Despite several rendering issues on the SlideShare site, the presentation is available here:

(See also: SlideShare: Cloud Computing Services and the Data Center)

The following weekend an interesting article about data centers appeared in the New York Times magazine:

(See also: NYtimes Magazine: Data Center Overload)
(See also: NYtimes Magazine: Data Center Overload slides)

NASA is developing a new integrated Cloud Computing environment they call NEBULA at NASA Ames Research Center. NEBULA is an open-source project, built from the ground up with common tools: Eucalyptus, JAVA, LDAP, Lustre, MySQL, Python, SAML, Subversion, and TRAC. It will provide high-capacity computing, storage and network connectivity, and use a ‘virtualized, scalable approach to achieve cost and energy efficiencies’.

According to the NEBULA website:

The fully-integrated nature of the NEBULA components provides for extremely rapid development of policy-compliant and secure web applications, fosters and encourages code reuse, and improves the coherence and cohesiveness of NASA’s collaborative web applications. It is used for Education and Public Outreach, for collaboration and public input, and also for mission support.

NEBULA extends the Software-as-a-Service to the realm of Platform-as-a-Service and Infrastructure-as-a-Service. In the process, slaying several classic conundrums of computational collaboration.

I wish them the best of luck.

(See also: NEBULA site)
(See also: InformationWeek: NASA Launches Nebula Compute Cloud)
(See also: Open Eucalyptus project)
(See also: Eucalyptus Cloud Computing presentation)

It’s been an interesting evening while Stephen Wolfram launches his new computational knowledge engine ‘WolframAlpha‘. There were some fits and starts, but I have been able to ask it some interesting questions.

The approach reminds me of Thinking Machines Wide Area Information Server (WAIS) and Gopher from the late 1980’s. I know that Stephen Wolfram worked at Thinking Machines and I don’t know if he was involved with the WAIS project, but it certainly was a fundamental influence on WolframAlpha. WAIS was ultimately sold to AOL in 1995, just as the World Wide Web was forming.

WolframAlpha is easily stumped. But then you ask it a question that fans out into an amazing array of results from wide and varied data sources. TEDChris has side by side comparison of seven queries given to WolframAlpha and Google. A helpful illustration of the differences between the two philosophies. When the answer isn’t a precise number, WolframAlpha will try to reduce the question to something it can answer precisely. If the answer is a precise or computed number WolframAlpha can produce an elegant and concise response, though much of the supporting data appears to be older sources than those revealed in similar Google searches. While powerful in certain domains (such as math, chemistry, census data), the result is a service that may produce what you need or nothing useful at all. Here are some funny queries of interest:

There is a certain level of hubris in the idea all knowledge can be contained, maintained, and computed centrally. WolframAlpha is a ‘come to the mountain’ experience. In contrast, Google’s shotgun response relies on the distributed nature of the internet, counting and weighing the edges between ideas, often responding with a myriad of links relying on the user to be the final filter.

Both systems have a place in my toolbox.

(See also: WolframAlpha: query interface)
(See also: Introducing WolframAlpha)
(See also: WAIS: Wide Area Information Server)
(See also: TEDChris: WolframAlpha vs Google)
(See also: TechCrunch: Putting Wolfram Alpha To The Test: Not Super-Impressed)

The TOP500.org list is an ordered collection of the 500 most powerful general purpose systems in use today. Rank is determined by the number of floating point operations per second (FLOPS) sustained while solving a dense system of linear equations in the LINPACK benchmark suite. The TOP500.org list is updated every six months.

There is now a Green500.org list ranking machines on the TOP500.org list based on energy efficiency, in FLOPS per Watt. LINPACK makes use of the BLAS (Basic Linear Algebra Subprograms) libraries to perform vector and matrix operations. The three benchmarks that comprise LINPACK were designed for use on vector processors in the 1970s and early 1980s.

If LINPACK is representative of the types of calculations and loads produced by your application suites, then Green500.org ranking may be a valid measure of performance efficiency. If LINPACK loads are not representative of your work, it would be interesting to explore a metric more appropriate to modern hardware and application loads. Perhaps LAPACK-based FLOPS over Watts metric?

(See also: TOP500.org)
(See also: Green500.org)

(See also: LINPACK: Fortran subroutines that analyze and solve linear equations.)
(See also: LINPACK: latest report)
(See also: LAPACK: Linear Algebra PACKage)
(See also: BLAS: Basic Linear Algebra Subprograms)

(See also: EnergyStar.gov)
(See also: GreenerComputing.com)

(See also: IEEE: Green Supercomputing Comes of Age)
(See also: IEEE: The Green500 List – Encouraging Sustainable Supercomputing)

(See also: Honey, I Shrunk the Beowulf)

Features of the Silicon Graphics Molecule concept include:

• High concurrency with 20,000 threads of execution — 40 times more than a single rack x86 cluster system
  
• High throughput with 15TB/sec of memory bandwidth per rack — over 20 times faster than a single rack x86 cluster system
  
• Greater balance with up to three times the memory bandwidth/OPS compared to current x86 CPUs
  
• High performance with approximately 3.5 times the computational performance per rack
  
• Greener with low-watt consumer CPUs and low-power memory that deliver 7 times better memory bandwidth/watt
  
• Innovative Silicon Graphics Kelvin cooling technology, which enables denser packaging by stabilizing thermal operations in densely configured solutions
  
• Operating environment flexibility, capable of running industry-standard Linux® implementations, with Microsoft® Windows® variants on some configurations
  

Classic problems appear to be solved. Speeds and feeds, heat and power. Not sure how they solve memory bandwidth bottlenecks at this density. Likely a NUMA (CC-NUMA?) architecture, but that would likely force memory down to the already improbably crowded processing modules. Cooling will be critical in a system such as this. Silicon Graphics® Kelvin™ cooling technology professes to solve this problem.

Granted, this is a prototype and may never be built for sale. It may never be built at all. I remain skeptical. I wish I were at SuperComputing 08 in Austin, TX this week to see it up close. If you are, please leave a comment.

(See also: SGI: a Glimpse of the Future)
(See also: Wired: SGI Creates 10,000-core Concept Computer)