Oracle and IBM fight for the heavy workload
Parallel universe: SunCluster and Exalogic
These are not the only parallel machines in the Oracle and IBM arsenals. There are several more important ones, and no doubt more will come out from Big Larry and Big Blue, as well as their competitors, as customers seek to solve specific problems with their clusters.
Oracle can't ignore the Sparc/Solaris base, which doesn't want to run Linux and needs a Sparc platform on which to run Oracle11g/RAC applications. In late September, ahead of its OpenWorld conference, Oracle rolled out a Sparc SuperCluster configuration, which marries its Sparc T4-4 quad-socket servers with the Exadata storage servers and some generic ZFS disk arrays.
The Sparc SuperCluster T4
Specifically, the Sparc SuperCluster rack has four of the Sparc T4-4 servers, each with four eight-core 3GHz Sparc T4 processors. Collectively, the four nodes, used to run Oracle 11g as well as application code, have 4TB of memory and depending on disk options, between 97TB to 198TB of disk capacity.
The rack has multiple QDR InfiniBand switches and 8.66TB of flash in the Exadata storage arrays, yielding 1.2 million IOPs. There are also a couple of Oracle's ZFS Storage 7320 arrays in there. The database nodes can run Solaris 10 or Solaris 11. Prices for the SuperCluster were not divulged.
The other interesting engineered system from Oracle is the Exalogic Elastic Cloud, a tuned machine to run a virtualised implementation of Oracle's WebLogic application server. In a full-rack configuration, the Exalogic cluster has 30 1U rack servers with a total of 386 Xeon X5670 cores spinning at 2.93GHz.
Each node has 96GB of main memory, just like in the Exadata X2-2 nodes, and 40TB of external disk in the rack. QDR InfiniBand links the nodes together so they can share work and 10-Gigabit Ethernet switches link the app serving cluster to the outside world.
The secret sauce in the Exalogic cluster is called Cache Coherence. As the name suggests, this is a piece of gridding software that allows those 30 servers to look like one giant app server to the outside world.
The Cache Coherence balances, synchronises, caches and partitions the app serving data and workloads under the covers.
Oracle is using its own implementation of Red Hat's Enterprise Linux, its riff on the Xen hypervisor and the JRockit virtual machine to run the WebLogic app server. (JRockit and WebLogic came to Oracle through, you guessed it, an acquisition.) Pricing for the Exalogic clustered app servers has not been announced.
Ask Dr Watson
IBM deployed its initial Watson question-answer machine on a BlueGene massively parallel supercomputer, but decided to promote the then-new Power7-based Power 750 workhorse server by challenging humans on the US Jeopardy! game show.
Watson was as much a publicity stunt as it was science, and with all the money Big Blue put into the project it needed to get something tangible out of it besides a win for the propeller-heads at IBM Research at Yorktown Heights, New York.
IBM's Watson QA System
The Watson machine consists of ten racks of Power 750 servers with a total of 2,880 Power7 cores and 16TB of main memory.
Watson drew on that memory and the fast 10-Gigabit Ethernet switches from Juniper linking the nodes together, as well as the parallel nature of the DeepQA software stack that searched through databases to find keywords and give responses.
The machine obliterated Ken Jennings, who with 74 wins has held the top rank in the game the longest, and Brad Rutter, who racked up a record $3.25m on the show during his reign earlier in the decade.
DeepQA creates an in-memory database of text, based on the Apache Hadoop MapReduce algorithm and related HDFS file system created by Yahoo!, to mimic the search-engine operations of Google.
The stack also includes a bit of code called Unstructured Information Management Architecture (UIMA), a framework created by IBM database gurus back in 2005 to help them cope with unstructured information such as text, audio and video streams. The UIMA code performs the natural language processing that parses text and helps Watson figure out what a Jeopardy! clue is about.
IBM is working with doctors and researchers at Columbia University, speech-recognition experts at Nuance and insurance company Wellpoint to commercialise Watson as a medical expert system.
I saw the Watson machine in beta testing only weeks after it won the Jeopardy! show and when it was stuffed to the gills with medical journals and encyclopedias. And it did a pretty good job at differential diagnosis, even if it is still not quite as convincing as House. ®
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