Canada Explores New Frontiers in Astroinformatics

By Nicole Hemsoth

January 17, 2011

In nearly every research discipline, the number of scientific instruments available to add to the stream of data input has been climbing. While this has spurred any number of software developments in recent years, without adequate hardware processing capabilities to handle the delgue, there can be no match for the possibilities that lie in the incoming data.

Accordingly, a number of research institutions are findings new ways to handle the data deluge, both in terms of reinventing grid-based paradigms and looking to cloud computing models to extend already stretched computational resources.

Astronomy is one of several areas that is suffering from the glut of data brought about by more streamlined, complex, and numerous instruments and not surprisingly, researchers are looking to grid and cloud models to handle the well of data.

Researchers Nicholas Ball and David Schade discussed the concept of astroinformatics in detail, stating that, “in the past two decades, astronomy has gone from being starved for data to being flooded by it. This onslaught has now reached the stage where the exploitation of these data has become a named discipline in its own right…This naming follows in analogy from the already established fields of bio- and geoinformatics, which contain their own journals and funding.”

Canada’s astronomy community is, like other nations with advanced astronomy research programs, looking for ways to approach their big data problem in an innovative way that combines elements of both grid and cloud computing. Their efforts could reshape current views of astroinformatics processing and help the country move toward its goals of becoming a global center for advancements in astronomical research. 

The Canadian Advanced Network for Astronomical Research (CANFAR) is behind an ongoing project in conjunction with CANARIE (a national research network organization) to create a cloud-based platform to support astronomy research. The effort is being led by researchers at the University of Victoria in British Columbia in conjunction with the Canadian Astronomy Data Centre (CADC) and with participation from 11 other Canadian universities.

The goal of the project is to “leverage customized virtual compute and storage clouds, providing astronomers with access to many datasets and resources previously constrained by their local hardware environment.”

The CANFAR platform will take advantage of CANARIE’s high-speed network and a number of open source and proprietary cloud and grid computing tools to allow the country’s astronomy researchers to better handle the vast datasets that are being generated by global observatories. It will also be propelled by the storage and compute capabilities from Compute Canada in addition to the expertise from the Herzberg Institute of Astrophysics and the National Research Council of Canada.

CANFAR is driven forward by a number of objectives to support its mission to create a “global machine” that will help researchers further their astronomy goals. The creators of the project stated, “All of the necessary components exist to support science but they don’t work well together in that mission. The type of service layer that is needed to support a high level of integration of these components for astronomy does not exist and needs to be invented, installed, and operated”

What CANFAR Can Do

The value proposition of CANFAR is that it will enable astronomers to process the data from astronomical surveys using a wide array of custom software packages and, of course, to widen the set of computational resources available for these purposes.

A report on the project described CANFAR as “an operational system for the delivery, processing, storage, analysis, and distribution of very large astronomical datasets” and as a project that pulls together a number of Canadian entities, including the Canadian National Research Network (CANARIE), Compute Canada’s extensive grid and storage capabilities, and the CADC data center to create a “unified storage and processing system.”

The report also describes the CANFAR project’s technical details, stating that it has “combined the best features of the grid and cloud processing models by providing a self-configuring virtual cluster deployed on multiple cloud clusters” that takes elements from grid-based services  as well as a number of cloud services, including “Condor, Nimbus or OpenNebula, Eucalyptus or Amazon EC2, Xen, VOSpace, UWS, SSO, CDP and GMS.”

The researchers behind the CANFAR project noted that when considering different virtualization options, they considered both Xen and KVM, but settled on Xen because of its wider popularity at the time and because it was the only one that facility operators had used on an experimental basis in the past.

On the scheduler front, there were complexities because the CANFAR virtual cluster needed a batch job processing system that would provide the functionality of a grid cluster, thus making both Grid Engine and Condor natural options. The team settled on Condor, however, because upon examination of the environment, they found that using Grid Engine would mean that they would have to modify the cluster configuration anytime a VM was added or removed.

The team selected Nimbus as the “glue between cloud clusters” which “examined the workload in the Condor queue and used resources from multiple cloud clusters to create a virtual cluster suitable for the current workload” and used the Nimbus toolkit as the primary cloud technology behind the cloud scheduler.

The team also developed support for openNebula, Eucalyptus and Ec2, but decided on Nimbus because it was open source and permitted the “cloud workload to be intermixed with conventional batch jobs unlike other systems. “ The research team behind CANFAR stated that they believed “that this flexibility makes the deployment more attractive to facility operators.”

With Linux as the operating system and an emphasis on interoperability and open source, CANFAR will be a proving ground for the use of these scheduling and cloud-based management tools on large datasets. In addition to other projects that make use of similar (although diverse in terms of packages used) interoperability and open source paradigms like NASA’s Nebula cloud, there will likely be a number of exciting proof of concept reports that will emerge over the course of the next year.

CANARIE’s vision for the project is that it will also “provide astronomers with novel and more immediate hands-on and interactive ways to process and share very large amounts of data emerging from space exploration.”

In addition to helping research better manage the incredible amounts of data filtering in from collection sites, the project’s goals are also tied to aiding collaboration opportunities among geographically dispersed scientists.

As the CANFAR team noted, “a schematic of contemporary astronomy research shows that the system is essentially a networked global array of infrastructure with scientists and telescopes as I/O devices.”

Slides describing some of the current research challenges and potential benefits as well as some of the context for the project can be found here.

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!

IBM Launches Commercial Quantum Network with Samsung, ORNL

December 14, 2017

In the race to commercialize quantum computing, IBM is one of several companies leading the pack. Today, IBM announced it had signed JPMorgan Chase, Daimler AG, Samsung and a number of other corporations to its IBM Q Net Read more…

By Tiffany Trader

TACC Researchers Test AI Traffic Monitoring Tool in Austin

December 13, 2017

Traffic jams and mishaps are often painful and sometimes dangerous facts of life. At this week’s IEEE International Conference on Big Data being held in Boston, researchers from TACC and colleagues will present a new Read more…

By HPCwire Staff

AMD Wins Another: Baidu to Deploy EPYC on Single Socket Servers

December 13, 2017

When AMD introduced its EPYC chip line in June, the company said a portion of the line was specifically designed to re-invigorate a single socket segment in what has become an overwhelmingly two-socket landscape in the d Read more…

By John Russell

HPE Extreme Performance Solutions

Explore the Origins of Space with COSMOS and Memory-Driven Computing

From the formation of black holes to the origins of space, data is the key to unlocking the secrets of the early universe. Read more…

Microsoft Wants to Speed Quantum Development

December 12, 2017

Quantum computing continues to make headlines in what remains of 2017 as several tech giants jockey to establish a pole position in the race toward commercialization of quantum. This week, Microsoft took the next step in Read more…

By Tiffany Trader

IBM Launches Commercial Quantum Network with Samsung, ORNL

December 14, 2017

In the race to commercialize quantum computing, IBM is one of several companies leading the pack. Today, IBM announced it had signed JPMorgan Chase, Daimler AG, Read more…

By Tiffany Trader

AMD Wins Another: Baidu to Deploy EPYC on Single Socket Servers

December 13, 2017

When AMD introduced its EPYC chip line in June, the company said a portion of the line was specifically designed to re-invigorate a single socket segment in wha Read more…

By John Russell

Microsoft Wants to Speed Quantum Development

December 12, 2017

Quantum computing continues to make headlines in what remains of 2017 as several tech giants jockey to establish a pole position in the race toward commercializ Read more…

By Tiffany Trader

HPC Iron, Soft, Data, People – It Takes an Ecosystem!

December 11, 2017

Cutting edge advanced computing hardware (aka big iron) does not stand by itself. These computers are the pinnacle of a myriad of technologies that must be care Read more…

By Alex R. Larzelere

IBM Begins Power9 Rollout with Backing from DOE, Google

December 6, 2017

After over a year of buildup, IBM is unveiling its first Power9 system based on the same architecture as the Department of Energy CORAL supercomputers, Summit a Read more…

By Tiffany Trader

Microsoft Spins Cycle Computing into Core Azure Product

December 5, 2017

Last August, cloud giant Microsoft acquired HPC cloud orchestration pioneer Cycle Computing. Since then the focus has been on integrating Cycle’s organization Read more…

By John Russell

GlobalFoundries, Ayar Labs Team Up to Commercialize Optical I/O

December 4, 2017

GlobalFoundries (GF) and Ayar Labs, a startup focused on using light, instead of electricity, to transfer data between chips, today announced they've entered in Read more…

By Tiffany Trader

HPE In-Memory Platform Comes to COSMOS

November 30, 2017

Hewlett Packard Enterprise is on a mission to accelerate space research. In August, it sent the first commercial-off-the-shelf HPC system into space for testing Read more…

By Tiffany Trader

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

AMD Showcases Growing Portfolio of EPYC and Radeon-based Systems at SC17

November 13, 2017

AMD’s charge back into HPC and the datacenter is on full display at SC17. Having launched the EPYC processor line in June along with its MI25 GPU the focus he 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

Japan Unveils Quantum Neural Network

November 22, 2017

The U.S. and China are leading the race toward productive quantum computing, but it's early enough that ultimate leadership is still something of an open questi Read more…

By Tiffany Trader

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

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

IBM Begins Power9 Rollout with Backing from DOE, Google

December 6, 2017

After over a year of buildup, IBM is unveiling its first Power9 system based on the same architecture as the Department of Energy CORAL supercomputers, Summit a Read more…

By Tiffany Trader

Perspective: What Really Happened at SC17?

November 22, 2017

SC is over. Now comes the myriad of follow-ups. Inboxes are filled with templated emails from vendors and other exhibitors hoping to win a place in the post-SC thinking of booth visitors. Attendees of tutorials, workshops and other technical sessions will be inundated with requests for feedback. Read more…

By Andrew Jones

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

Tensors Come of Age: Why the AI Revolution Will Help HPC

November 13, 2017

Thirty years ago, parallel computing was coming of age. A bitter battle began between stalwart vector computing supporters and advocates of various approaches to parallel computing. IBM skeptic Alan Karp, reacting to announcements of nCUBE’s 1024-microprocessor system and Thinking Machines’ 65,536-element array, made a public $100 wager that no one could get a parallel speedup of over 200 on real HPC workloads. Read more…

By John Gustafson & Lenore Mullin

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

Flipping the Flops and Reading the Top500 Tea Leaves

November 13, 2017

The 50th edition of the Top500 list, the biannual publication of the world’s fastest supercomputers based on public Linpack benchmarking results, was released 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

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