With Power Comes Complexity

By John West

September 14, 2009

When rPath CTO Erik Troan speaks during the opening session at this year’s High Performance Computing on Wall Street conference on Monday morning, he’ll be emphasizing something that old school HPC’ers are very familiar with: complexity. Even moderately-sized HPC clusters are a study in complexity: everything — from operating system patches to compilers and job schedulers to an individual user’s shell preferences — interacts with everything else. Getting it all working and hammered into a stable system after the initial installation can take upwards of six months (in the average case; I once had a pair of systems that took nearly two years to stabilize, though) in a process that can seem a lot like playing whack-a-mole without a hammer. Once a system is stable, administrators and center management are understandably loathe to make a change.

And yet change is precisely what is required in today’s large-scale computing environments. When clusters were primarily confined to research environments, whether in national labs or R&D units of large corporations, then it was acceptable to expect the users to adapt to the environment. If a system took a week to stabilize after an upgrade, no one liked it, but users accepted it, not least because there usually wasn’t a lot of discipline in the system change process. There might have been a list of what changed, but in many cases even that list is not made today until after the upgrade is complete and everyone gets together to compare notes.

As HPC continues to be pulled deeper into the back offices of all kinds of companies, the line between “enterprise” computing and “high performance” computing is blurring. Enterprise users expect mature systems management, including detailed planning and management with detailed manifests sufficient to completely rebuild the operating environment at any point in time, whether to rerun a legacy application or to roll back out of an upgrade that had unexpected consequences down the road.

Although old school HPC’ers are familiar with this complexity, they haven’t done much to develop the tools and disciplines to manage it in a controlled fashion. Configuration management databases (CMDBs) are not uncommon in large, production-oriented HPC centers. But CMDBs are frequently de-coupled from implementation, and this means that it is pretty easy to ignore the CM process “just this once” to make a “really important” change, at which point the database is out of synch with reality. Good admins keep notes and backups, but these tend to depend upon individual discipline and are often manual processes with a little cron scheduling thrown in.

Whittling down complexity is rPath’s mission. Before he founded the company, Erik Troan served as Red Hat’s VP of Product Engineering, chief developer for Red Hat Software, and in several other roles. He was responsible for leading development for Red Hat Linux, RPM, and Anaconda, and has co-authored two editions of Linux Application Development. Excellent chops for a guy that’s now leading a company that positions itself to help manage the complexity of the HPC software environment.

rPath is a privately-held company of about 30 people that has been through three rounds of venture funding since its founding in 2005. The company offers a release automation platform (automatic provisioning) that includes version control for everything on a system: firmware, OS, patches, compilers, linkers and applications.

Administrators can use rPath’s tools to document the complete state of a cluster (or many clusters), set up a planned change, deploy that change to all the systems in a cluster, and automatically roll back if it doesn’t go well. Troan identifies RPM and the many front-ends built on top of RPM (yum and so on) as source-level management tools, and distinguishes rPath’s tools from them based on their ability to manage and provision everything from the OS up, including complete virtual machine images if you go for that sort of thing.

When Troan talks on Monday morning, he will emphasize three rules for a scalable approach to software infrastructure management:

  1. Stay application-centric.
  2. Keep versions controlled on everything.
  3. Automated provisioning is key.

Troan says that commercial organizations often mirror the approach to cluster building taken in research environments: start with the hardware and the operating system, and make everything else work out. This can work just fine in an environment where COTS packages don’t dominate, or where you are working with a very mature application that is flexible in terms of its operating environment. But if your application is more finicky, or held together with bailing wire and tape, or you don’t have access to the source, this is a recipe for pain. Sure you can partition up your cluster and deploy different operating systems to support all your various application requirements, but only if you actually know what those requirements are.

The point is to start with the problem the cluster is supposed to solve, figure out what tools you need to solve that problem, and build the environment that supports it. This sounds straightforward, but a key error that can happen is that the application group will do this kind of planning and then not communicate it to the technology team running the acquisition, causing problems in implementation.

Troan’s second key for scalable HPC infrastructure management is to keep track of the version on everything, and don’t make any ad hoc changes. Basically the idea is that organizations need to think of their clusters as a delicately balanced ecosystem where everything is interrelated. Strong version control will allow organizations to track back through a change that breaks something and know exactly where to look for a problem, and will also support forward planning for change.

Up to this point in Troan’s three rules, we only have a process. In fact, we really don’t have anything more than one can get by establishing a strong CM discipline in an organization with a good CMDB and maybe some ITIL practice thrown in for good measure.

Troan says the key for tying it all together is coupling version control and documentation of state with the implementation of change through an automated provisioning system. Changes are rolled forward automatically and can be rolled back as needed to any prior state. The documentation is always complete provided that the tool managing version control is linked to the tool managing implementation deployment, and if administrators always use the system (a problem) for any change, then configuration drift is eliminated as a source of instability in your production systems.

This is a discipline that I currently employ among the desktop systems in my organization, for example, but not on my HPC systems. It seems obvious now that I think about it.

rPath’s technology is seeing adoption in real HPC environments, and Troan says that organizations like the Department of Energy labs, various companies in Europe, and Sony Pictures Imageworks are using rPath tools to manage large-scale compute clusters today.

Troan’s three rules are obviously informed by where he has positioned his company and his career; they are certainly necessary, but they may not be sufficient for the establishment of a sound discipline to tame what are often wild and wooly HPC deployments. Still, I am glad to see this conversation happening at this particular event. The HPC conversation is well advanced on Wall Street, and as the adoption of our technologies there increases, they will need mileposts to help them merge our two worlds together.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Weekly Twitter Roundup (Feb. 23, 2017)

February 23, 2017

Here at HPCwire, we aim to keep the HPC community apprised of the most relevant and interesting news items that get tweeted throughout the week. Read more…

By Thomas Ayres

HPE Server Shows Low Latency on STAC-N1 Test

February 22, 2017

The performance of trade and match servers can be a critical differentiator for financial trading houses. Read more…

By John Russell

HPC Financial Update (Feb. 2017)

February 22, 2017

In this recurring feature, we’ll provide you with financial highlights from companies in the HPC industry. Check back in regularly for an updated list with the most pertinent fiscal information. Read more…

By Thomas Ayres

Rethinking HPC Platforms for ‘Second Gen’ Applications

February 22, 2017

Just what constitutes HPC and how best to support it is a keen topic currently. Read more…

By John Russell

HPE Extreme Performance Solutions

O&G Companies Create Value with High Performance Remote Visualization

Today’s oil and gas (O&G) companies are striving to process datasets that have become not only tremendously large, but extremely complex. And the larger that data becomes, the harder it is to move and analyze it – particularly with a workforce that could be distributed between drilling sites, offshore rigs, and remote offices. Read more…

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

IDC: Will the Real Exascale Race Please Stand Up?

February 21, 2017

So the exascale race is on. And lots of organizations are in the pack. Government announcements from the US, China, India, Japan, and the EU indicate that they are working hard to make it happen – some sooner, some later. Read more…

By Bob Sorensen, IDC

ExxonMobil, NCSA, Cray Scale Reservoir Simulation to 700,000+ Processors

February 17, 2017

In a scaling breakthrough for oil and gas discovery, ExxonMobil geoscientists report they have harnessed the power of 717,000 processors – the equivalent of 22,000 32-processor computers – to run complex oil and gas reservoir simulation models. Read more…

By Doug Black

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

IDC: Will the Real Exascale Race Please Stand Up?

February 21, 2017

So the exascale race is on. And lots of organizations are in the pack. Government announcements from the US, China, India, Japan, and the EU indicate that they are working hard to make it happen – some sooner, some later. Read more…

By Bob Sorensen, IDC

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

Drug Developers Use Google Cloud HPC in the Fight Against ALS

February 16, 2017

Within the haystack of a lethal disease such as ALS (amyotrophic lateral sclerosis / Lou Gehrig’s Disease) there exists, somewhere, the needle that will pierce this therapy-resistant affliction. Read more…

By Doug Black

Azure Edges AWS in Linpack Benchmark Study

February 15, 2017

The “when will clouds be ready for HPC” question has ebbed and flowed for years. Read more…

By John Russell

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

Cray Posts Best-Ever Quarter, Visibility Still Limited

February 10, 2017

On its Wednesday earnings call, Cray announced the largest revenue quarter in the company’s history and the second-highest revenue year. Read more…

By Tiffany Trader

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

US, China Vie for Supercomputing Supremacy

November 14, 2016

The 48th edition of the TOP500 list is fresh off the presses and while there is no new number one system, as previously teased by China, there are a number of notable entrants from the US and around the world and significant trends to report on. Read more…

By Tiffany Trader

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

Enlisting Deep Learning in the War on Cancer

December 7, 2016

Sometime in Q2 2017 the first ‘results’ of the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) will become publicly available according to Rick Stevens. He leads one of three JDACS4C pilot projects pressing deep learning (DL) into service in the War on Cancer. Read more…

By John Russell

D-Wave SC16 Update: What’s Bo Ewald Saying These Days

November 18, 2016

Tucked in a back section of the SC16 exhibit hall, quantum computing pioneer D-Wave has been talking up its new 2000-qubit processor announced in September. Forget for a moment the criticism sometimes aimed at D-Wave. This small Canadian company has sold several machines including, for example, ones to Lockheed and NASA, and has worked with Google on mapping machine learning problems to quantum computing. In July Los Alamos National Laboratory took possession of a 1000-quibit D-Wave 2X system that LANL ordered a year ago around the time of SC15. Read more…

By John Russell

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

CPU Benchmarking: Haswell Versus POWER8

June 2, 2015

With OpenPOWER activity ramping up and IBM’s prominent role in the upcoming DOE machines Summit and Sierra, it’s a good time to look at how the IBM POWER CPU stacks up against the x86 Xeon Haswell CPU from Intel. Read more…

By Tiffany Trader

Leading Solution Providers

Nvidia Sees Bright Future for AI Supercomputing

November 23, 2016

Graphics chipmaker Nvidia made a strong showing at SC16 in Salt Lake City last week. Read more…

By Tiffany Trader

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

Dell Knights Landing Machine Sets New STAC Records

November 2, 2016

The Securities Technology Analysis Center, commonly known as STAC, has released a new report characterizing the performance of the Knight Landing-based Dell PowerEdge C6320p server on the STAC-A2 benchmarking suite, widely used by the financial services industry to test and evaluate computing platforms. The Dell machine has set new records for both the baseline Greeks benchmark and the large Greeks benchmark. Read more…

By Tiffany Trader

What Knights Landing Is Not

June 18, 2016

As we get ready to launch the newest member of the Intel Xeon Phi family, code named Knights Landing, it is natural that there be some questions and potentially some confusion. Read more…

By James Reinders, Intel

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

KNUPATH Hermosa-based Commercial Boards Expected in Q1 2017

December 15, 2016

Last June tech start-up KnuEdge emerged from stealth mode to begin spreading the word about its new processor and fabric technology that’s been roughly a decade in the making. Read more…

By John Russell

  • arrow
  • Click Here for More Headlines
  • arrow
Share This