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Video: Massive I/O Requirements for the SKA Telescope

In this video from the 2013 Open Fabrics Developer Workshop, Bill Boas from Cray presents: Massive I/O Requirements for the SKA Telescope.

Processing the vast quantities of data produced by the SKA will require very high performance central supercomputers capable of 100 petaflops per second processing power. This is about 50 times more powerful than the most powerful supercomputer in 2010 and equivalent to the processing power of about one hundred million PCs.

Download the slides (PDF) or check out more OFA videos in our Open Fabrics Worshop Video Gallery.


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High Performance RDMA-based Design for Big Data and Web 2.0 memcached

In this video from the 2013 Open Fabrics Developer Workshop, D.K. Panda from Ohio State University presents: High Performance RDMA-based Design for Big Data and Web 2.0 memcached.

You can check out more OFA videos at our Open Fabrics Workshop Video Gallery.


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Video: Accelerating Big Data over RDMA

In this video from the 2013 Open Fabrics Developer Workshop, Sreev Doddabalapur from Mellanox presents: Accelerating Big Data over RDMA.

You can check out more OFA videos at our Open Fabrics Workshop Video Gallery.


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Big Data Freeway Under Construction in San Diego

If you’ve ever driven the freeways of Southern California, you might wonder about the metaphor chosen to describe the new high speed, Big Data network announced this week by the University of California, San Diego.

Known as the Prism@UCSD project, the university is building a high performance cyberinfrastructure to support bursts of Big Data between campus facilities housing diverse disciplines – such as science, engineering, medicine and the arts – without killing the main campus network.

With $500,000 in funding from the National Science Foundation (NSF), the UCSD division of the California Institute for Telecommunications and Information Technology (Calit2) is developing Prism specifically to support researchers in such data-intensive scientific areas as genomic sequencing, climate science, electron microscopy, oceanography and physics.

We’ve identified a variety of big data users on this campus who need ten gigabit/s and faster bandwidth to deal with the avalanche of data coming from scientific instruments such as sequencers, microscopes and computing clusters,” said Philip Papadopoulos, principal investigator on the Prism@UCSD project, who splits his time between Calit2 and the university’s San Diego Supercomputer Center (SDSC). “We’re starting at 1 Terabit/s of connected capacity through our next-generation modular switch, which is at the center of the Prism network. It can carry 20 times the traffic of our current research network, and it’s 100 times the bandwidth of the main campus network.”

Adds Papadopoulos, “You can think of Prism as the HOV lane, whereas our very capable campus network represents the slower lanes on the freeway.” Let’s hope he’s talking about the freeway at three in the morning.

Prism@UCSD is a response to the growing challenge of Big Data,” said Calit2 Director Larry Smarr. “The key innovation in Prism@UCSD is to provide end-to-end dedicated large bandwidth to the end-users on campus.”

And he too invokes the freeway metaphor: “The Prism Big Data network also creates a high-capacity ‘data freeway’ to campus, national or international networks,” adds Smarr.

A roadway that has an aggregate bandwidth equivalent to over one terabit per second could go a long way to clearing up Southern California’s traffic problems.

Read the Full Story.


Also posted in Education, Hardware, I/O, Research | Leave a comment

Video: Hadoop Acceleration with RDMA

In this video, Eyal Gutkind from Mellanox presents: Hadoop Acceleration with RDMA. The presentation was recorded at the HPC Advisory Council Stanford Conference 2013. Download the slides (PDF).


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Mellanox Accelerates Teradata Unified Big Analytics Appliance


Clipped from http://www.teradata.com/Aster-Big-Analytics-Appliance/

Today Mellanox announced that Teradata has chosen its InfiniBand interconnect solution to accelerate the Teradata Aster Big Analytics Appliance. Designed for demanding analytics which require high computational power and the fastest data movement, the Teradata Aster Big Analytics Appliance offers up to 19 times better data throughput and performs analytics up to 35 times faster than typical off-the-shelf commodity bundles.

Teradata Aster Big Analytics Appliance is part of a truly unified, high-performance big data analytics architecture for the enterprise and will help customers achieve business value,” said Carson Schmidt, vice president of platform engineering at Teradata. “The Mellanox InfiniBand interconnect is the best choice to enable the performance that is needed to analyze big data at a speed that no other analytic platform can deliver. This performance maximizes the return on investment and accelerates time to value.”

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CERN to Move Big Data through Terabit Network

Over at Datacenter Knowledge, Rich Miller writes that CERN’s new data center in Budapest is set to be one of the first beneficiaries of a new terabit network created by GÉANT, a European data network for researchers and scientists.

GÉANT’s migration to the latest transmission and switching technology is designed to support up to 2Tbps (terabits per second) capacity across the core network. 500Gbps capacity will be available across the core network from first implementation, delivering circuits across Europe that will allow individual users to transfer data at speeds of up to 100Gbps, or multiples thereof, thereby enabling faster collaboration on critical projects and meeting the rapidly increasing demand for data transfer.

Talk about Big Data–the CERN Large Hadron Collider generates over 100 petabytes of data per year at its home near Geneva, Switzerland. Read the Full Story.


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Massive 790 Gigabit Network Capacity Lights Up SC12

The SC12 conference this week in Salt Lake City will be home to one of the fastest computer networks in the world.

Known as SCinet, the network is built each year to support the international conference for high performance computing, networking, storage and analysis. Over 100 engineers representing industry, academia and government institutions have volunteered their time over the past year to plan and build SCinet using nearly $28 million in donated equipment. The network will serve as the primary backbone supporting all 10,000+ SC conference attendees as they unveil their latest innovations in high performance computing applications.

Unlike typical Internet traffic, scientific workflows tend to demand high capacity network links for long duration large data flows,” said Linda Winkler, Senior Network Engineer at Argonne National Laboratory and chair of SCinet for SC12. “The SCinet infrastructure was architected to meet these demanding requirements.”

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Spectra Logic Rolls Out 10GbE Connectivity to Tape Solution

Today Spectra Logic announced the introduction of support for 10 Gigabit Ethernet iSCSI connectivity as an interface option for the Spectra T-Series tape libraries. Offered in partnership with Bridgeworks, the solution enables simple integration of tape systems into 10GbE SANs.

We’re excited to continue on the path of keeping tape storage systems easy to integrate in the modern data center. By supporting the Bridgeworks solution for 10GbE iSCSI connectivity to our T-series tape libraries, our customers who are designing data center solutions based on 10GbE iSCSI no longer need to maintain a FC SAN just for their tape storage system,” said Molly Rector, executive vice president of product management and worldwide marketing, Spectra Logic.

The 10GbE iSCSI to FC bridge is available for purchase through Bridgeworks. Read the Full Story.


Also posted in Business of Big Data, Hardware, Storage, Tape | Leave a comment

A ‘Maverick Fabric’ for Big Data Analytics

Over at Network World, Gnodal CEO Bob Fernande writes, just as in HPC clusters, plain old Ethernet doesn’t cut it for Big Data Analyitics. He then proposes a different approach with a new “maverick fabric.”

Such a fabric should have a way to eliminate network congestion within a multi-switch Ethernet framework to free up available bandwidth in the network fabric. It also should significantly improve performance by negotiating load-balancing flows between switches with no performance hit and, use a “fairness” algorithm that prioritizes packets in the network and ensures that broadcast data or other large frame traffic, such as localized storage sub-systems, will not unfairly consume bandwidth.

Read the Full Story.


Also posted in Analytics, Hardware | 2 Comments

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