Duke University anticipates $100,000 or more per year in energy savings, while increasing processing power.

By Nicole Hemsoth

November 1, 2010

Duke University anticipates $100,000 or more per year in energy savings, while increasing processing power.

Crunching large quantities of data is a crucial component of modern academic life. On university campuses, everyone from chemists and engineers to researchers in sociology, economics and even literature needs access to high-performance computing (HPC). At Duke University, the Duke Shared Cluster Resource (DSCR) supports these needs for professors across the spectrum.

The DSCR serves 650 end users in 70 different research groups. One major research area that the DSCR caters to is the bioinformatics community. “Several of our professors are doing genome comparisons,” says John Pormann, Duke’s director of scalable computing. “Some researchers are building models that establish probabilities for when certain genes arose—and when species with a common ancestor became distinct. One is trying to develop the tree of life for a set of fungi by looking at genetics.”

Many bioinformatics researchers need to process an unprecedented volume of data. “One of our professors is working with a grant agency that gives grant recipients the newest, fastest gene-sequencing machine, rather than offering a large amount of money,” Pormann says. “Professors receive a cutting-edge gene sequencer, which spits out enormous amounts of data. They depend on the DSCR to provide an HPC environment that supports their data analysis needs.”

Cutting-edge research using limited power

In its efforts to meet those needs, the DSCR faces substantial logistical challenges. The building that houses the data center was constructed to hold classrooms, not a server farm. The data center has already maxed out the amount of electricity that can run through the building’s conduit. Its floor is raised only 12 inches, and the last air conditioning installation involved overhead units because the installers weren’t convinced they could push enough air through the floor to keep all the equipment cool.

“If we exceed the capacity of our current air conditioning unit, we have to go back to the drawing board,” says Pormann. “Adding power to our current location would be expensive because we’d have to bring in new power lines from the street, digging up sidewalks and parking lots in the process. Moving to a new data center would cost well into the six figures. We’d like to stay where we are, but that means we need to use the power and cooling in that room as efficiently as possible. It’s imperative as we expand our computing power that we keep our power and cooling resources constant.”

168 fewer watts per server

The DSCR needs to maximize the ratio of processing power to energy consumption for servers in its HPC cluster. The cluster encompasses 729 servers, from Dell PowerEdge M610 blade servers with Intel Xeon processor 5600 series to seven-year-old rack-mounted boxes. Oracle Grid Engine dynamically provisions application workloads to the most appropriate resources in the cluster.

To gain insight into the DSCR’s balance between processing power and consumption of energy and cooling resources, Pormann embarked on research of his own. He studied how CPU utilization correlates to power consumption in the cluster. For more than a year he collected data on the wattage drawn by the cluster’s primary servers, all Dell dual-CPU, quad-core machines, running their normal workload.

The comparison between machines at 100 percent CPU utilization is striking: Each of the data center’s rack-mounted Dell PowerEdge 1950 servers with Intel Xeon processor X5355 uses 369 watts. Its Dell PowerEdge M600 blade servers with Intel Xeon processor E5420 use 221 watts each. And its PowerEdge M610 blades with Intel Xeon processor E5520 use 201 watts. In three generations, PowerEdge servers reduced their power consumption by 168 watts, or 46 percent, at 100 percent CPU utilization.

“Across the board, from idle performance up to 100 percent CPU utilization, we see significant drops in power consumption on new Dell blade servers,” Pormann reports. “The form factor itself reduces energy needs because blades have fewer, larger, more efficient power supplies, and that’s clearly a factor in the sharp decline in power consumption that we see between the PowerEdge 1950 servers and the PowerEdge M610 blades.”

Comparing the Dell PowerEdge M600 blades with Intel Xeon processor E5420 and the PowerEdge M610 blades with Intel Xeon processor E5520 shows the difference a more efficient processor can make. “The across-the-board drop of roughly 20 watts is primarily attributable to CPU improvements,” says Pormann. “This suggests that all workloads would see significant improvements in energy savings from simply moving to the new CPUs. No matter what load is placed on the system, we should see significant reductions in power usage.”

$100,000-plus per year in energy cost savings

In addition to helping the DSCR stay in its current location, reducing servers’ power usage—both directly and by reducing air conditioning usage—saves the university money on an ongoing basis. “Even with North Carolina’s below-average power costs, we’re seeing savings of $100,000 or more per year, just by reducing our energy usage,” Pormann says.

As energy consumption falls, processing power grows dramatically with each new generation of Dell blades. “Every time we add a Dell PowerEdge M610 blade, we can pull older nodes from the cluster and retain the same processing power,” Pormann says. “When we buy new equipment, our users are always astounded at how much faster their jobs run. But we can’t directly calculate how many older nodes are comparable to a new blade. For one researcher, a new blade might replace eight older servers, but for another researcher that ratio might be 12 to 1.”

The DSCR just implemented six new 12-CPU-core PowerEdge M610 blades with Intel Xeon processor 5600 series and 96 gigabytes of memory per blade. “We’re really looking forward to seeing what they can do,” says Pormann. “Our early data indicates that they use no more power than our 8-CPU-core PowerEdge M610 blades with Intel Xeon processor E5520. So we should see a 50 percent increase in computational capability with zero increase in power consumption.”

Available capacity in the HPC cluster indicates that the new Dell PowerEdge blades are giving the cluster a substantial boost in processing power. Historically, the DSCR has run at about 70 percent of its total capacity. Since recent additions of Dell blades, utilization has declined to around 50 percent, so the cluster’s unused capacity has increased by as much as 30 percent. “Because we have more head room, we have the capability for researchers to do different kinds of experimentation,” says Pormann. “They don’t have to worry about wasting capacity anymore. They appreciate that whenever they need more computational power, it’s here.”

Pormann attributes the performance gains of the latest Dell servers to advancements, in part, in their management of memory. “More and more of our users are asking about large memory configurations,” he says. “It seems research projects are starting to be constrained by node memory performance and capacity. Over the last nine months, three different professors involved in bioinformatics have asked me whether they can get 256 or 512 gigabytes of memory in a single blade. One of them is working with images, each of which is on the order of a terabyte in size. I told them that systems with those memory configurations are on the Dell road map. The integrated memory controller and the Intel QuickPath architecture give the Dell blades exceptional bandwidth for memory processing.”

The DSCR further improves performance within the cluster using the Intel Compiler Suite. “We’re leveraging the Intel compilers as much as possible,” Pormann says. “What we’ve seen so far is that the Intel compilers, compared with the open source compilers, provide anywhere from 20 to 50 percent improvement in performance. You run the exact same C code through the Intel compiler, and the executable is faster. The Intel compilers seem to take advantage of all the bells and whistles in these new Intel processors.”

Server management tools bring additional efficiencies

Now Pormann is figuring out better ways to use the tools at his disposal to manage power for the cluster’s servers. The DSCR uses Dell Chassis Management Controller (CMC) to monitor energy consumption of the blades. Then IPMItool, an open source utility, exports this data to the Oracle Grid Engine. “Dell has its own add-ons to IPMItool,” Pormann says. “We were able to talk to the Dell engineering group, and they gave us information about the command line interfaces we could use to gather this data for Grid Engine.”

Pormann and his team currently can use Dell CMC to remotely control power usage within the cluster. “Dell CMC should enable us to easily power off machines and idle groups of machines to reduce the cluster’s overall heat load,” says Pormann.

The next step is to automate the process of powering off servers through Oracle Grid Engine. “An idle machine still uses more than 100 watts,” says Pormann. “Throttling the CPU may reduce power consumption, but it should be used in conjunction with powering off unused machines. And our systems should be capable of powering machines down automatically so someone doesn’t have to push buttons 24×7.  Knowing we have this potential in the blades helps us justify our continuing commitment to building out these tools.”

Mapping the cluster’s future

Duke purchases most of the cluster’s hardware from Dell for several reasons. One is the product road map from Dell and Intel. “We like Dell’s track record of always putting the newest equipment from Intel in their hardware,” Pormann says. “When Intel announces a new chip, we know we’re going to see it in Dell’s equipment shortly. Knowing what’s coming on those road maps enables us to spend our money very wisely.”

Perhaps the most important reason why the DSCR continues to purchase from Dell is that Pormann has always been pleased with the support he’s received. “Anytime we have a hardware issue, Dell cross-ships us parts and gives us access to engineers,” says Pormann. “As long as Dell and Intel continue to work on efficiency in the ratio of processing power to energy consumption, we’ll be able to continue to increase computational power, even as we stay in our current data center.”

For more information visit Dell.

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!

Advancing Modular Supercomputing with DEEP and DEEP-ER Architectures

February 24, 2017

Knowing that the jump to exascale will require novel architectural approaches capable of delivering dramatic efficiency and performance gains, researchers around the world are hard at work on next-generation HPC systems. Read more…

By Sean Thielen

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

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…

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

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

Advancing Modular Supercomputing with DEEP and DEEP-ER Architectures

February 24, 2017

Knowing that the jump to exascale will require novel architectural approaches capable of delivering dramatic efficiency and performance gains, researchers around the world are hard at work on next-generation HPC systems. Read more…

By Sean Thielen

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

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

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

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

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

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

Leading Solution Providers

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

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

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

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

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

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

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