CERN Project Sees Orders-of-Magnitude Speedup with AI Approach

By Rob Farber

August 14, 2018

An award-winning effort at CERN has demonstrated potential to significantly change how the physics based modeling and simulation communities view machine learning. The CERN team demonstrated that AI-based models have the potential to act as orders-of-magnitude-faster replacements for computationally expensive tasks in simulation, while maintaining a remarkable level of accuracy.

Dr. Federico Carminati (Project Coordinator, CERN) points out, “This work demonstrates the potential of ‘black box’ machine-learning models in physics-based simulations.”

A poster describing this work was awarded the prize for best poster in the category ‘programming models and systems software’ at ISC’18. This recognizes the importance of the work, which was carried out by Dr. Federico Carminati, Gul Rukh Khattak, and Dr. Sofia Vallecorsa at CERN, as well as Jean-Roch Vlimant at Caltech. The work is part of a CERN openlab project in collaboration with Intel Corporation, who partially funded the endeavor through the Intel Parallel Computing Center (IPCC) program.

Widespread potential impact for simulation

The world-wide impact for High-Energy Physics (HEP) scientists could be substantial, as outlined by the CERN poster, which points out that ”Currently, most of the LHC’s worldwide distributed CPU budget — in the range of half a million CPU-years equivalent — is dedicated to simulation.” Speeding up the most time-consuming simulation tasks (e.g., high-granularity calorimeters, which are components in a detector that measure the energy of particles[i]) will help scientists better utilize these allocations. The following are comparative results obtained by the CERN team in the time to create an electron shower, once the AI model has been fully trained:

Figure 1: Comparative runtime to create an electron shower of the machine-learning method (e.g. 3d GAN) vs. the full Monte-Carlo simulation (Image courtesy CERN)

Dr. Sofia Vallecorsa points out that the CPU based runtime is important as nearly all of the Geant user base runs on CPUs. Vallecorsa is a CERN physicist who was also highlighted in the CERN article Coding has no gender.

As scientists consider future CERN experiments, Vallecorsa observes, “Given future plans to upgrade CERN’s Large Hadron Collider, dramatically increasing particle collision rates, frameworks like this have the potential to play an important role in ensuring data rates remain manageable.”

This kind of approach could help to realize similar orders-of-magnitude-faster speedups for computationally expensive simulation tasks used in a range of fields.

Vallecorsa explains that the data distributions coming from the trained machine-learning model are remarkably close to the real and simulated data.

A big change in thinking

The team demonstrated that “energy showers” detected by calorimeters can be interpreted as a 3D image[ii]. The process is illustrated in the following figure. The team adopted this approach from the machine-learning community as deep-learning convolutional neural networks are heavily utilized when working with images.

Figure 2: Schematic from the poster showing how a single particle creates an electron shower that can be viewed as an image (Courtesy CERN)

Use of GANS

The CERN team decided to train Generative Adversarial Networks (GANs) on the calorimeter images. GANs are particularly suited to act as a replacement for the expensive Monte Carlo methods used in HEP simulations as they generate realistic samples for complicated probability distributions, allow multi-modal output, can do interpolation, and are robust against missing data.

The basic idea is easy to understand: train a Generator (G) to create the calorimeter image with sufficient accuracy to trick a discriminator (D) which tries to identify artificial samples from the generator compared to real samples from the Monte Carlo simulation. G reproduces the data distribution starting from random noise. D estimates the probability that a sample came from the training data rather than G. The training procedure for G is to maximize the probability of D making a mistake. A high-level illustration of the GAN is provided below.

Figure 3: High-level view of training a GAN (image from https://medium.com/@devnag/generative-adversearial-networks-in-50-lines-of-code-pytorch-e81b79659e3f)

Even though the description is simple, 3D GANs are unfortunately not “out-of-the-box” networks, which meant the training of the model was non-trivial.

Results

After detailed validation of the trained GAN, there was “remarkable” agreement between the images from the generator and the Monte-Carlo images. This type of approach could potentially be beneficial in other fields where Monte Carlo simulation is used.

More specifically, the CERN team compared high level quantities (e.g., energy shower shapes) and detailed calorimeter response (e.g., single cell response) between the trained generator and the standard Monte Carlo. The CERN team describes the agreement, which is within a few percent, as “remarkable” in their poster.

Visually this agreement can be seen by how closely the blue (real data) and red lines (GAN generated data) overlap in the following results reported in the poster.

Figure 4: Transverse shower shape for 100-500 GeV pions. Red is the GAN data while blue represents the real data. (Image courtesy CERN)

 

Figure 5: Longitudinal shower shape for 400 GeV electron (Image courtesy CERN)

 

Figure 6: Longitudinal shower shape for 100 GeV electron (Image courtesy CERN)

Vallecorsa summarizes these results by stating, “The agreement between the images generated by our model and the Monte Carlo images has been beyond our expectations. This demonstrates that this is a promising avenue for further investigation.”

CERN openlab

The CERN team plans to test performance using FPGAs and other integrated accelerator technologies. FPGAs are known to deliver lower latency and higher inferencing performance than both CPUs and GPUs[iii]. The CERN group also intends to test several deep learning techniques in the hope of achieving a yet greater speedup with respect to Monte Carlo techniques, and ensuring this approach covers a range of detector types, which CERN believes is key to future projects.

This research is being carried out through a CERN openlab project. CERN openlab is a public-private partnership through which CERN collaborates with leading ICT companies to drive innovation in cutting-edge ICT solutions for its research community. Intel has been a partner in CERN openlab since it was first established in 2001. Dr. Alberto Di Meglio (Head of CERN openlab) observes, “At CERN, we’re always interested in exploring upcoming technologies that can help researchers to make new ground-breaking discoveries about our universe. We support this through joint R&D projects with our collaborators from industry, and by making cutting-edge technologies available for evaluation by researchers at CERN.”

Summary

The HPC modeling and simulation community now has a promising path forward to exploit the benefits of machine learning. The key, as demonstrated by CERN, is that the machine-learning-generated distribution needs to be indistinguishable from other high-fidelity methods in physics-based simulations.

The motivation is straightforward: (1) orders of magnitude faster performance, (2) efficient CPU implementations, and (3) this approach could enable the use of other new technologies such as FPGAs that may significantly improve performance.

Additional References

Rob Farber is a global technology consultant and author with an extensive background in HPC and in machine learning technology that he applies at national labs and commercial organizations on a variety of problems including challenges in high energy physics. Rob can be reached at [email protected]

[i] http://cds.cern.ch/record/2254048#

[ii] ibid

[iii] https://medium.com/syncedreview/deep-learning-in-real-time-inference-acceleration-and-continuous-training-17dac9438b0b

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!

SODALITE: Towards Automated Optimization of HPC Application Deployment

May 29, 2020

Developing and deploying applications across heterogeneous infrastructures like HPC or Cloud with diverse hardware is a complex problem. Enabling developers to describe the application deployment and optimising runtime p Read more…

By the SODALITE Team

What’s New in HPC Research: Astronomy, Weather, Security & More

May 29, 2020

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

DARPA Looks to Automate Secure Silicon Designs

May 28, 2020

The U.S. military is ramping up efforts to secure semiconductors and its electronics supply chain by embedding defenses during the chip design phase. The automation effort also addresses the high cost and complexity of s Read more…

By George Leopold

COVID-19 HPC Consortium Expands to Europe, Reports on Research Projects

May 28, 2020

The COVID-19 HPC Consortium, a public-private effort delivering free access to HPC processing for scientists pursuing coronavirus research – some utilizing AI-based techniques – has expanded to more than 56 research Read more…

By Doug Black

What’s New in Computing vs. COVID-19: IceCube, TACC, Watson & More

May 28, 2020

Supercomputing, big data and artificial intelligence are crucial tools in the fight against the coronavirus pandemic. Around the world, researchers, corporations and governments are urgently devoting their computing reso Read more…

By Oliver Peckham

AWS Solution Channel

Computational Fluid Dynamics on AWS

Over the past 30 years Computational Fluid Dynamics (CFD) has grown to become a key part of many engineering design processes. From aircraft design to modelling the blood flow in our bodies, the ability to understand the behaviour of fluids has enabled countless innovations and improved the time to market for many products. Read more…

Supercomputer Simulations Explain the Asteroid that Killed the Dinosaurs

May 28, 2020

The supercomputing community has cataclysms on the mind. Hot on the heels of supercomputer-powered research delving into the fate of the neanderthals, a team of researchers used supercomputers at the DiRAC (Distributed R Read more…

By Oliver Peckham

COVID-19 HPC Consortium Expands to Europe, Reports on Research Projects

May 28, 2020

The COVID-19 HPC Consortium, a public-private effort delivering free access to HPC processing for scientists pursuing coronavirus research – some utilizing AI Read more…

By Doug Black

$100B Plan Submitted for Massive Remake and Expansion of NSF

May 27, 2020

Legislation to reshape, expand - and rename - the National Science Foundation has been submitted in both the U.S. House and Senate. The proposal, which seems to Read more…

By John Russell

IBM Boosts Deep Learning Accuracy on Memristive Chips

May 27, 2020

IBM researchers have taken another step towards making in-memory computing based on phase change (PCM) memory devices a reality. Papers in Nature and Frontiers Read more…

By John Russell

Hats Over Hearts: Remembering Rich Brueckner

May 26, 2020

HPCwire and all of the Tabor Communications family are saddened by last week’s passing of Rich Brueckner. He was the ever-optimistic man in the Red Hat presiding over the InsideHPC media portfolio for the past decade and a constant presence at HPC’s most important events. Read more…

Nvidia Q1 Earnings Top Expectations, Datacenter Revenue Breaks $1B

May 22, 2020

Nvidia’s seemingly endless roll continued in the first quarter with the company announcing blockbuster earnings that exceeded Wall Street expectations. Nvidia Read more…

By Doug Black

Microsoft’s Massive AI Supercomputer on Azure: 285k CPU Cores, 10k GPUs

May 20, 2020

Microsoft has unveiled a supercomputing monster – among the world’s five most powerful, according to the company – aimed at what is known in scientific an Read more…

By Doug Black

HPC in Life Sciences 2020 Part 1: Rise of AMD, Data Management’s Wild West, More 

May 20, 2020

Given the disruption caused by the COVID-19 pandemic and the massive enlistment of major HPC resources to fight the pandemic, it is especially appropriate to re Read more…

By John Russell

AMD Epyc Rome Picked for New Nvidia DGX, but HGX Preserves Intel Option

May 19, 2020

AMD continues to make inroads into the datacenter with its second-generation Epyc "Rome" processor, which last week scored a win with Nvidia's announcement that Read more…

By Tiffany Trader

Supercomputer Modeling Tests How COVID-19 Spreads in Grocery Stores

April 8, 2020

In the COVID-19 era, many people are treating simple activities like getting gas or groceries with caution as they try to heed social distancing mandates and protect their own health. Still, significant uncertainty surrounds the relative risk of different activities, and conflicting information is prevalent. A team of Finnish researchers set out to address some of these uncertainties by... Read more…

By Oliver Peckham

[email protected] Turns Its Massive Crowdsourced Computer Network Against COVID-19

March 16, 2020

For gamers, fighting against a global crisis is usually pure fantasy – but now, it’s looking more like a reality. As supercomputers around the world spin up Read more…

By Oliver Peckham

[email protected] Rallies a Legion of Computers Against the Coronavirus

March 24, 2020

Last week, we highlighted [email protected], a massive, crowdsourced computer network that has turned its resources against the coronavirus pandemic sweeping the globe – but [email protected] isn’t the only game in town. The internet is buzzing with crowdsourced computing... Read more…

By Oliver Peckham

Global Supercomputing Is Mobilizing Against COVID-19

March 12, 2020

Tech has been taking some heavy losses from the coronavirus pandemic. Global supply chains have been disrupted, virtually every major tech conference taking place over the next few months has been canceled... Read more…

By Oliver Peckham

DoE Expands on Role of COVID-19 Supercomputing Consortium

March 25, 2020

After announcing the launch of the COVID-19 High Performance Computing Consortium on Sunday, the Department of Energy yesterday provided more details on its sco Read more…

By John Russell

Supercomputer Simulations Reveal the Fate of the Neanderthals

May 25, 2020

For hundreds of thousands of years, neanderthals roamed the planet, eventually (almost 50,000 years ago) giving way to homo sapiens, which quickly became the do Read more…

By Oliver Peckham

Steve Scott Lays Out HPE-Cray Blended Product Roadmap

March 11, 2020

Last week, the day before the El Capitan processor disclosures were made at HPE's new headquarters in San Jose, Steve Scott (CTO for HPC & AI at HPE, and former Cray CTO) was on-hand at the Rice Oil & Gas HPC conference in Houston. He was there to discuss the HPE-Cray transition and blended roadmap, as well as his favorite topic, Cray's eighth-gen networking technology, Slingshot. Read more…

By Tiffany Trader

Honeywell’s Big Bet on Trapped Ion Quantum Computing

April 7, 2020

Honeywell doesn’t spring to mind when thinking of quantum computing pioneers, but a decade ago the high-tech conglomerate better known for its control systems waded deliberately into the then calmer quantum computing (QC) waters. Fast forward to March when Honeywell announced plans to introduce an ion trap-based quantum computer whose ‘performance’ would... Read more…

By John Russell

Leading Solution Providers

SC 2019 Virtual Booth Video Tour

AMD
AMD
ASROCK RACK
ASROCK RACK
AWS
AWS
CEJN
CJEN
CRAY
CRAY
DDN
DDN
DELL EMC
DELL EMC
IBM
IBM
MELLANOX
MELLANOX
ONE STOP SYSTEMS
ONE STOP SYSTEMS
PANASAS
PANASAS
SIX NINES IT
SIX NINES IT
VERNE GLOBAL
VERNE GLOBAL
WEKAIO
WEKAIO

Contributors

Fujitsu A64FX Supercomputer to Be Deployed at Nagoya University This Summer

February 3, 2020

Japanese tech giant Fujitsu announced today that it will supply Nagoya University Information Technology Center with the first commercial supercomputer powered Read more…

By Tiffany Trader

Tech Conferences Are Being Canceled Due to Coronavirus

March 3, 2020

Several conferences scheduled to take place in the coming weeks, including Nvidia’s GPU Technology Conference (GTC) and the Strata Data + AI conference, have Read more…

By Alex Woodie

Exascale Watch: El Capitan Will Use AMD CPUs & GPUs to Reach 2 Exaflops

March 4, 2020

HPE and its collaborators reported today that El Capitan, the forthcoming exascale supercomputer to be sited at Lawrence Livermore National Laboratory and serve Read more…

By John Russell

Cray to Provide NOAA with Two AMD-Powered Supercomputers

February 24, 2020

The United States’ National Oceanic and Atmospheric Administration (NOAA) last week announced plans for a major refresh of its operational weather forecasting supercomputers, part of a 10-year, $505.2 million program, which will secure two HPE-Cray systems for NOAA’s National Weather Service to be fielded later this year and put into production in early 2022. Read more…

By Tiffany Trader

‘Billion Molecules Against COVID-19’ Challenge to Launch with Massive Supercomputing Support

April 22, 2020

Around the world, supercomputing centers have spun up and opened their doors for COVID-19 research in what may be the most unified supercomputing effort in hist Read more…

By Oliver Peckham

Summit Supercomputer is Already Making its Mark on Science

September 20, 2018

Summit, now the fastest supercomputer in the world, is quickly making its mark in science – five of the six finalists just announced for the prestigious 2018 Read more…

By John Russell

15 Slides on Programming Aurora and Exascale Systems

May 7, 2020

Sometime in 2021, Aurora, the first planned U.S. exascale system, is scheduled to be fired up at Argonne National Laboratory. Cray (now HPE) and Intel are the k Read more…

By John Russell

TACC Supercomputers Run Simulations Illuminating COVID-19, DNA Replication

March 19, 2020

As supercomputers around the world spin up to combat the coronavirus, the Texas Advanced Computing Center (TACC) is announcing results that may help to illumina Read more…

By Staff report

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