CERN, Google Drive Future of Global Science Initiatives

By Ian Armas Foster

May 21, 2013

Large-scale, worldwide scientific initiatives, such as the one that found the Higgs Boson or the one that is currently researching the depths of proteomics, rely on some cloud-based system to both coordinate efforts and manage computational efforts at peak times that cannot be contained within the combined in-house HPC resources.

Last week at Google I/O, Brookhaven National Lab’s Sergey Panitkin discussed the role of the Google Compute Engine in providing computational support to ATLAS, a detector of high-energy particles at the Large Hadron Collider (LHC).

On July 4 of last year, one of the largest physics experiments in history announced the finding of the Higgs Boson. The discovery was another step in the verification of the Standard Model of elementary particles, and it was largely a result of the data collected by the ATLAS detector that was later stored, analyzed, and used in simulations in computational centers around the world.

Naturally, CERN is equipped with significant computational capabilities as it sifts through the swaths of data created by the LHC. However, a great deal of that data was being sent out to scientists across the world in over a hundred computing centers located in over 40 countries.

As a result, Google stepped forward in August of last year to offer its Compute Engine services for overflow scientific computing periods. According to Panitkin, those spikes would occur before major conferences, overloading the existing computational framework. These overflow spikes represent an intriguing phenomenon, a macro-scale example of a problem that many mid-sized research institutions face on their own. Many of those institutions house their own HPC cluster that handles the majority of their heavy duty computational leg-work. When those resources are exhausted at peak times, they turn to the cloud.

When that problem manifests itself at key times across a research project that spans hundreds of facilities across the globe, that becomes a massive, worldwide HPC cloud computing challenge.

As such, the ATLAS project was invited by Google to test the Google Compute Engine in an effort to complete that challenge.

The experience has gone well so far, according to Panitkin. “All in all, we had a great experience with Google Computing. We tested several computational scenarios on that platform…we think that Google Compute Engine is a modern cloud infrastructure that can serve as a stable, high performance platform for scientific computing.”

The ATLAS collector, diagrammed below, was designed to intake and record 800 million proton-proton interactions per second. Of those 800 million collisions per second, only about 0.0002 Higgs signatures are detected per second. That translates to one signature for every 83 minutes or so. The computing systems have to sift through that huge dataset containing information from each of those almost billion interactions a second to find that one distinct pattern.

Thankfully, much of the ATLAS data is instantly filtered and discarded by an automatic trigger system. Were this not the case, the collector would generate a slightly unsustainable petabyte of data per second.

Adding to the challenge that the enormous amount of data presents is the very particular signature the ATLAS project was looking for. According to Panitkin, sifting through that much is akin to trying to find just one person in a system of a thousand planets of the same population as Earth. To help visualize what that looks like, the above picture represents all the possible signatures while the diagram below shows the one specific indicator of the Higgs Boson.

CERN collects the data and initially distributes it to its 11 tier-one centers, as shown in the diagram below. The cloud and specifically the Google Compute Engine enter the picture in tier two, where about two hundred centers across the globe simulate their respective sections based on the tier-naught CERN data.

Combining all of those resources into a shared system is essential for scientific researchers, as they cull information from other tests and simulations run. According to Andrew Hanushevsky, who presented alongside Panitkin at the Google I/O event, the system was aggregated using the XRootD system. XRootD, coupled with cmsd, was instrumental and combining and managing the thousand-core PROOF cluster made for ATLAS as well as the 4000-core HTCondor cluster for CERN’s collision analysis.

The important aspect was ensuring the system acted as one, as Hanushevsky explained. “This is a B tree, we can split it up anyway we want and this is great for doing cloud deployment. Part of that tree can be inside the GCE, another part can be in a private cloud, another part in a private cluster, and we can piece that all together to make it look like one big cluster.”

With that in place, the researchers could share information across the network at an impressive transfer rate of 57 Mbps transfer rate to the Google Compute Engine.

Finally, according to Panitkin, the computations done over GCE were impressively accurate. The system reported, according to Panitkin, “no failures due to Google Compute Engine.”

The best science requires extensive collaboration. Global projects such as the one that found the Higgs Boson mark the pinnacle of that collaboration, and these efforts can only grow stronger with the betterment of large-scale cloud-based computing services like Google Compute Engine.

Related Articles

Avoiding Scientific Computing Bottlenecks in the Cloud

On the Verge of Cloud 2.0

Running Computational Fluid Dynamics in the Cloud

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!

SC17 Student Cluster Competition Configurations: Fewer Nodes, Way More Accelerators

November 16, 2017

The final configurations for each of the SC17 “Donnybrook in Denver” Student Cluster Competition have been released. Fortunately, each team received their equipment shipments on time and undamaged, so the teams are r Read more…

By Dan Olds

Student Clusterers Demolish HPCG Record! Nanyang Sweeps Benchmarks

November 16, 2017

Nanyang pulled off the always difficult double-play at this year’s SC Student Cluster Competition. The plucky team from Singapore posted a world record LINPACK, thus taking the Highest LINPACK Award, but also managed t Read more…

By Dan Olds

Student Cluster LINPACK Record Shattered! More LINs Packed Than Ever before!

November 16, 2017

Nanyang Technological University, the pride of Singapore, utterly destroyed the Student Cluster Competition LINPACK record by posting a score of 51.77 TFlop/s at SC17 in Denver. The previous record, established by German Read more…

By Dan Olds

HPE Extreme Performance Solutions

Harness Scalable Petabyte Storage with HPE Apollo 4510 and HPE StoreEver

As a growing number of connected devices challenges IT departments to rapidly collect, manage, and store troves of data, organizations must adopt a new generation of IT to help them operate quickly and intelligently. Read more…

Hyperion Market Update: ‘Decent’ Growth Led by HPE; AI Transparency a Risk Issue

November 15, 2017

The HPC market update from Hyperion Research (formerly IDC) at the annual SC conference is a business and social “must,” and this year’s presentation at SC17 played to a SRO crowd at a downtown Denver hotel. This w Read more…

By Doug Black

SC17 Student Cluster Competition Configurations: Fewer Nodes, Way More Accelerators

November 16, 2017

The final configurations for each of the SC17 “Donnybrook in Denver” Student Cluster Competition have been released. Fortunately, each team received their e Read more…

By Dan Olds

Student Clusterers Demolish HPCG Record! Nanyang Sweeps Benchmarks

November 16, 2017

Nanyang pulled off the always difficult double-play at this year’s SC Student Cluster Competition. The plucky team from Singapore posted a world record LINPAC Read more…

By Dan Olds

Student Cluster LINPACK Record Shattered! More LINs Packed Than Ever before!

November 16, 2017

Nanyang Technological University, the pride of Singapore, utterly destroyed the Student Cluster Competition LINPACK record by posting a score of 51.77 TFlop/s a Read more…

By Dan Olds

Hyperion Market Update: ‘Decent’ Growth Led by HPE; AI Transparency a Risk Issue

November 15, 2017

The HPC market update from Hyperion Research (formerly IDC) at the annual SC conference is a business and social “must,” and this year’s presentation at S Read more…

By Doug Black

The Betting Window is Closed: Final Student Cluster Competition Betting Odds are in!

November 15, 2017

The window has closed and the bettors are clutching their tickets, anxiously awaiting the results of the SC17 Student Cluster Competition. We’ve seen big chan Read more…

By Dan Olds

2017 Student Cluster Competition Benchmarks, Workloads, and Pre-Planned Disasters

November 15, 2017

The students competing in the 2017 Student Cluster Competition in Denver are facing a grueling 48 hour marathon of HPC benchmarks and real scientific applicatio Read more…

By Dan Olds

Nvidia Focuses Its Cloud Containers on HPC Applications

November 14, 2017

Having migrated its top-of-the-line datacenter GPU to the largest cloud vendors, Nvidia is touting its Volta architecture for a range of scientific computing ta Read more…

By George Leopold

HPE Launches ARM-based Apollo System for HPC, AI

November 14, 2017

HPE doubled down on its memory-driven computing vision while expanding its processor portfolio with the announcement yesterday of the company’s first ARM-base Read more…

By Doug Black

US Coalesces Plans for First Exascale Supercomputer: Aurora in 2021

September 27, 2017

At the Advanced Scientific Computing Advisory Committee (ASCAC) meeting, in Arlington, Va., yesterday (Sept. 26), it was revealed that the "Aurora" supercompute Read more…

By Tiffany Trader

NERSC Scales Scientific Deep Learning to 15 Petaflops

August 28, 2017

A collaborative effort between Intel, NERSC and Stanford has delivered the first 15-petaflops deep learning software running on HPC platforms and is, according Read more…

By Rob Farber

Oracle Layoffs Reportedly Hit SPARC and Solaris Hard

September 7, 2017

Oracle’s latest layoffs have many wondering if this is the end of the line for the SPARC processor and Solaris OS development. As reported by multiple sources Read more…

By John Russell

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Google Releases Deeplearn.js to Further Democratize Machine Learning

August 17, 2017

Spreading the use of machine learning tools is one of the goals of Google’s PAIR (People + AI Research) initiative, which was introduced in early July. Last w Read more…

By John Russell

GlobalFoundries Puts Wind in AMD’s Sails with 12nm FinFET

September 24, 2017

From its annual tech conference last week (Sept. 20), where GlobalFoundries welcomed more than 600 semiconductor professionals (reaching the Santa Clara venue Read more…

By Tiffany Trader

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

Amazon Debuts New AMD-based GPU Instances for Graphics Acceleration

September 12, 2017

Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The Read more…

By John Russell

Leading Solution Providers

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

EU Funds 20 Million Euro ARM+FPGA Exascale Project

September 7, 2017

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development. Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work... Read more…

By Tiffany Trader

Delays, Smoke, Records & Markets – A Candid Conversation with Cray CEO Peter Ungaro

October 5, 2017

Earlier this month, Tom Tabor, publisher of HPCwire and I had a very personal conversation with Cray CEO Peter Ungaro. Cray has been on something of a Cinderell Read more…

By Tiffany Trader & Tom Tabor

Cray Moves to Acquire the Seagate ClusterStor Line

July 28, 2017

This week Cray announced that it is picking up Seagate's ClusterStor HPC storage array business for an undisclosed sum. "In short we're effectively transitioning the bulk of the ClusterStor product line to Cray," said CEO Peter Ungaro. Read more…

By Tiffany Trader

Intel Launches Software Tools to Ease FPGA Programming

September 5, 2017

Field Programmable Gate Arrays (FPGAs) have a reputation for being difficult to program, requiring expertise in specialty languages, like Verilog or VHDL. Easin Read more…

By Tiffany Trader

HPC Chips – A Veritable Smorgasbord?

October 10, 2017

For the first time since AMD's ill-fated launch of Bulldozer the answer to the question, 'Which CPU will be in my next HPC system?' doesn't have to be 'Whichever variety of Intel Xeon E5 they are selling when we procure'. Read more…

By Dairsie Latimer

IBM Advances Web-based Quantum Programming

September 5, 2017

IBM Research is pairing its Jupyter-based Data Science Experience notebook environment with its cloud-based quantum computer, IBM Q, in hopes of encouraging a new class of entrepreneurial user to solve intractable problems that even exceed the capabilities of the best AI systems. Read more…

By Alex Woodie

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Share This