Exascale Readiness Key to Solving High Energy Physics Mysteries

By Linda Barney

April 13, 2022

Scientists at Brookhaven National Laboratory, Columbia University, the University of Connecticut, University of Edinburgh, Regensburg University, and the University of Southampton are seeking answers to physics mysteries at the highest energies and shortest distances. The team is devising new methods and enhancing their code in order to exploit the huge potential of the forthcoming Intel-HPE Aurora exascale supercomputer.

Dr. Norman Christ, Ephraim Gildor Professor of Computational Theoretical Physics at Columbia University explains, “Supercomputers are required because we are studying phenomena that involve quarks and gluons whose interactions require enormous computer resources to accurately predict results. Using the Aurora exascale supercomputer will allow us to do high energy physics research that isn’t possible on existing supercomputers. Our research focuses on rare processes that are sensitive to new phenomena, which can appear directly only in experiments performed at energies far higher than those accessible in present particle accelerators.”

Some of the questions the team hopes to answer include:

  • Can the 0.0000000000001% difference between the masses of the two species of neutral K meson be predicted by the Standard Model of particle physics?
  • What are the contributions of the up, down, strange and charm quarks at low energy to the asymmetries between particles and anti-particles found in the decays of these K mesons?
  • Does the new measurement of a very rare decay of a K+ meson into a p+ meson plus two neutrinos that occurs once in every ten billion decays, agree with the prediction of the Standard Model?

Physicists hope the answers to questions such as these will provide clues to underlying laws of nature that governed the origins of our universe.

The team is using early versions of the Intel Xe GPUs and anticipates a 50X processing speed-up in running calculations compared to those done on the ALCF Mira supercomputer. The team’s improved codes targeting Aurora make extensive use of the oneAPI multi-platform framework.

Discovering the nature of sub-atomic particles

Physics research seeks to discover information about the fundamental elements of matter and the laws, which govern their interactions. There are important phenomena observed on a cosmic scale such as the dominance of matter over anti-matter and the observations that suggest the existence of dark matter and dark energy that hint at new particles and interactions not present in the Standard Model.

Central to the Standard Model are elementary particles called quarks and gluons that combine to form particles known as hadrons which include the protons and neutrons that make up the atomic nucleus. Quarks have properties such as mass, electrical charge, color charge and spin. There are six known types of quark named up, down, charm, strange, top, and bottom.

For every type of quark, an antiquark exists with the same properties as the quark but with the opposite sign (negative versus positive) for the electric and color charges. The four heavier types of quark can change into up and down quarks through a process called weak decay. Extensive experiments performed over the past 70 years revealed how these quarks combine to form hundreds of different types of stable and unstable particles. In the 1970’s, scientists discovered that the large array of different hadron particles were actually different combinations of these six different types of quarks. The forces causing the quarks to combine could be described by quantum chromo-dynamics (QCD) equations that describe the strong nuclear force. However, solving these QCD equations was impossible before the development of supercomputers.

The realistic solution of QCD equations is only possible on modern supercomputers. The approach using supercomputers is dramatically different from the usual approach to quantum problems at the atomic scale. Richard Feynman developed an approach that requires carefully generating samples or snapshots of the fluctuating fields that describe the forces between the quarks. These samples indicate points in a space of 5 billion dimensions and require powerful computers to run the simulations.

Lattice QCD, developed in the 1970s, replaces the space-time continuum by a regular grid or lattice of locations, each corresponding to a specific point in space at a specific time. Research accomplishments using these methods evolved with each new generation of supercomputers enabling exciting new results which were previously out of reach. The large step in computer power represented by the class of exascale computers such as Aurora will again propel lattice QCD research to a new level.

Lattice QCD case study

The study of fundamental questions in particle physics using lattice QCD is a large international effort actively pursued on the fastest supercomputers around the world. Christ states, “In preparing to use an important new supercomputer such as Aurora, our research groups work together as a single Aurora Early Science project so that what is learned can benefit everyone. Our project is one part of the effort to be ready to use Aurora as soon as it begins to operate.”

“The weak decays in which the heavier four quarks (top, bottom, charm, and strange) transform into the two lighter up and down quarks are caused by processes that happen at very high energies. This energy is approximately one hundred times higher than the energy stored in the mass of the proton or neutron—the constituents from which the atomic nucleus is built. These high energies can accurately be treated by a complementary method called QCD perturbation theory. Lattice QCD can be used to solve the low energy part of the problem while QCD perturbation theory can handle this high-energy part.”

“The charm quark is too heavy to treat accurately with lattice QCD but too light to allow QCD perturbation theory to be used. Fortunately, this is a problem that Aurora can solve. The underlying difficulty created by the large mass of the charm quark is caused by its small quantum size. As a particle becomes more massive, its properties become more sensitive to what happens at shorter distances. If lattice QCD is to accurately describe the physics of charm quarks, the artificial distance between the lattice points must be made smaller than that needed to treat the less massive up, down, and strange quarks. If the lattice points are to be placed closer together, far more points will be needed to fill a volume of an appropriate physical size. These issues make the problem much more difficult. Typically, if the spacing between lattice points is reduced by a factor of two, the computational time required to solve this new problem will by one hundred times greater. Thus, this entire class of questions can for the first time be effectively tackled with Aurora.”

Figure 1. – Sketch of the quantum process in which a K0 meson transforms into its anti-particle. The wavy lines represent gluons, the red lines light up and down quarks and the green line indicates a strange quark. The yellow squares show Standard Model weak interactions in which a strange quark transforms into three light quarks. The underlying grid structure indicates the process as computed using lattice QCD. Courtesy of Dr. Christ, Columbia University.

Software used in the high energy research

A large component of lattice QCD research is devoted to developing powerful algorithms and highly efficient computer code. The change from supercomputers constructed of arrays of interconnected CPUs (central processing units) to arrays of interconnected clusters of GPUs (graphics processing units) created huge challenges and huge opportunities for those developing lattice QCD codes and algorithms. The software used for the team’s ESP project is based on the open-source Grid system, software targeting lattice QCD developed by Peter Boyle of Brookhaven and the University of Edinburgh and his collaborators.

Grid was developed to replace the low-level but high-performance assembly language code used in early lattice QCD calculations. Grid exploits the features of the C++11 language and the significant advances in compiler technology to achieve assembly-language performance even for highly parallel CPU architectures from a high-level language. In fact, the abstractions used in Grid can also provide platform portability. Grid code can now be compiled both for CPUs and GPUs giving high performance on both architectures.

Preparing to run on the Aurora supercomputer

Aurora is taking advantage of the oneAPI industry initiative that will free researchers from the proprietary CUDA software that is widely used on the Summit supercomputer. This provides for code development on a broad-based open standard allowing developers to program once and run on different hardware from different vendors. To do so, Aurora supports the SYCL C++ abstraction layer that is part of the oneAPI industry initiative. As described above, running on Aurora required generalizations of Grid since lattice QCD code must be able to compile on both CPU and GPU systems.

Christ states, “Perhaps the greatest difficulty for lattice QCD is caused by the substantial increase in GPU computing power which is not matched by the performance of the communications network that interconnects the Aurora nodes, which are themselves clusters of well-connected GPUs. Since lattice QCD must exchange data between these nodes, such an imbalance between the processing power of the nodes and the bandwidth of the data communication between the nodes can result in a ‘network-bound’ application in which the slower communications network limits the overall performance.” The Intel solution slated for Aurora includes two Next Generation Intel Xeon Scalable processors (codename Sapphire Rapids) paired with six Intel Xe GPUs offering significant computing power for the available network performance. Application algorithms can be modified like lattice QCD has done to adjust to this architectural change and achieve optimal performance.

The Aurora supercomputer will also use Intel’s Next Gen Xeon Scalable Processor plus High Bandwidth Memory (HBM). It offers 64GB of high-bandwidth memory configurable in three modes: HBM-only, Flat, and Cache. End users running on Aurora can determine the mode in which to run the workload. It is anticipated that applications and problems that can fit within the available 64GB of HBM can run in HBM-only mode without changes. Similarly for those applications requiring more than 64GB, cache mode can be utilized without changes. Flat memory mode offers users greater control over tuning for optimal performance if developers are willing and able to make some algorithmic changes.

“A major goal of the team’s Early Science preparations is to overcome these network challenges by exploiting the size and power of the individual nodes. To avert the QCD communication problem, the team is reorganizing the calculation. A larger fraction of the calculation is divided among the powerful nodes and carried out with no communication between the nodes, using only infrequent bursts of communication between the nodes. Fortunately, there are earlier domain-decomposed algorithms that have this character, and which are now being actively reconfigured for Aurora’s architecture,” states Christ.  This work will also benefit QCD on future technologies expected to continue this trend.

Future Lattice QCD Research

“Having the power of the exascale Aurora supercomputer will open new vistas for lattice QCD research. For those processes in which the charm quark plays a central role, we expect to carry out calculations that were not previously possible, obtaining results with a level of precision and accuracy with the potential to reveal new particles and interactions not present in the Standard Model. The same physical laws determine the behavior of matter at the smallest and largest scales. We may dream that these discoveries will also help to explain unanswered questions raised by the large-scale structure of the Universe such as nature of dark matter, dark energy, and the preponderance of matter over anti-matter, a dominance necessary for our existence,” says Christ.

The ALCF is a DOE Office of Science User Facility.

Linda Barney is the founder and owner of Barney and Associates, a technical/marketing writing, training, and web design firm in Beaverton, OR.

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!

HPC Pioneer Gordon Bell Passed Away

May 22, 2024

Legendary computer scientist Gordon Bell passed away last Friday at his home in Coronado, CA. He was 89. The New York Times has a nice tribute piece. A long-time pioneer with Digital Equipment Corp, he pushed hard for de Read more…

ISC 2024 — A Few Quantum Gems and Slides from a Packed QC Agenda

May 22, 2024

If you were looking for quantum computing content, ISC 2024 was a good place to be last week — there were around 20 quantum computing related sessions. QC even earned a slide in Kathy Yelick’s opening keynote — Bey 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 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…

ISC 2024 — A Few Quantum Gems and Slides from a Packed QC Agenda

May 22, 2024

If you were looking for quantum computing content, ISC 2024 was a good place to be last week — there were around 20 quantum computing related sessions. QC eve 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…

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…

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…

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 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…

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…

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…

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…

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…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire