.”

The team also demonstrated strong scaling up to 1,024 nodes – which, on Summit, equates to over 6,000 GPUs. Huerta contrasted the workflows: training a neural net across a single hour on Summit, then processing thousands of signals per second using the trained model – versus processing “just a handful” of signals per second with existing algorithms. 

“We accomplished this because our colleagues at Oak Ridge, who are collaborating with IBM and Nvidia experts, were willing to help us set up everything in the machine,” Huerta said. 

The team at ORNL also recognized the suitability of Summit for Huerta’s work. “Summit’s leadership-class capabilities and AI-friendly architecture were ideal for the team to grow and accelerate the exploration,” said Arjun Shankar, leader of the Advanced Data and Workflow Group at the Oak Ridge Leadership Computing Facility (OLCF), in an interview with ORNL’s Katie Bethea.

What’s next

While all of the team’s 10,000 node hours on Summit have been used, Huerta hopes to return to the machine soon. “The next step is to go again and play this game,” he said, “but now including all these additional corrections to the shape of the waveforms.” These waveforms, he explained, were too computationally intensive to include in the initial round of training on Summit, but when added, will increase the dimensionality of the neural net. The neural net is also updated and improved every few hours with new observations from LIGO, which are incorporated via transfer learning without necessitating a full-fledged retraining of the model.

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!

Intel’s Silicon Brain System a Blueprint for Future AI Computing Architectures

April 24, 2024

Intel is releasing a whole arsenal of AI chips and systems hoping something will stick in the market. Its latest entry is a neuromorphic system called Hala Point. The system includes Intel's research chip called Loihi 2, Read more…

Anders Dam Jensen on HPC Sovereignty, Sustainability, and JU Progress

April 23, 2024

The recent 2024 EuroHPC Summit meeting took place in Antwerp, with attendance substantially up since 2023 to 750 participants. HPCwire asked Intersect360 Research senior analyst Steve Conway, who closely tracks HPC, AI, Read more…

AI Saves the Planet this Earth Day

April 22, 2024

Earth Day was originally conceived as a day of reflection. Our planet’s life-sustaining properties are unlike any other celestial body that we’ve observed, and this day of contemplation is meant to provide all of us Read more…

Intel Announces Hala Point – World’s Largest Neuromorphic System for Sustainable AI

April 22, 2024

As we find ourselves on the brink of a technological revolution, the need for efficient and sustainable computing solutions has never been more critical.  A computer system that can mimic the way humans process and s Read more…

Empowering High-Performance Computing for Artificial Intelligence

April 19, 2024

Artificial intelligence (AI) presents some of the most challenging demands in information technology, especially concerning computing power and data movement. As a result of these challenges, high-performance computing Read more…

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that have occurred about once a decade. With this in mind, the ISC Read more…

Intel’s Silicon Brain System a Blueprint for Future AI Computing Architectures

April 24, 2024

Intel is releasing a whole arsenal of AI chips and systems hoping something will stick in the market. Its latest entry is a neuromorphic system called Hala Poin Read more…

Anders Dam Jensen on HPC Sovereignty, Sustainability, and JU Progress

April 23, 2024

The recent 2024 EuroHPC Summit meeting took place in Antwerp, with attendance substantially up since 2023 to 750 participants. HPCwire asked Intersect360 Resear Read more…

AI Saves the Planet this Earth Day

April 22, 2024

Earth Day was originally conceived as a day of reflection. Our planet’s life-sustaining properties are unlike any other celestial body that we’ve observed, Read more…

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that ha Read more…

Software Specialist Horizon Quantum to Build First-of-a-Kind Hardware Testbed

April 18, 2024

Horizon Quantum Computing, a Singapore-based quantum software start-up, announced today it would build its own testbed of quantum computers, starting with use o Read more…

MLCommons Launches New AI Safety Benchmark Initiative

April 16, 2024

MLCommons, organizer of the popular MLPerf benchmarking exercises (training and inference), is starting a new effort to benchmark AI Safety, one of the most pre Read more…

Exciting Updates From Stanford HAI’s Seventh Annual AI Index Report

April 15, 2024

As the AI revolution marches on, it is vital to continually reassess how this technology is reshaping our world. To that end, researchers at Stanford’s Instit Read more…

Intel’s Vision Advantage: Chips Are Available Off-the-Shelf

April 11, 2024

The chip market is facing a crisis: chip development is now concentrated in the hands of the few. A confluence of events this week reminded us how few chips 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…

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…

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…

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…

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…

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…

Leading Solution Providers

Contributors

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…

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…

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…

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…

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…

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…

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’s Xeon General Manager Talks about Server Chips 

January 2, 2024

Intel is talking data-center growth and is done digging graves for its dead enterprise products, including GPUs, storage, and networking products, which fell to Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire