The Itanium Solutions Blog

A recently published whitepaper from Alinean VP and Senior Analyst, Paul Demopoulos took an in-depth look at HP-UX 11i on Itanium-based Integrity Servers vs. Red Hat Linux on IBM x86 Servers.

From the abstract:

“This paper analyzes the three year lifecycle TCO of two alternative platforms, considering the costs to plan, purchase, implement, manage, and use two comparable server configurations for a specified scenario, application, and workload. The comparisons in this study use HP-UX 11i, a UNIX solution hosted on an open system platform using HP Integrity servers (Intel® Itanium®-based servers with 4, 8 and 16 cores depending on function) versus Red Hat Linux running on IBM x86 servers and quantifies how open systems UNIX solutions running on Intel Itanium servers can deliver higher levels of manageability, consolidation, virtualization, adaptability, security, and availability. As a result of the analysis, HP-UX 11i running on HP Integrity servers provides substantially more benefits in business critical computing environments, delivering higher levels of consolidation to deliver total cost of ownership (TCO) savings of more than 20% compared to Red Hat Linux on IBM x86 servers.”

Get the whitepaper here.

As a new contributor to the Itanium Solutions blog, let me give you a quick intro. Having graduated with a computer science(CS)/math degree 25+ years ago, I’ve seen my share of changes along the way, but what surprises me most are the changes that have not yet occurred. While I was taking CS classes in the early 80’s I shied away from taking more COBOL programming classes because the ‘common wisdom’ was that COBOL applications, and the mainframe they ran on, were on a downward trend and not an area where you wanted to focus your career. The mainframe is still around, and there are more lines of COBOL code running than any other programming language. Who would have believed it?

I put my time on the mainframe as a programmer for a petroleum engineering firm, and still remember a late night onsite at one of our customers, a large bank in west Texas. After recompiling, linking and loading my latest update, I suddenly discovered that everyone was gone, the doors were locked … and could only be opened with a key that I did not possess. It was about that time, my hands-on computer programming interest waned. Today, I am a program manager in HP’s Enterprise Storage, Server and Networking group, and privileged to interact with a variety of customers and partners looking to drive innovation in the data center.

Now on to the point of this blog post – unlike 25 years ago when the mainframe was essentially the only option if you needed a highly available server, the HP Superdome has similar availability and reliability of the mainframe. The Superdome server was designed to run mission critical enterprise applications and has 128 Intel Itanium cores that can be utilized for scale-up applications using a large number of cores for single OS instance, or be partitioned to run scale-out applications running different OS’s…or both. The reliability & availability was built-in to the Superdome, not tacked on as an afterthought.

How does the HP Integrity Superdome stack up? Compared to a z10 mainframe, the Superdome has similar availability and reliability… BUT at a 3 year TCO that is 1/8th that of the mainframe. Check out the comparison in our new white paper. Having cut my teeth on the mainframe in my formative years I respect the longevity it has been able to achieve, but it sure is difficult to justify such a hefty premium when other alternatives deliver the goods.

John Pickett
Mainframe Alternative Program Manager
HP Enterprise Servers, Storage & Networking
Blog: Legacy Transformation

I would like to share with the Itanium Solutions blog our experience with HP-UX on Itanium platforms. We initially started evaluation of the Itanium architecture shortly after it was released. Although my team and I had a very positive impression about PA-RISC technology, mainly in the area of stability and predictability, we were keen to explore possibilities offered by Itanium. As heavy HP users we were interested in preserving the current advantages of the RA-RISC platform while exploring features of the new system. Surprisingly to us, Itanium was very stable even with the early releases. After multiple tests in our non-production environment we found out that there weren’t any major obstacles in the adoption of this new technology.

We started gradually by upgrading the old PA-RISC to the new platform with the clear goal of reducing maintenance costs and improving efficiency. Normally we would apply new technologies on less important systems, but in this case, problems with scalability and performance forced us to make a decision concerning our mission-critical Billing/CRM system. Our main concerns were related to data consistency and failover scenarios. Precise planning along with close cooperation with expert HP reps made it possible to upgrade PA-RISC to Itanium sooner. And the targets we set concerning performance, scalability and TCO optimization were overachieved.

We are proud that the Itanium Solutions Alliance recognized our work and efforts on this project. The main reason I believe we were nominated and selected as the winner in Mission-Critical Data category was because of our objective to use the full functionality of the solution. The case study featuring our solution is now available for download. We welcome your questions and comments.

-Simeon Dimitrov, Mobiltel

It’s a little known fact that the same uniquely scalable shared memory architecture that enables SGI Altix® 4700 with Intel® Itanium® processors to power technical and scientific breakthroughs also excels at high-performance reasoning on ontologies for enterprise data analytics applications. Ontologies are knowledge models or formal representations of a set of relevant concepts within a domain and the relationship between these concepts.

A major advantage of ontologies for data analytics is the ability to share the meaning (semantics) of information in a knowledge model, capture complex relationships and integrate heterogeneous data sources. These characteristics can only be achieved if the ontology run-time is able to scale with a growing number of facts.

Silicon Graphics and Ontoprise GmbH have demonstrated that OntoBroker® inference engine can load and process large ontologies in main memory. The SGI Altix 4700 platform has a unique configuration elasticity that allows adding processors and memory independent of each other, and thus easily accommodating user growth and securing hardware investment with a lower TCO. Here are some benchmark examples using the OntoBroker inference engine on a SGI Altix 4700 server:

–Complex graph traversal. Finding the possible traversable paths between the nodes in a graph comprising of 1 million nodes takes only 15.7 seconds, thus making complex reasoning possible

–Semantic retrieval and query processing with 104 facts. Five classes of 195 queries with varying complexity run in less than 18 milliseconds on the SGI Altix® 4700

–SmartWeb®. The longest queries for multimedia web content with 95 queries and 60 rules takes an average of 17 seconds from a disk-based database but only an average of 73 milliseconds from a non-materialized in-memory model.

–Wikipedia® knowledge base search. The most complex query with average result sets from Wikipedia® knowledge base takes less than 35 ms with a trade-off of load time of 48 million wiki facts in 138 minutes

–Automotive test. A large ontology comprising of 1.4 million facts takes only 133 seconds for in-memory load while queries over the indexed database model, and the database load took 381 seconds. The query times showed that large result sets benefit most from an in-memory model

So with a professional reasoning engine like OntoBroker, and scalable servers like SGI Altix 4700, users of many applications can find required information much more quickly and easily.

As a leader in computationally intensive computing, SGI tends to set the pace for the large memory systems often required to crunch the numbers in massive data sets. In a recent press release, we announced that our Altix systems have now achieved 21 Terabytes of globally addressable memory at customer sites. I’d like to explain what this means in more depth and offer examples.

The Altix 450/4700 (Itanium) systems can accommodate 128 terabytes of globally shared memory under the control of a single instance of the Linux operating system. The system may also be partitioned among multiple instances of Linux and provide globally addressable shared memory among OS instances via SGI’s unique NUMAlink® interconnect technology. What this means to the customer is essentially saving time: time-to-results, time-to-solution and time-to-innovation. It significantly simplifies application development and debugging for all parallel programming models be it OpenMP, pthreads, MPI or SHMEM.

In addition, it offers an integrated platform for application fusion, which enables running a mix of different applications and workloads. As workloads usually change during the project life-cycle, a global shared memory platform lowers TCO compared to clusters that require node reconfiguration.

We have seen great success for memory-resident database applications with uses in Internet data centers and transaction processing; as well as those based on “graph theory,” an important area of mathematics with uses in defense and homeland security applications, multi-disciplinary science, and data assimilation. Some customers who are already seeing the advantages of the SGI Altix product line are:

Wright-Patterson Air Force Base: the laboratory here uses an SGI Altix 4700 system with 4,608 Intel Itanium processors in a single supercomputer equipped with 20 TB of globally addressable memory and 440 TB of usable disk space. Globally addressable memory means applications can be shared across various operating systems via SGI NUMAlink. One of the largest computers in the Department of Defense, the SGI resource helps DoD researchers to design faster, reduce risk by increasing the quality of modeling and simulation, and support an intensifying effort to develop “game-changing” computational science and engineering applications.

The Leibniz Supercomputing Centre Munich (LRZ): This facility operates a 4,864 Intel Itanium processor system with slightly over 39 TB of globally addressable memory that is hard at work solving increasingly complex simulations in physics and astrophysics, materials research, fluid dynamics, chemistry, geosciences and biological sciences.

Click here for more information about SGI® Altix® Itanium globally addressable memory capabilities, or click here for the press release.