Pan-European Cloud to Support Big Science

By Tiffany Trader

March 6, 2012

Three of Europe’s most prominent research centers, CERN, the European Space Agency (ESA), and the European Molecular Biology Laboratory (EMBL) have teamed up to launch a massive cloud computing project. Helix Nebula – the Science Cloud, which takes its name from a large planetary nebula in the Aquarius constellation, will support the fast-growing IT requirements of European scientists. After an initial two-year pilot phase, the project will be expanded to include governmental organizations and industry.

The launch is part of the wider Digital Agenda for Europe. Europe’s cloud-first goals are outlined in the Strategic Plan for a Scientific Cloud Computing infrastructure for Europe, which includes this ambitious vision statement:

In 2020, all scientists of all disciplines will choose the European Cloud Computing Infrastructure as their first option to store and access data, for data processing and analysis. This infrastructure will be considered as a natural infrastructure for the global science community similar to the road or telecommunication infrastructure for the general public today.

This infrastructure will contain vast quantities of data, an unrivalled array of open source tools, and a literally infinite amount of computing power accessible and usable from any kind of computer, smart phone or tablet device. Science will make significant progresses by applying data sharing and interdisciplinary research using this infrastructure as the fundamental tool. Important articles for leading publications, such as Nature and Science, will be derived from this infrastructure and it will be the source of a drastic increase of patents in Europe.

This infrastructure will have such a reliability and worldwide recognition for its implemented security/privacy scheme that also commercial companies will be using this “high security area” to derive patents.

For now, at least, the Helix Nebula project is a Europe-only endeavor due to concern over US laws like the Patriot Act, which conflict with European data security and privacy mandates. Commercial partners include Atos, Capgemini, CloudSigma, Interoute, Logica, Orange Business Services, SAP, SixSq, Telefonica, Terradue, Thales, The Server Labs and T-Systems, as well as the Cloud Security Alliance, the OpenNebula Project and the European Grid Infrastructure (EGI.eu).

The participants are working on creating a common framework, documenting everything and getting real computing going, but as the project gains steam, other scientific organizations and service providers will be invited to join.

“Assuming this phase is successful, an expansion to include more applications, more research and public organizations and more cloud computing suppliers is foreseen. Of particular interest is to stimulate a market where SME can make use of the computing platform to provide new services,” notes Bob Jones, head of CERN openlab.

CloudSigma, an Infrastructure-as-a-Service (IaaS) provider, based in Zurich, Switzerland, is supplying the cloud infrastructure for the project. CEO Robert Jenkins explains that the research partners were frustrated by a lack of communication among cloud providers, and decided to use their collective buying power to commission a pan-European cloud for HPC and scientific computing. CloudSigma has been working with supply and demand side partners since June 2011, to assess the HPC requirements of the research institutions and from there design a cloud computing environment that meets these specific needs.

At this stage, they’ve completed a successful proof-of-concept pilot with CERN, which is using the additional computing power to process data from the Large Hadron Collider as part of the search for the theoretical Higgs boson. They’re currently working with EMBL to enable more accurate gene sequencing methodology and with ESA to process large amounts of earth science data to support natural disaster research. While Jenkins was reticent to comment on the individual compute requirements of the three partners, he estimates that the total combined computing power for the project will be in the neighborhood of 50,000 – 100,000 CPU cores.

The data requirements of these institutions are accelerating rapidly, a bit like a car accelerating out in front of them, as Jenkins puts it. At EMBL, the wet lab output and the data from extracting DNA is doubling every six months or so. This puts pressure on the later stages, in terms of assembly and sequencing, and so forth. The research sites must spend more and more time and effort chasing after the extra computing capacity, which increasingly distracts them from their primary mission, the science.

In a nutshell, there’s a shortfall in computing capacity. Not to mention some of these very important projects and problems that they are trying to solve are limited by the amount of actual computing power they can deploy because of coordination problems and practical issues. As just one example of the latter, CERN cannot do more science at the moment because Geneva cannot give them more electricity.

“It’s kind of crazy that these problems are holding back some of the most important scientific research areas for mankind,” remarks Jenkins, “The idea of Helix Nebula is that we can bring the collective computing power of these different providers and the cloud delivery mechanism, with the flexibility and transparency that it enables, to be able to allow these institutions to essentially burst into cloud and pull down those extra computing resources.”

A committee of supply side and demand side partners meets regularly to map out the cloud system architectures. They evaluate the information coming in from the different proof-of-concepts to determine how the various partners are getting their work done and the requirements that involves. Then they document the performance requirements in terms of networking, CPU, RAM, etc. – all these different aspects of computing are captured and fed back to the group.

Jenkins stresses the importance of coordination and the role of networking to support that. “One of things we’re working on at Helix Nebula is creating proper coordination between the cloud and the different providers so that we’re able to hand off data and transfer it to each other very efficiently and reliably,” he says. The participants all sit down to optimize their networking, to make it easier for data to get where it needs to go.

“There’s a big win to be had from cloud providers coordinating to make their clouds much more user-friendly when you’re actually using more than one cloud. That doesn’t generally happen,” notes Jenkins.

CERN’s Bob Jones shares a similar outlook: “The extreme scale of the computing needs of CERN, in terms of processing power, data transfer rates and data storage capacity, pushes what can be done with cloud computing beyond its current limits. Science relies on collaboration, so the cloud services being deployed need to able to allow groups of researchers around the world to share their data and results in a secure manner. The sharing of resources in a secure manner is challenging what can be done with cloud computing today.”

When it comes to cloud technology, one of the strengths of Helix Nebula is that it’s very open, Jenkins explains. It doesn’t have any specific cloud technology requirements, stipulating what software providers must run. It’s more about the use case, being able to process a given data type with a specified level of performance. The methodology is cross-technology, with some providers using VMware, others using KVM, OpenStack or OpenNebula, all coordinating together to create a common framework. In the future, Jenkins says they may choose a cross-cloud driver, but during this proof-of-concept phase, which is where they’re at now, they want to capture all the requirements first.

The initial work dovetails with the project’s strategic objective, which states: “The European Research Area shall drive the development and implementation of a secure and globally recognised European Cloud Computing Infrastructure, initially targeting science users. This infrastructure will become ‘the’ platform for Europe, under public governance, ensuring open standard and interoperability and adhering to European policies, norms and requirements.”

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!

Advancing Modular Supercomputing with DEEP and DEEP-ER Architectures

February 24, 2017

Knowing that the jump to exascale will require novel architectural approaches capable of delivering dramatic efficiency and performance gains, researchers around the world are hard at work on next-generation HPC systems. Read more…

By Sean Thielen

Weekly Twitter Roundup (Feb. 23, 2017)

February 23, 2017

Here at HPCwire, we aim to keep the HPC community apprised of the most relevant and interesting news items that get tweeted throughout the week. Read more…

By Thomas Ayres

HPE Server Shows Low Latency on STAC-N1 Test

February 22, 2017

The performance of trade and match servers can be a critical differentiator for financial trading houses. Read more…

By John Russell

HPC Financial Update (Feb. 2017)

February 22, 2017

In this recurring feature, we’ll provide you with financial highlights from companies in the HPC industry. Check back in regularly for an updated list with the most pertinent fiscal information. Read more…

By Thomas Ayres

HPE Extreme Performance Solutions

O&G Companies Create Value with High Performance Remote Visualization

Today’s oil and gas (O&G) companies are striving to process datasets that have become not only tremendously large, but extremely complex. And the larger that data becomes, the harder it is to move and analyze it – particularly with a workforce that could be distributed between drilling sites, offshore rigs, and remote offices. Read more…

Rethinking HPC Platforms for ‘Second Gen’ Applications

February 22, 2017

Just what constitutes HPC and how best to support it is a keen topic currently. Read more…

By John Russell

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

IDC: Will the Real Exascale Race Please Stand Up?

February 21, 2017

So the exascale race is on. And lots of organizations are in the pack. Government announcements from the US, China, India, Japan, and the EU indicate that they are working hard to make it happen – some sooner, some later. Read more…

By Bob Sorensen, IDC

ExxonMobil, NCSA, Cray Scale Reservoir Simulation to 700,000+ Processors

February 17, 2017

In a scaling breakthrough for oil and gas discovery, ExxonMobil geoscientists report they have harnessed the power of 717,000 processors – the equivalent of 22,000 32-processor computers – to run complex oil and gas reservoir simulation models. Read more…

By Doug Black

Advancing Modular Supercomputing with DEEP and DEEP-ER Architectures

February 24, 2017

Knowing that the jump to exascale will require novel architectural approaches capable of delivering dramatic efficiency and performance gains, researchers around the world are hard at work on next-generation HPC systems. Read more…

By Sean Thielen

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

IDC: Will the Real Exascale Race Please Stand Up?

February 21, 2017

So the exascale race is on. And lots of organizations are in the pack. Government announcements from the US, China, India, Japan, and the EU indicate that they are working hard to make it happen – some sooner, some later. Read more…

By Bob Sorensen, IDC

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

Drug Developers Use Google Cloud HPC in the Fight Against ALS

February 16, 2017

Within the haystack of a lethal disease such as ALS (amyotrophic lateral sclerosis / Lou Gehrig’s Disease) there exists, somewhere, the needle that will pierce this therapy-resistant affliction. Read more…

By Doug Black

Azure Edges AWS in Linpack Benchmark Study

February 15, 2017

The “when will clouds be ready for HPC” question has ebbed and flowed for years. Read more…

By John Russell

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

US, China Vie for Supercomputing Supremacy

November 14, 2016

The 48th edition of the TOP500 list is fresh off the presses and while there is no new number one system, as previously teased by China, there are a number of notable entrants from the US and around the world and significant trends to report on. Read more…

By Tiffany Trader

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

D-Wave SC16 Update: What’s Bo Ewald Saying These Days

November 18, 2016

Tucked in a back section of the SC16 exhibit hall, quantum computing pioneer D-Wave has been talking up its new 2000-qubit processor announced in September. Forget for a moment the criticism sometimes aimed at D-Wave. This small Canadian company has sold several machines including, for example, ones to Lockheed and NASA, and has worked with Google on mapping machine learning problems to quantum computing. In July Los Alamos National Laboratory took possession of a 1000-quibit D-Wave 2X system that LANL ordered a year ago around the time of SC15. Read more…

By John Russell

Enlisting Deep Learning in the War on Cancer

December 7, 2016

Sometime in Q2 2017 the first ‘results’ of the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) will become publicly available according to Rick Stevens. He leads one of three JDACS4C pilot projects pressing deep learning (DL) into service in the War on Cancer. Read more…

By John Russell

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

Leading Solution Providers

CPU Benchmarking: Haswell Versus POWER8

June 2, 2015

With OpenPOWER activity ramping up and IBM’s prominent role in the upcoming DOE machines Summit and Sierra, it’s a good time to look at how the IBM POWER CPU stacks up against the x86 Xeon Haswell CPU from Intel. Read more…

By Tiffany Trader

Nvidia Sees Bright Future for AI Supercomputing

November 23, 2016

Graphics chipmaker Nvidia made a strong showing at SC16 in Salt Lake City last week. Read more…

By Tiffany Trader

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

Dell Knights Landing Machine Sets New STAC Records

November 2, 2016

The Securities Technology Analysis Center, commonly known as STAC, has released a new report characterizing the performance of the Knight Landing-based Dell PowerEdge C6320p server on the STAC-A2 benchmarking suite, widely used by the financial services industry to test and evaluate computing platforms. The Dell machine has set new records for both the baseline Greeks benchmark and the large Greeks benchmark. Read more…

By Tiffany Trader

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

Intel and Trump Announce $7B for Fab 42 Targeting 7nm

February 8, 2017

In what may be an attempt by President Trump to reset his turbulent relationship with the high tech industry, he and Intel CEO Brian Krzanich today announced plans to invest more than $7 billion to complete Fab 42. Read more…

By John Russell

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