ORNL Researchers Help to Bring Application Coupling One Step Closer to Reality

May 7, 2018

May 7, 2018 — Despite exponential increases in computing power over the last couple of decades, many physical processes still present unique challenges for researchers seeking to advance their fields via modeling and simulation.

These processes are so complex that accurately capturing the entirety of their physics is rarely possible with one application. In these cases, researchers look to “couple,” or combine, different codes to get the answers they need.

One such area primed for application coupling is nuclear fusion, or replicating the process that fuels our sun in a magnetic bottle on Earth in the hopes it could one day provide the world with a virtually unlimited, and clean, power source. Fusion energy’s physics are notoriously tricky, requiring a powerful yet delicate plasma to be magnetically confined and sustained at temperatures approaching 10,000 times the core of the sun.

But as computers approach the exascale, or an entire order of magnitude more powerful than today’s leading systems, an unparalleled understanding of what goes on in fusion power devices—and, by extension, the possibility of commercial fusion power—may finally be within reach.

The core and edge regions have very different physics, but because they affect not only one another but also the strength and stability of the reaction, simulating them simultaneously is necessary to truly advance our understanding of fusion plasmas and bring fusion one step closer to reality.

And researchers at Oak Ridge National Laboratory and Princeton Plasma Physics Laboratory have done just that. These two teams partnered with others from Argonne National Laboratory, Lawrence Livermore National Laboratory, Rutgers University, The University of Texas at Austin, Lawrence Berkeley National Laboratory, Georgia Tech, Kitware, Brown University, Sandia National Lab, New Jersey Institute of Technology, and the University of Oregon, to successfully couple separate core and edge applications for the first time.

Using ORNL’s Titan, the fastest computer in the US for open science, the team was able to couple two codes: the popular XGC1 code, which simulates behavior of the ions, electrons and neutral atoms in the barrier region between the core and the material wall, and GENE, which simulates the plasma core.

The work represents more than just a milestone for plasma physics; it also brings researchers one step closer to the coupling of separate applications necessary to truly simulate fusion plasmas and other complex physical phenomena.

The successful simulation grew out of a plan hatched among ORNL’s Scott Klasky, PPPL’s C-S Chang and Amitava Bhattacharjee, and The University of Texas at Austin’s Frank Jenko to couple XGC and GENE in a four-year time frame as part of a much larger goal by the Department of Energy’s Exascale Computing Project to model an entire fusion device in less than 10 years. Such a window was necessary to prepare for a truly coupled-application run, in which fusion’s spatial, temporal and physical characteristics must be seamlessly married. And because of fusion’s disparities in spatial and temporal scales, a framework for modeling an entire fusion device had to be codesigned with experts in physics, computer science, applied math and hardware technologies.

Coupling the two codes in a somewhat simplified manner, yet with all the essential ingredients, was the logical first step. “We knew that if we couldn’t run this coupled simulation on Titan with simplified physics, we would have to rethink our coupling timeline,” said Klasky, who added that the coupling was only possible thanks to the hard work of colleagues Julien Dominski, Gabriele Merlo and Eric Suchyta.

Norbert Podhorszki, the chief scientist in charge of coupling the physics codes, noted: “Creating a scalable framework to help us achieve unlimited energy through fusion is an incredible motivator for computer scientists.”

“Our team worked together with more than 40 scientists from nine organizations to integrate numerous separate projects in a matter of days,” said Podhorszki. “These efforts motivate many of the younger scientists in our group and allow us to be creative in solving complex problems critical to the DOE mission.”

The coupling was further complicated by the fact that the codes themselves are based on different methodologies. XGC1 is a Particle-In-Cell (PIC) code, which monitors the individual interactions between particles that can greatly alter the behavior of the edges of the plasma. GENE on the other hand is a continuum code, meaning it makes assumptions that the material being simulated is smoothly varying over space, enabling the simulation of the average behavior of small regions in order to build a picture of the overall system.

Beyond the codes there were other components, such as data reduction and visualization, that had to be married as well; in all, 11 different components were seamlessly integrated. This required a delicate balancing act because the incorporation of the various components meant making tradeoffs in both individual performances and the performance of the larger simulation.

“It proved our ability to compose numerous services together on an HPC resource and place the ‘right’ processing at the ‘right place,’” said Klasky, adding that by using ORNL’s ADIOS middleware package, they were able to conduct the entire enterprise solely in memory, resulting in an efficient exascale service-oriented architecture for the coupling of fusion codes.

A collaborative effort

Whereas the vision for the simultaneous simulation came from Klasky, Chang, Bhattacharjee and Jenko, the simulations themselves required collaboration across multiple agencies including DOE’s Exascale Computing Project, the Scientific Discovery through Advanced Computing program, and the Office of Advanced Scientific Computing Research.

“This milestone wouldn’t have been possible without this collaboration across agencies and teams,” said Klasky.

Of course, having one of the world’s most powerful computers didn’t hurt, either. Simulating the edge and core separately is highly demanding in its own right, but simulating them concurrently required a machine with Titan’s power.

But machines like Titan present their own challenges, and to ensure they were making the most of the Cray XK7 and that the simulations were running smoothly, the team developed a coupling framework capable of constantly monitoring XGC’s performance.

Besides enabling the current simulations, the framework will be immensely helpful in understanding the impact of different exascale tradeoffs for next-generation machines. “Big computers like Titan exist to solve large problems. And to do that, you must use as much of the machine as possible,” said Klasky, adding that running these complex simulations on next-generation DOE machines, including Summit at ORNL, will be critical to fusion’s success.

Furthermore, understanding performance tradeoffs on collaborators’ machines, such as TSUBAME 3, will further enable the team to streamline coupling going forward. Attaining such an understanding meant monitoring the simulation itself, along with the various I/O, data reduction and visualization components, in real time. This real-time monitoring enabled the team to correct mistakes as they unfolded, increasing the validity of the results and reducing time to solution.

Klasky said all of the components were run together in memory, thus allowing the relevant specialists to monitor their specific areas of interests.

“The physicists can look at the physics, the computational scientists can monitor performance, and the visualization team can ensure the visualization is accurate,” he said. “People can run complex situations that involve coupling, visualization and performance, with the codes composed and optimized for the largest machines in the world.”

And although the current domain of interest is fusion, Klasky said that the same framework could be applied to chemistry, molecular dynamics and nearly any other science domain capable of taking advantage of science’s most powerful computers.

“We’ve made a critical step toward application coupling but have really only scratched the surface,” said Klasky.

In fact, the team is now working with Hub Van Dam of Brookhaven National Laboratory to apply its framework to the popular computational chemistry code NW Chem, paving the way for the rest of the scientific spectrum to take advantage of the unprecedented computing power just around the corner.

The team included Qing Liu and William Godoy on ADIOS; Manish Parashar and Philip Davis on Dataspaces; Julien Dominski, Jong Choi and Eric Suchyta on the ECP code coupler; Greg Eisenhauer on Flexpath; Kshitij Mehta, Bryce Allen and Matthew Wolf on Savanna-Cheetah; Kevin Huck on TAU and SOS; David Pugmire, James Kress and Mark Kim on the visualization services; Berk Geveci, Ken Moreland and Donglian Chu on VTK-M; Robert Hager on XGC-core; Seung Hoe Ku and Michael Churchill on XGC-edge; Gabriele Merlo and Frank Jenko on GENE; and Scott Klasky, C-S Chang, Norbert Podhorszki, Ian Foster and Todd Munson for overall leadership.

Titan is part of the Oak Ridge Leadership Computing Facility, a DOE Office of Science User Facility.

ORNL is managed by UT-Battelle for the Department of Energy’s Office of Science, the single largest supporter of basic research in the physical sciences in the United States. DOE’s Office of Science is working to address some of the most pressing challenges of our time. For more information, please visit http://science.energy.gov/.


Source: ORNL

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

GTC 2019: Chief Scientist Bill Dally Provides Glimpse into Nvidia Research Engine

March 22, 2019

Amid the frenzy of GTC this week – Nvidia’s annual conference showcasing all things GPU (and now AI) – William Dally, chief scientist and SVP of research, provided a brief but insightful portrait of Nvidia’s rese Read more…

By John Russell

ORNL Helps Identify Challenges of Extremely Heterogeneous Architectures

March 21, 2019

Exponential growth in classical computing over the last two decades has produced hardware and software that support lightning-fast processing speeds, but advancements are topping out as computing architectures reach thei Read more…

By Laurie Varma

Interview with 2019 Person to Watch Jim Keller

March 21, 2019

On the heels of Intel's reaffirmation that it will deliver the first U.S. exascale computer in 2021, which will feature the company's new Intel Xe architecture, we bring you our interview with our 2019 Person to Watch Jim Keller, head of the Silicon Engineering Group at Intel. Read more…

By HPCwire Editorial Team

HPE Extreme Performance Solutions

HPE and Intel® Omni-Path Architecture: How to Power a Cloud

Learn how HPE and Intel® Omni-Path Architecture provide critical infrastructure for leading Nordic HPC provider’s HPCFLOW cloud service.

powercloud_blog.jpgFor decades, HPE has been at the forefront of high-performance computing, and we’ve powered some of the fastest and most robust supercomputers in the world. Read more…

IBM Accelerated Insights

Insurance: Where’s the Risk?

Insurers are facing extreme competitive challenges in their core businesses. Property and Casualty (P&C) and Life and Health (L&H) firms alike are highly impacted by the ongoing globalization, increasing regulation, and digital transformation of their client bases. Read more…

What’s New in HPC Research: TensorFlow, Buddy Compression, Intel Optane & More

March 20, 2019

In this bimonthly feature, HPCwire highlights newly published research in the high-performance computing community and related domains. From parallel programming to exascale to quantum computing, the details are here. Read more…

By Oliver Peckham

GTC 2019: Chief Scientist Bill Dally Provides Glimpse into Nvidia Research Engine

March 22, 2019

Amid the frenzy of GTC this week – Nvidia’s annual conference showcasing all things GPU (and now AI) – William Dally, chief scientist and SVP of research, Read more…

By John Russell

At GTC: Nvidia Expands Scope of Its AI and Datacenter Ecosystem

March 19, 2019

In the high-stakes race to provide the AI life-cycle solution of choice, three of the biggest horses in the field are IBM, Intel and Nvidia. While the latter is only a fraction of the size of its two bigger rivals, and has been in business for only a fraction of the time, Nvidia continues to impress with an expanding array of new GPU-based hardware, software, robotics, partnerships and... Read more…

By Doug Black

Nvidia Debuts Clara AI Toolkit with Pre-Trained Models for Radiology Use

March 19, 2019

AI’s push into healthcare got a boost yesterday with Nvidia’s release of the Clara Deploy AI toolkit which includes 13 pre-trained models for use in radiolo Read more…

By John Russell

It’s Official: Aurora on Track to Be First US Exascale Computer in 2021

March 18, 2019

The U.S. Department of Energy along with Intel and Cray confirmed today that an Intel/Cray supercomputer, "Aurora," capable of sustained performance of one exaf Read more…

By Tiffany Trader

Why Nvidia Bought Mellanox: ‘Future Datacenters Will Be…Like High Performance Computers’

March 14, 2019

“Future datacenters of all kinds will be built like high performance computers,” said Nvidia CEO Jensen Huang during a phone briefing on Monday after Nvidia revealed scooping up the high performance networking company Mellanox for $6.9 billion. Read more…

By Tiffany Trader

Oil and Gas Supercloud Clears Out Remaining Knights Landing Inventory: All 38,000 Wafers

March 13, 2019

The McCloud HPC service being built by Australia’s DownUnder GeoSolutions (DUG) outside Houston is set to become the largest oil and gas cloud in the world th Read more…

By Tiffany Trader

Quick Take: Trump’s 2020 Budget Spares DoE-funded HPC but Slams NSF and NIH

March 12, 2019

U.S. President Donald Trump’s 2020 budget request, released yesterday, proposes deep cuts in many science programs but seems to spare HPC funding by the Depar Read more…

By John Russell

Nvidia Wins Mellanox Stakes for $6.9 Billion

March 11, 2019

The long-rumored acquisition of Mellanox came to fruition this morning with GPU chipmaker Nvidia’s announcement that it has purchased the high-performance net Read more…

By Doug Black

Quantum Computing Will Never Work

November 27, 2018

Amid the gush of money and enthusiastic predictions being thrown at quantum computing comes a proposed cold shower in the form of an essay by physicist Mikhail Read more…

By John Russell

The Case Against ‘The Case Against Quantum Computing’

January 9, 2019

It’s not easy to be a physicist. Richard Feynman (basically the Jimi Hendrix of physicists) once said: “The first principle is that you must not fool yourse Read more…

By Ben Criger

ClusterVision in Bankruptcy, Fate Uncertain

February 13, 2019

ClusterVision, European HPC specialists that have built and installed over 20 Top500-ranked systems in their nearly 17-year history, appear to be in the midst o Read more…

By Tiffany Trader

Intel Reportedly in $6B Bid for Mellanox

January 30, 2019

The latest rumors and reports around an acquisition of Mellanox focus on Intel, which has reportedly offered a $6 billion bid for the high performance interconn Read more…

By Doug Black

Why Nvidia Bought Mellanox: ‘Future Datacenters Will Be…Like High Performance Computers’

March 14, 2019

“Future datacenters of all kinds will be built like high performance computers,” said Nvidia CEO Jensen Huang during a phone briefing on Monday after Nvidia revealed scooping up the high performance networking company Mellanox for $6.9 billion. Read more…

By Tiffany Trader

Looking for Light Reading? NSF-backed ‘Comic Books’ Tackle Quantum Computing

January 28, 2019

Still baffled by quantum computing? How about turning to comic books (graphic novels for the well-read among you) for some clarity and a little humor on QC. The Read more…

By John Russell

Contract Signed for New Finnish Supercomputer

December 13, 2018

After the official contract signing yesterday, configuration details were made public for the new BullSequana system that the Finnish IT Center for Science (CSC Read more…

By Tiffany Trader

Deep500: ETH Researchers Introduce New Deep Learning Benchmark for HPC

February 5, 2019

ETH researchers have developed a new deep learning benchmarking environment – Deep500 – they say is “the first distributed and reproducible benchmarking s Read more…

By John Russell

Leading Solution Providers

SC 18 Virtual Booth Video Tour

Advania @ SC18 AMD @ SC18
ASRock Rack @ SC18
DDN Storage @ SC18
HPE @ SC18
IBM @ SC18
Lenovo @ SC18 Mellanox Technologies @ SC18
NVIDIA @ SC18
One Stop Systems @ SC18
Oracle @ SC18 Panasas @ SC18
Supermicro @ SC18 SUSE @ SC18 TYAN @ SC18
Verne Global @ SC18

It’s Official: Aurora on Track to Be First US Exascale Computer in 2021

March 18, 2019

The U.S. Department of Energy along with Intel and Cray confirmed today that an Intel/Cray supercomputer, "Aurora," capable of sustained performance of one exaf Read more…

By Tiffany Trader

IBM Quantum Update: Q System One Launch, New Collaborators, and QC Center Plans

January 10, 2019

IBM made three significant quantum computing announcements at CES this week. One was introduction of IBM Q System One; it’s really the integration of IBM’s Read more…

By John Russell

IBM Bets $2B Seeking 1000X AI Hardware Performance Boost

February 7, 2019

For now, AI systems are mostly machine learning-based and “narrow” – powerful as they are by today's standards, they're limited to performing a few, narro Read more…

By Doug Black

The Deep500 – Researchers Tackle an HPC Benchmark for Deep Learning

January 7, 2019

How do you know if an HPC system, particularly a larger-scale system, is well-suited for deep learning workloads? Today, that’s not an easy question to answer Read more…

By John Russell

HPC Reflections and (Mostly Hopeful) Predictions

December 19, 2018

So much ‘spaghetti’ gets tossed on walls by the technology community (vendors and researchers) to see what sticks that it is often difficult to peer through Read more…

By John Russell

Arm Unveils Neoverse N1 Platform with up to 128-Cores

February 20, 2019

Following on its Neoverse roadmap announcement last October, Arm today revealed its next-gen Neoverse microarchitecture with compute and throughput-optimized si Read more…

By Tiffany Trader

Move Over Lustre & Spectrum Scale – Here Comes BeeGFS?

November 26, 2018

Is BeeGFS – the parallel file system with European roots – on a path to compete with Lustre and Spectrum Scale worldwide in HPC environments? Frank Herold Read more…

By John Russell

France to Deploy AI-Focused Supercomputer: Jean Zay

January 22, 2019

HPE announced today that it won the contract to build a supercomputer that will drive France’s AI and HPC efforts. The computer will be part of GENCI, the Fre Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This