For the longest time, people thought that humans could not run a mile in less than four minutes. Then, in 1954, [Sir Roger Bannister] beat that perception, and shortly thereafter, once he showed it was possible, many other runners were able to achieve this also. The same is being said now about the IBM Watson computer which appeared this week against two human contestants on Jeopardy!

(2014 Update: A lot has happened since I originally wrote this blog post! I intended this as a fun project for college students to work on during their summer break. However, IBM is concerned that some businesses might be led to believe they could simply stand up their own systems based entirely on open source and internally developed code for business use. IBM recommends instead the [IBM InfoSphere BigInsights] which packages much of the software described below. IBM has also launched a new "Watson Group" that has [Watson-as-a-Service] capabilities in the Cloud. To raise awareness to these developments, IBM has asked me to rename this post from IBM Watson - How to build your own "Watson Jr." in your basement to the new title IBM Watson -- How to replicate Watson hardware and systems design for your own use in your basement. I also took this opportunity to improve the formatting layout.)

Often, when a company demonstrates new techology, these are prototypes not yet ready for commercial deployment until several years later. IBM Watson, however, was made mostly from commercially available hardware, software and information resources. As several have noted, the 1TB of data used to search for answers could fit on a single USB drive that you buy at your local computer store.

But could you fit an entire Watson in your basement? The IBM Power 750 servers used in IBM Watson earned the [EPA Energy Star] rating, and is substantially [more energy-efficient than comparable 4-socket x86, Itanium, or SPARC servers]. However, having ninety of them in your basement would drive up your energy bill.

That got me thinking, would it be possible to build your own question-answering system, something less fancy, less sophisticated, scaled-down for personal use? John Pultorak explained [how to build your own Apollo Guidance Computer (AGC) in your basement]. Jay Shafer explains [how to build your own house for $20K]. And a 17-year-old George Hotz figured out a [hack to unlock your Apple iPhone] over the summer in his basement.

It turns out that much of the inner workings of IBM Watson were written in a series of articles in [IBM Systems Journal, Vol. 43, No. 3]. You can also read the [Wikipedia article]. Eric Brown from IBM Research will be presenting "Jeopardy: Under the Hood of IBM Watson Supercomputer" at next month's [The Linux Foundation End User Summit].

Take a look at the [IBM Research Team] to determine how the project was organized. Let's decide what we need, and what we don't in our version for personal use:

(Disclaimer: As with any Do-It-Yourself (DIY) project, I am not responsible if you are not happy with your version for personal use I am basing the approach on what I read from publicly available sources, and my work in Linux, supercomputers, XIV, and SONAS. For our purposes, this version for personal use is based entirely on commodity hardware, open source software, and publicly available sources of information. Your implementation will certainly not be as fast or as clever as the IBM Watson you saw on television.)

Step 1: Buy the Hardware

Supercomputers are built as a cluster of identical compute servers lashed together by a network. You will be installing Linux on them, so if you can avoid paying extra for Microsoft Windows, that would save you some money. Here is your shopping list:

• Three x86 hosts, with the following:
  • 64-bit quad-core processor, either Intel-VT or AMD-V capable,
  • 8GB of DRAM, or larger
  • 300GB of hard disk, or larger
  • CD or DVD Read/Write drive
  • 1GbE Ethernet
• Computer Monitor, mouse and keyboard
• Ethernet 1GbE 4-port hub, and appropriate RJ45 cables
• Surge protector and Power strip
• Local Console Monitor (LCM) 4-port switch (formerly known as a KVM switch) and appropriate cables. This is optional, but will make it easier during the development. Once your implementation is operational, you will only need the monitor and keyboard attached to one machine. The other two machines can remain "headless" servers.

 

Step 2: Establish Networking

IBM Watson used Juniper switches running at 10Gbps Ethernet (10GbE) speeds, but was not connected to the Internet while playing Jeopardy! Instead, these Ethernet links were for the POWER7 servers to talk to each other, and to access files over the Network File System (NFS) protocol to the internal customized SONAS storage  I/O nodes.

The implementation will be able to run "disconnected from the Internet" as well. However, you will need Internet access to download the code and information sources. For our purposes, 1GbE should be sufficient. Connect your Ethernet hub to your DSL or Cable modem. Connect all three hosts to the Ethernet switch. Connect your keyboard, video monitor and mouse to the LCM, and connect the LCM to the three hosts.

Step 3: Install Linux and Middleware

To say I use Linux on a daily basis is an understatement. Linux runs on my Android-based cell phone, my laptop at work, my personal computers at home, most of our IBM storage devices from SAN Volume Controller to XIV to SONAS, and even on my Tivo at home which recorded my televised episodes of Jeopardy!

For this project, you can use any modern Linux distribution that supports KVM. IBM Watson used Novel SUSE Linux Enterprise Server [SLES 11]. Alternatively, I can also recommend either Red Hat Enterprise Linux [RHEL 6] or Canonical [Ubuntu v10]. Each distribution of Linux comes in different orientations. Download the the 64-bit "ISO" files for each version, and burn them to CDs.

• Graphical User Interface (GUI) oriented, often referred to as "Desktop" or "HPC-Head"
• Command Line Interface (CLI) oriented, often referred to as "Server" or "HPC-Compute"
• Guest OS oriented, to run in a Hypervisor such as KVM, Xen, or VMware. Novell calls theirs "Just Enough Operating System" [JeOS].

For this version for personal use, I have chosen a [multitier architecture], sometimes referred to as an "n-tier" or "client/server" architecture.

Host 1 - Presentation Server

For the Human-Computer Interface [HCI], the IBM Watson received categories and clues as text files via TCP/IP, had a [beautiful avatar] representing a planet with 42 circles streaking across in orbit, and text-to-speech synthesizer to respond in a computerized voice. Your implementation will not be this sophisticated. Instead, we will have a simple text-based Query Panel web interface accessible from a browser like Mozilla Firefox.

Host 1 will be your Presentation Server, the connection to your keyboard, video monitor and mouse. Install the "Desktop" or "HPC Head Node" version of Linux. Install [Apache Web Server and Tomcat] to run the Query Panel. Host 1 will also be your "programming" host. Install the [Java SDK] and the [Eclipse IDE for Java Developers]. If you always wanted to learn Java, now is your chance. There are plenty of books on Java if that is not the language you normally write code.

While three little systems doesn't constitute an "Extreme Cloud" environment, you might like to try out the "Extreme Cloud Administration Tool", called [xCat], which was used to manage the many servers in IBM Watson.

Host 2 - Business Logic Server

Host 2 will be driving most of the "thinking". Install the "Server" or "HPC Compute Node" version of Linux. This will be running a server virtualization Hypervisor. I recommend KVM, but you can probably run Xen or VMware instead if you like.

Host 3 - File and Database Server

Host 3 will hold your information sources, indices, and databases. Install the "Server" or "HPC Compute Node" version of Linux. This will be your NFS server, which might come up as a question during the installation process.

Technically, you could run different Linux distributions on different machines. For example, you could run "Ubuntu Desktop" for host 1, "RHEL 6 Server" for host 2, and "SLES 11" for host 3. In general, Red Hat tries to be the best "Server" platform, and Novell tries to make SLES be the best "Guest OS".

My advice is to pick a single distribution and use it for everything, Desktop, Server, and Guest OS. If you are new to Linux, choose Ubuntu. There are plenty of books on Linux in general, and Ubuntu in particular, and Ubuntu has a helpful community of volunteers to answer your questions.

Step 4: Download Information Sources

You will need some documents for your implementation to process.

IBM Watson used a modified SONAS to provide a highly-available clustered NFS server. For this version, we won't need that level of sophistication. Configure Host 3 as the NFS server, and Hosts 1 and 2 as NFS clients. See the [Linux-NFS-HOWTO] for details. To optimize performance, host 3 will be the "official master copy", but we will use a Linux utility called rsync to copy the information sources over to the hosts 1 and 2. This allows the task engines on those hosts to access local disk resources during question-answer processing.

We will also need a relational database. You won't need a high-powered IBM DB2. Your implementation can do fine with something like [Apache Derby] which is the open source version of IBM CloudScape from its Informix acquisition. Set up Host 3 as the Derby Network Server, and Hosts 1 and 2 as Derby Network Clients. For more about structured content in relational databases, see my post [IBM Watson - Business Intelligence, Data Retrieval and Text Mining].

Linux includes a utility called wget which allows you to download content from the Internet to your system. What documents you decide to download is up to you, based on what types of questions you want answered. For example, if you like Literature, check out the vast resources at [FullBooks.com]. You can automate the download by writing a shell script or program to invoke wget to all the places you want to fetch data from. Rename the downloaded files to something unique, as often they are just "index.html". For more on wget utility, see [IBM Developerworks].

Step 5: The Query Panel - Parsing the Question

Next, we need to parse the question and have some sense of what is being asked for. For this we will use [OpenNLP] for Natural Language Processing, and [OpenCyc] for the conceptual logic reasoning. See Doug Lenat presenting this 75-minute video [Computers versus Common Sense]. To learn more, see the [CYC 101 Tutorial].

Unlike Jeopardy! where Alex Trebek provides the answer and contestants must respond with the correct question, we will do normal Question-and-Answer processing. To keep things simple, we will limit questions to the following formats:

• Who is ...?
• Where is ...?
• When did ... happen?
• What is ...?
• Which ...?

Host 1 will have a simple Query Panel web interface. At the top, a place to enter your question, and a "submit" button, and a place at the bottom for the answer to be shown. When "submit" is pressed, this will pass the question to "main.jsp", the Java servlet program that will start the Question-answering analysis. Limiting the types of questions that can be posed will simplify hypothesis generation, reduce the candidate set and evidence evaluation, allowing the analytics processing to continue in reasonable time.

Step 6: Unstructured Information Management Architecture

The "heart and soul" of IBM Watson is Unstructured Information Management Architecture [UIMA]. IBM developed this, then made it available to the world as open source. It is maintained by the [Apache Software Foundation], and overseen by the Organization for the Advancement of Structured Information Standards [OASIS].

Basically, UIMA lets you scan unstructured documents, gleam the important points, and put that into a database for later retrieval. In the graph above, DBs means 'databases' and KBs means 'knowledge bases'. See the 4-minute YouTube video of [IBM Content Analytics], the commercial version of UIMA.

Starting from the left, the Collection Reader selects each document to process, and creates an empty Common Analysis Structure (CAS) which serves as a standardized container for information. This CAS is passed to Analysis Engines , composed of one or more Annotators which analyze the text and fill the CAS with the information found. The CAS are passed to CAS Consumers which do something with the information found, such as enter an entry into a database, update an index, or update a vote count.

 

(Note: This point requires, what we in the industry call a small matter of programming, or [SMOP]. If you've always wanted to learn Java programming, XML, and JDBC, you will get to do plenty here. )

 

If you are not familiar with UIMA, consider this [UIMA Tutorial].

Step 7: Parallel Processing

People have asked me why IBM Watson is so big. Did we really need 2,880 cores of processing power? As a supercomputer, the 80 TeraFLOPs of IBM Watson would place it only in 94th place on the [Top 500 Supercomputers]. While IBM Watson may be the [Smartest Machine on Earth], the most powerful supercomputer at this time is the Tianhe-1A with more than 186,000 cores, capable of 2,566 TeraFLOPs.

To determine how big IBM Watson needed to be, the IBM Research team ran the DeepQA algorithm on a single core. It took 2 hours to answer a single Jeopardy question! Let's look at the performance data:

Element	Number of cores	Time to answer one Jeopardy question
Single core	1	2 hours
Single IBM Power750 server	32	< 4 minutes
Single rack (10 servers)	320	< 30 seconds
IBM Watson (90 servers)	2,880	< 3 seconds

The old adage applies, [many hands make for light work]. The idea is to divide-and-conquer. For example, if you wanted to find a particular street address in the Manhattan phone book, you could dispatch fifty pages to each friend and they could all scan those pages at the same time. This is known as "Parallel Processing" and is how supercomputers are able to work so well. However, not all algorithms lend well to parallel processing, and the phrase [nine women can't have a baby in one month] is often used to remind us of this.

Fortuantely, UIMA is designed for parallel processing. You need to install UIMA-AS for Asynchronous Scale-out processing, an add-on to the base UIMA Java framework, supporting a very flexible scale-out capability based on JMS (Java Messaging Services) and ActiveMQ. We will also need Apache Hadoop, an open source implementation used by Yahoo Search engine. Hadoop has a "MapReduce" engine that allows you to divide the work, dispatch pieces to different "task engines", and the combine the results afterwards.

Host 2 will run Hadoop and drive the MapReduce process. Plan to have three KVM guests on Host 1, four on Host 2, and three on Host 3. That means you have 10 task engines to work with. These task engines can be deployed for Content Readers, Analysis Engines, and CAS Consumers. When all processing is done, the resulting votes will be tabulated and the top answer displayed on the Query Panel on Host 1.

Step 8: Testing

To simplify testing, use a batch processing approach. Rather than entering questions by hand in the Query Panel, generate a long list of questions in a file, and submit for processing. This will allow you to fine-tune the environment, optimize for performance, and validate the answers returned.

There you have it. By the time you get your implementation fully operational, you will have learned a lot of useful skills, including Linux administration, Ethernet networking, NFS file system configuration, Java programming, UIMA text mining analysis, and MapReduce parallel processing. Hopefully, you will also gain an appreciation for how difficult it was for the IBM Research team to accomplish what they had for the Grand Challenge on Jeopardy! Not surprisingly, IBM Watson is making IBM [as sexy to work for as Apple, Google or Facebook], all of which started their business in a garage or a basement with a system as small as this version for personal use.

technorati tags: IBM, Watson, Jeopardy, Challenge, POWER7, EPA, Energy Star, RHEL, SLES, Ubuntu, Linux, UIMA, Hadoop, MapReduce, KVM, DeepQA, Roger Bannister, John Pultorak, Jay Shafer, George Hotz

, Eric Brown

Tonight PBS plans to air Season 38, Episode 6 of NOVA, titled [Smartest Machine On Earth]. Here is an excerpt from the station listing:

"What's so special about human intelligence and will scientists ever build a computer that rivals the flexibility and power of a human brain? In "Artificial Intelligence," NOVA takes viewers inside an IBM lab where a crack team has been working for nearly three years to perfect a machine that can answer any question. The scientists hope their machine will be able to beat expert contestants in one of the USA's most challenging TV quiz shows -- Jeopardy, which has entertained viewers for over four decades. "Artificial Intelligence" presents the exclusive inside story of how the IBM team developed the world's smartest computer from scratch. Now they're racing to finish it for a special Jeopardy airdate in February 2011. They've built an exact replica of the studio at its research lab near New York and invited past champions to compete against the machine, a big black box code -- named Watson after IBM's founder, Thomas J. Watson. But will Watson be able to beat out its human competition?"

Craig Rhinehart offers [10 Things You Need to Know About the Technology Behind Watson].

An artist has come up with this clever [unofficial poster].

Dr. Jon Lenchner from IBM Research has a series of posts on [How Watson "sees", "hears", and "speaks"] and [Selected Nuances].

Like most supercomputers, Watson runs the Linux operating system. The system runs 2,880 cores (90 IBM Power 750 servers, four sockets each, eight cores per socket) to achieve 80 [TeraFlops]. TeraFlops is the unit of measure for supercomputers, representing a trillion floating point operations. By comparison, Hans Morvec, principal research scientist at the Robotics Institute of Carnegie Mellon University (CMU) estimates that the [human brain is about 100 TeraFlops]. So, in the three seconds that Watson gets to calculate its response, it would have processed 240 trillion operations.

Several readers of my blog have asked for details on the storage aspects of Watson. Basically, it is a modified version of IBM Scale-Out NAS [SONAS] that IBM offers commercially, but running Linux on POWER instead of Linux-x86. System p expansion drawers of SAS 15K RPM 450GB drives, 12 drives each, are dual-connected to two storage nodes, for a total of 21.6TB of raw disk capacity. The storage nodes use IBM's General Parallel File System (GPFS) to provide clustered NFS access to the rest of the system. Each Power 750 has minimal internal storage mostly to hold the Linux operating system and programs.

When Watson is booted up, the 15TB of total RAM are loaded up, and thereafter the DeepQA processing is all done from memory. According to IBM Research, "The actual size of the data (analyzed and indexed text, knowledge bases, etc.) used for candidate answer generation and evidence evaluation is under 1TB." For performance reasons, various subsets of the data are replicated in RAM on different functional groups of cluster nodes. The entire system is self-contained, Watson is NOT going to the internet searching for answers.

On ZDnet, Steven J. Vaughan-Nichols welcomes our new [Linux Penguin Jeopardy overlords]. I have to say I share his enthusiasm!

technorati tags: IBM, Nova, Watson, #ibmwatson, Jeopardy, POWER7, p750, supercomputer, TeraFlops, disk, SONAS, GPFS, SAS, Craig Rhinehart, Jon Lenchner, Hans Morvec, Carnegie Mellon University, CMU

Wrapping up my coverage of the annual [2010 System Storage Technical University], I attended what might be perhaps the best session of the conference. Jim Nolting, IBM Semiconductor Manufacturing Engineer, presented the new IBM zEnterprise mainframe, "A New Dimension in Computing", under the Federal track.

The zEnterprises debunks the "one processor fits all" myth. For some I/O-intensive workloads, the mainframe continues to be the most cost-effective platform. However, there are other workloads where a memory-rich Intel or AMD x86 instance might be the best fit, and yet other workloads where the high number of parallel threads of reduced instruction set computing [RISC] such as IBM's POWER7 processor is more cost-effective. The IBM zEnterprise combines all three processor types into a single system, so that you can now run each workload on the processor that is optimized for that workload.

IBM zEnterprise z196 Central Processing Complex (CPC)

Let's start with the new mainframe z196 central processing complex (CPC). Many thought this would be called the z11, but that didn't happen. Basically, the z196 machine has a maximum 96 cores versus z10's 64 core maximum, and each core runs 5.2GHz instead of z10's cores running at 4.7GHz.  It is available in air-cooled and water-cooled models. The primary operating system that runs on this is called "z/OS", which when used with its integrated UNIX System Services subsystem, is fully UNIX-certified. The z196 server can also run z/VM, z/VSE, z/TPF and Linux on z, which is just Linux recompiled for the z/Architecture chip set. In my June 2008 post [Yes, Jon, there is a mainframe that can help replace 1500 servers], I mentioned the z10 mainframe had a top speed of nearly 30,000 MIPS (Million Instructions per Second). The new z196 machine can do 50,000 MIPS, a 60 percent increase!

(Update: Back in 2007, IBM and Sun mutually supported [OpenSolaris on an IBM System z mainframe]. Unfortunately, after Oracle acquired Sun, the OpenSolaris Governing Board has [grown uneasy over Oracle's silence] about the future of OpenSolaris on any platform. The OpenSolaris [download site] identifies 2009.06 as the latest release, but only for x86 and SPARC chip sets. Apparently, the 2010.03 release expected five months ago in March has slipped. Now it looks official that [OpenSolaris is Dead].)

The z196 runs a hypervisor called PR/SM that allows the box to be divided into dozens of logical partitions (LPAR), and the z/VM operating system can also act as a hypervisor running hundreds or thousands of guest OS images. Each core can be assigned a specialty engine "personality": GP for general processor, IFL for z/VM and Linux, zAAP for Java and XML processing, and zIIP for database, communications and remote disk mirroring. Like the z9 and z10, the z196 can attach to external disk and tape storage via ESCON, FICON or FCP protocols, and through NFS via 1GbE and 10GbE Ethernet.

IBM zEnterprise BladeCenter Extension (zBX)

There is a new frame called the zBX that basically holds two IBM BladeCenter chassis, each capable of 14 blades, so total of 28 blades per zBX frame. For now, only select blade servers are supported inside, but IBM plans to expand this to include more as testing continues. The POWER-based blades can run native AIX, IBM's other UNIX operating system, and the x86-based blades can run Linux-x86 workloads, for example. Each of these blade servers can run a single OS natively, or run a hypervisor to have multiple guest OS images.  IBM plans to look into running other POWER and x86-based operating systems in the future.

If you are already familiar with IBM's BladeCenter, then you can skip this paragraph. Basically, you have a chassis that holds 14 blades connected to a "mid-plane". On the back of the chassis, you have hot-swappable modules that snap into the other side of the mid-plane. There are modules for FCP, FCoE and Ethernet connectivity, which allows blades to talk to each other, as well as external storage. BladeCenter Management modules serve as both the service processor as well as the keyboard, video and mouse Local Console Manager (LCM). All of the IBM storage options available to IBM BladeCenter apply to zBX as well.

Besides general purpose blades, IBM will offer "accelerator" blades that will offload work from the z196. For example, let's say an OLAP-style query is issued via SQL to DB2 on z/OS. In the process of parsing the complicated query, it creates a Materialized Query Table (MQT) to temporarily hold some data. This MQT contains just the columnar data required, which can then be transferred to a set of blade servers known as the Smart Analytics Optimizer (SAO), then processes the request and sends the results back. The Smart Analytics Optimizer comes in various sizes, from small (7 blades) to extra large (56 blades, 28 in each of two zBX frames).   A 14-blade configuration can hold about 1TB of compressed DB2 data in memory for processing.

IBM zEnterprise Unified Resource Manager

You can have up to eight z196 machines and up to four zBX frames connected together into a monstrously large system. There are two internal networks. The Inter-ensemble data network (IEDN) is a 10GbE that connects all the OS images together, and can be further subdivided into separate virtual LANs (VLAN). The Inter-node management network (INMN) is a 1000 Mbps Base-T Ethernet that connects all the host servers together to be managed under a single pane of glass known as the Unified Resource Manager. It is based on IBM Systems Director.

By integrating service management, the Unified Resource Manager can handle Operations, Energy Management, Hypervisor Management, Virtual Server Lifecycle Management, Platform Performance Management, and Network Management, all from one place.

IBM Rational Developer for System z Unit Test (RDz)

But what about developers and testers, such as those Independent Software Vendors (ISV) that produce mainframe software. How can IBM make their lives easier?

Phil Smith on z/Journal provides a history of [IBM Mainframe Emulation]. Back in 2007, three emulation options were in use in various shops:

• Open Mainframe, from Platform Solutions, Inc. (PSI)
• FLEX-ES, from Fundamental Software, Inc.
• Hercules, which is an open source package

None of these are viable options today. Nobody wanted to pay IBM for its Intellectual Property on the z/Architecture or license the use of the z/OS operating system. To fill the void, IBM put out an officially-supported emulation environment called IBM System z Professional Development Tool (zPDT) available to IBM employees, IBM Business Partners and ISVs that register through IBM Partnerworld. To help out developers and testers who work at clients that run mainframes, IBM now offers IBM Rational Developer for System z Unit Test, which is a modified version of zPDT that can run on a x86-based laptop or shared IBM System x server. Based on the open source [Eclipse IDE], the RDz emulates GP, IFL, zAAP and zIIP engines on a Linux-x86 base. A four-core x86 server can emulate a 3-engine mainframe.

With RDz, a developer can write code, compile and unit test all without consuming any mainframe MIPS. The interface is similar to Rational Application Developer (RAD), and so similar skills, tools and interfaces used to write Java, C/C++ and Fortran code can also be used for JCL, CICS, IMS, COBOL and PL/I on the mainframe. An IBM study ["Benchmarking IDE Efficiency"] found that developers using RDz were 30 percent more productive than using native z/OS ISPF. (I mention the use of RAD in my post [Three Things to do on the IBM Cloud]).

What does this all mean for the IT industry? First, the zEnterprise is perfectly positioned for [three-tier architecture] applications. A typical example could be a client-facing web-server on x86, talking to business logic running on POWER7, which in turn talks to database on z/OS in the z196 mainframe. Second, the zEnterprise is well-positioned for government agencies looking to modernize their operations and significantly reduce costs, corporations looking to consolidate data centers, and service providers looking to deploy public cloud offerings. Third, IBM storage is a great fit for the zEnterprise, with the IBM DS8000 series, XIV, SONAS and Information Archive accessible from both z196 and zBX servers.

To learn more, see the [12-page brochure] or review the collection of [IBM Redbooks]. Check out the [IBM Conferences schedule] for an event near you. Next year, the IBM Storage University will be held July 18-22, 2011 in Orlando, Flordia.

technorati tags: IBM, Technical University, zEnterprise, x86, POWER7, RISC, z/OS, Linux, AIX, OpenSolaris, Oracle, FICON, NFS, z196, zBX, DB2, SAO, IEDN, INMN, RDz, ISV, Eclipse, Cloud Computing

Continuing my week in Washington DC for the annual [2010 System Storage Technical University], here is my quick recap of the keynote sessions presented Monday morning. Marlin Maddy, Worldwide Technical Events Executive for IBM Systems Lab Services and Training, served as emcee.

Roland Hagen

Roland Hagan, IBM Vice President for IBM System x server platform, presented on how IBM is redefining the x86 computing experience. More than 50 percent of all servers are x86 based. These x86 servers are easy to acquire, enjoy a large application base, and can take advantage of readily available skilled workforce for administration. The problem is that 85 percent of x86 processing power remains idle, energy costs are 8 times what they were 12 years ago, and management costs are now 70 percent of the IT budget.

IBM has the number one market share for scalable x86 servers. Roland covered the newly announced eX5 architecture that has been deployed in both rack-optimized models as well as IBM BladeCenter blade servers. These can offer 2x the memory capacity as competitive offerings, which is important for today's server virtualization, database and analytics workloads. This includes 40 and 80 DIMM models of blades, and 64 to 96 DIMM models of rack-optimized systems. IBM also announced eXFlash, internal Solid State Drives accessible at bus speeds. FlexNode allows a 4-node system to dynamically change to 2 separate 2-node systems.

By 2013, analysts estimate that 69 percent of x86 workloads will be virtualized, and that 22 percent of servers will be running some form of hypervisor software. By 2015, this grows to 78 percent of x86 workloads being virtualized, and 29 percent of servers running hypervisor.

Doug Balog

Doug Balog, IBM Vice President and Disk Storage Business Line Executive, presented how the growth of information results in a "perfect storom" for the storage industry. Storage Admins are focused on managing storage growth and the related costs and complexity, proper forecasting and capacity planning, and backup administration. IBM's strategy is to help clients in the following areas:

• Storage Efficiency - getting the most use out of the resources you invest
• Service Delivery - ensuring that information gets to the right people at the right time, simplify reporting and provisioning
• Data Protection - protecting data against unethical tampering, unauthorized access, and unexpected loss and corruption

He wrapped up his talk covering the success of DS8700 and XIV. In fact, 60 percent of XIV sales are to EMC customers. The TCO of an XIV is less than half the TCO of a comparable EMC VMAX disk system.

Dave McQueeney

Dave McQueeney, IBM Vice President for Strategy and CTO for US Federal, covered how IBM's Smarter Planet vision for smarter cities, smarter healthcare, smarter energy grid and smarter traffic are being adopted by the public sector. Almost every data center in US Federal government is out of power, floor space and/or cooling capability. An estimated 80 percent of US Federal government IT budgets are spent on maintenance and ongoing operations, leaving very little left over for the big transformational projects that President Barack Obama wants to accomplish.

Who has the most active Online Transaction Processing (OLTP)? You might guess a big bank, but it is the US Department of Homeland Security (DHS), with a system processing 600 million transactions per day. Another government agency is #2, and the top Banking application is finally #3. The IBM mainframe has solved problems 10 to 15 years ago that the distributed systems are just now encountering today. Worldwide, more than 80 percent of banks use mainframes to handle their financial transactions.

IBM's recent POWER7 set of servers are proving successful in the field. For example, Allianz was able to consolidate 60 servers to 1. Running DB2 on POWER7 server is 38 percent less expensive than Oracle on x86 Nehalem processors. For Java, running JVM on POWER7 is 73 percent better than JVM on x86 Nehalem.

The US federal government ingests a large amount of data. It has huge 10-20 PB data warehouses. In fact, the amount of GB received every year by the US federal government alone exceed the production of all disk drives produced by all drive manufacturers. This means that all data must be processed through "data reduction" or it is gone forever.

Clod Barrera

The last keynote for Monday was given by Clod Barrera, IBM Distinguished Engineer and Chief Technical Strategist for System Storage. He started out shocking the audience with his view that the "disk drive industry is a train wreck". While R&D in disk drives enjoyed a healthy improvement curve up to about 2004, it has now slowed down, getting more difficult and more expensive to improve performance and capacity of disk drives. The rest of his presentation was organized around three themes:

1. Integrated Stacks - while new-comers like Oralce/Sun and the VCE coalition are promoting the benefits of integrated stacks, IBM has been doing this for the past five decades. New advancements in Server and Storage virtualization provide exciting new opportunities.
2. Integrated Systems - solutions like IBM Information Archive and SONAS, and new features like Easy Tier that help adopt SSD transparently. As it gets harder and harder to scale-up, IBM has moved to innovative scale-out architectures.
3. Integrated Data Center management - companies are now realizing that management and governance are critical factors of success, and that this needs to be integrated between traditional IT, private, public and hybrid cloud computing.

This was a great inspiring start for what looks like an awesome week!

technorati tags: IBM, Technical University, Marlin Maddy, Roland Hagen, Doug Balog, Dave McQueeney, Clod Barrera, x86, eX5, FlexNode, Barack Obama, DHS, OLTP, DB2, POWER7, Oracle, JVM, Intel, Nehalem