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!

Scalable Informatics Ceases Operations

March 23, 2017

On the same day we reported on the uncertain future for HPC compiler company PathScale, we are sad to learn that another HPC vendor, Scalable Informatics, is closing its doors. Read more…

By Tiffany Trader

‘Strategies in Biomedical Data Science’ Advances IT-Research Synergies

March 23, 2017

“Strategies in Biomedical Data Science: Driving Force for Innovation” by Jay A. Etchings (John Wiley & Read more…

By Tiffany Trader

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

Google Launches New Machine Learning Journal

March 22, 2017

On Monday, Google announced plans to launch a new peer review journal and “ecosystem” Read more…

By John Russell

HPE Extreme Performance Solutions

HFT Firms Turn to Co-Location to Gain Competitive Advantage

High-frequency trading (HFT) is a high-speed, high-stakes world where every millisecond matters. Finding ways to execute trades faster than the competition translates directly to greater revenue for firms, brokerages, and exchanges. Read more…

Swiss Researchers Peer Inside Chips with Improved X-Ray Imaging

March 22, 2017

Peering inside semiconductor chips using x-ray imaging isn’t new, but the technique hasn’t been especially good or easy to accomplish. Read more…

By John Russell

LANL Simulation Shows Massive Black Holes Break ‘Speed Limit’

March 21, 2017

A new computer simulation based on codes developed at Los Alamos National Laboratory (LANL) is shedding light on how supermassive black holes could have formed in the early universe contrary to most prior models which impose a limit on how fast these massive ‘objects’ can form. Read more…

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Intel Ships Drives Based on 3-D XPoint Non-volatile Memory

March 20, 2017

Intel Corp. has begun shipping new storage drives based on its 3-D XPoint non-volatile memory technology as it targets data-driven workloads. Read more…

By George Leopold

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

New Japanese Supercomputing Project Targets Exascale

March 14, 2017

Another Japanese supercomputing project was revealed this week, this one from emerging supercomputer maker, ExaScaler Inc., and Keio University. The partners are working on an original supercomputer design with exascale aspirations. Read more…

By Tiffany Trader

Nvidia Debuts HGX-1 for Cloud; Announces Fujitsu AI Deal

March 9, 2017

On Monday Nvidia announced a major deal with Fujitsu to help build an AI supercomputer for RIKEN using 24 DGX-1 servers. Read more…

By John Russell

HPC4Mfg Advances State-of-the-Art for American Manufacturing

March 9, 2017

Last Friday (March 3, 2017), the High Performance Computing for Manufacturing (HPC4Mfg) program held an industry engagement day workshop in San Diego, bringing together members of the US manufacturing community, national laboratories and universities to discuss the role of high-performance computing as an innovation engine for American manufacturing. Read more…

By Tiffany Trader

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

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

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

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

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

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

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

Leading Solution Providers

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

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

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

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

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

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

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

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