The Open Data Center Alliance (ODCA) is holding its Forecast event in San Francisco in June, and I’ve been invited to moderate the panel discussing Virtual Machine Interoperability. As moderator, I’ll be far more interested in facilitating insights from panel and audience than in wittering on about what I think, so I wanted to use this blog post to begin getting some of the issues clear in my mind. What is VM interoperability, and why does it matter? From time to time, I write about Open Data. This has nothing to do with that. The Open Data Center Alliance is interested in data centres, not data. The Alliance was established back in 2010 with Intel driving things forward, and now claims over 300 member organisations, including the likes of BMW, Lockheed Martin, Microsoft, Deutsche Bank and Marriott Hotels. According to the ODCA website, we came together to deliver a unified voice for emerging data center and cloud computing requirements. Our mission is to speed the migration to cloud computing by enabling the solution and service ecosystem to address IT requirements with the highest level of interoperability and standards. Much of the Alliance’s work involves identifying customer requirements and capturing these in a series of usage […]

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A computer exists that’s been able to solve complex problems set for it by Google and NASA 11,000 times faster than any traditional supercomputer. And those were the simple problems.

On harder problems, it was 33,000 times faster and on the really hard problems it was reportedly 50,000 times faster.

It’s a so-called quantum computer build on the principles of quantum mechanics and Google and NASA thought enough of the thing to buy one at a cost of maybe $10 million-$15 million and set up a Quantum Artificial Intelligence Lab at NASA’s Ames Research Center.

There they’re going to try to advance machine learning, which, as Google says, is all about building better models of the world to make more accurate predictions. And that, from Google’s point-of-view, includes understanding spoken questions and what’s on the web so it can build a more useful and accurate search engine.

Other people want to use it to cure diseases and create effective environmental policies, both of which need better models, and they’ll get a chance because the Universities Space Research Association (USRA) will get time on the machine and make it available to researchers from around the world.

Together they’ll try move from theory to practice, building real solutions on quantum hardware.

Google says hopefully, “We actually think quantum machine learning may provide the most creative problem-solving process under the known laws of physics.”

The machine they’ll be working on was built in Canada by D-Wave Systems, where Egenera founder and former Goldman Sachs CIO Vern Brownell is CEO.

It’s a second-generation machine. D-Wave only sold one of its first-generation 128-qubit D-Wave One commercial systems. That went to Lockheed Martin, which recently upgraded it to the new D-Wave Two machine Google and NASA are getting.

D-Wave sees the technology being heavily applied to the cloud. In fact it talks of a quantum cloud with a few high-end traditional servers at the back-end. Coincidently enough Google figures the best use of quantum computing is to combine quantum machines with the traditional machines in its clouds.

The D-Wave computer works by considering complex problems in terms of optimal outcomes. It can just consider more possible outcomes simultaneously and shake out the one that meets all the variables faster and with the least expenditure of energy than any other modern computer.

It considers the problem in terms of energy states and applies quantum physics to magically come up with the answer.

The technique is called quantum annealing.

And a quantum computer isn’t like a standard computer that represents data in bits that are either on or off, 1 or 0. Nope, a 10-quantum bit computer, or 10-qubit computer, can simultaneously represent data in 1,024 states,

Inside the D-Wave Two box are now 512 problem-solving qubits and its superconducting processor reportedly has to be cooled to near absolute zero.

NASA and Google reportedly mean to upgrade to 2.048 qubits sometime in the next year or two.

D-Wave has been working the kinks out of the esoteric widgetry since 1999 and in the process has gotten at least $61 million – well, maybe it’s closer to $100 million – in funding from such as Amazon CEO Jeff Bezos through his venture arm Bezos Expeditions, In-Q-Tel, the CIA’s venture boys, and of course Goldman Sachs.

Other believers who contributed include Draper Fisher Jurvetson, Harris &Harris Group, the Business Development Bank of Canada, BC Investment Management Corporation and Growth Works Capital among others.

The NASA-Google machine is currently being installed at Moffet Field and should be in use by fall. It is expected to be considered by financial services, healthcare and national security.

D-Wave just set up a US company in Palo Alto earlier this month to overcome any national security objections to dealing with a Canadian concern. It hired Bo Ewald as president and head of global customer operations.

Bo has run SGI and was president, COO and CTO at Cray Research, CEO and chairman of Linux Networx, e-Stamp, and most recently Perceptive Pixel. He started his career at the Los Alamos National Lab.

The company has also hired Steve Cakebread, another SGI veteran, as CFO. He used to be president and CFO of Salesforce.com and after that CFO of Pandora.

See http://googleresearch.blogspot.com/2013/05/launching-quantum-artificial…..

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SAP, the third-largest software company in the world after Microsoft and

Oracle, says it’s moving all data into main memory and all systems to the

cloud.

The company’s newly announced HANA Cloud Platform is going to be

the foundation of its whole cloud portfolio, creating a single point for its

cloud-based technology, including application development and integration

services, database and analytics services.

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By Andrew Carr, CEO Bull UK & Ireland @acarr_bull

Businesses today increasingly look at technologies like big data and software-defined networking as being disruptive in the sense that they force organisations to evaluate new business models and new routes to market.

Rather than having negative associations, disruptive in this context means having an impact through a different way of thinking about business issues and challenges, as opposed to the traditional dictionary definition of ‘throwing into confusion or disorder’.

This new interpretation of the word is focused on the development of new ways of working, ultimately leading to new revenue streams and enhanced competitive edge. Indeed, truly disruptive technologies will have a lasting impact on the IT and business landscape and will ultimately be absorbed into the mainstream.

This is what is happening today with one of the most celebrated disruptive technologies of all: cloud computing, which is now widely seen as …

As anyone with a vested interest in cloud computing will know, the perception of the data centre has evolved considerably, from isolated resource centres to more connected pools, helping maximise IT efficiency.

Not surprisingly, with the potential available, the numbers are growing. 60% of server workloads are set to be virtualised by 2014, compared to only 12% in 2008m, with total investment in data centre infrastructure growing 5% on average year on year.

There are, of course, pros and cons to virtualisation, with companies continuing to balance out efficiency and agility against security considerations.

Network solutions provider Ciena, in an infographic, has stated that “the cloud is only as good as the network that supports it,” calling its solution a “data centre without walls”.

Find out the journey from data centre to cloud in the infographic below (click to enlarge):

Tony Baer, Principal Analyst, IT – Enterprise Solutions

With the X3 generation of the Oracle Exadata and Exalogic engineered-systems platforms significantly upping the amount of Flash (SSD) and memory (DRAM), Oracle is now cranking up the speed on its applications portfolio. With Flash and DRAM prices plummeting, it is now cost-effective to persist, rather than temporarily cache, data. Oracle claims that much of its existing application portfolio can run up to 16x faster, unmodified, on the X3-2 Oracle Exadata and Exalogic models.

Oracle is now taking the next step in optimizing portions of its application portfolio to take full advantage of the new X3-2 line. Oracle’s Fast Data approach to enterprise applications follows SAP’s release of SAP Business Suite and CRM on the in-memory HANA platform. Ovum believes that Oracle’s approach is a logical first step, and would like to see this eventually yield a new generation of …

You may have heard that cloud computing and Software-as-a-Service (SaaS) models can turn software technology into a pay-as-you-go utility that businesses can “plug in to” and use like electricity?

Perhaps — however, software technology is far more varied, nuanced and diverse than electricity. You don’t win customers by having better electricity than your competition. Software, by contrast,…

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Activist shareholder Elliott Management, the hedge fund that pushed Novell

and BMC into selling out and has Compuware on its list, is muscling in on

NetApp.

According to Bloomberg it has taken a “significant” position still under 5%

in the data storage house, meaning to push for changes to the board and a

cash return strategy.

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