Beyond Speeds and Feeds

By By Geoffrey James

July 13, 2009

High Performance Computing (HPC) was once limited to a select group of laboratories where scientists or engineers solved complex problems on huge mainframe “supercomputers” that cost millions of dollars to buy and maintain. Today the drop in the price of computer power has combined with new architectures for clustering to bring HPC to a wide range of applications inside a growing number of industries at a reasonable price.

“Computer power is the raw fuel for business innovation,” explains Dr. Jeff Layton, enterprise technologist for HPC at Dell Inc. “Making HPC available to a wider range of customers, and making it more cost-effective, will have a long-term effect, not just on productivity but also on the ability of companies to thrive, not only during difficult economic times but also for many years to come.”

Along with this democratization of HPC has come a growing understanding, among pundits and executives alike, that the traditional way of measuring HPC—the raw performance of a single CPU—seems out of date. As the computer industry leaps to more-complex computing environments, it has become clear that HPC performance must be redefined in order to encapsulate the wider business case, according to Scot Schultz, AMD’s senior strategic alliance manager for HPC.

“What’s important is not how fast the CPU can run a test suite but how effectively it can solve a real-life problem,” Schultz says.

Productivity Now Trumps Raw Performance
More and more analysts, OEMs and IT executives have come to understand that raw performance is less important than how the underlying architecture makes end users more productive. “The performance that’s actually delivered to end users is highly dependent on the chip architecture and how well the software can take advantage of it,” explains Layton.

IT managers who make HPC buying decisions based purely on those obsolete measurements risk getting less bang for their buck, according to John Spooner, an analyst at the market research firm Technology Business Research (TBR). “There are always going to be customers who want all-out performance and don’t care about anything else,” he admits, “but many companies are now embracing the idea that the greatest business value comes not from raw performance but from getting the maximum performance for your overall IT dollar.”

Companies that adopt HPC are typically less interested in “speed and feeds” than in creating a long-term competitive advantage. A case in point is the sport department of Ferrari, one of the first companies to test Microsoft’s Windows HPC Server 2008.

“Ferrari is always looking for the most-advanced technological solutions, and the same goes for software and engineering,” says Piergiorgio Grossi, head of information systems at Ferrari. Like many other companies embracing HPC today, Ferrari is using it widely across the corporation—“for our users, engineers and administrators,” Grossi says.

Companies need to be thinking about productivity as a performance measurement, according to Vince Mendillo, director of marketing for the HPC business group at Microsoft. “HPC is expanding into vertical markets, ranging from engineering to aerospace to energy and many other industries,” he explains. “Ultimately, HPC is about helping customers get the job done.”

Measuring Productivity
HPC has traditionally been measured in terms of the raw computing power of a single core on a single CPU. Using that primitive metric, the battle for “market leadership” has been primarily between the two leading CPU firms: AMD and Intel, according to Rob Enderle of the Enderle Group. “For decades, these two companies have traded positions as the ‘industry leader’ when it comes to raw performance figures,” he says.

It’s a contest that’s likely to continue for the foreseeable future, according to Ken Cayton, research manager for enterprise platforms at the market research firm IDC. “Both companies are constantly moving forward, so one would expect to see the same kind of leapfrog behavior we’ve seen so frequently in the past,” he says.

However, IT executives need to be aware that the traditional “speeds and feeds” measurement is largely irrelevant in a world in which HPC takes place on CPU chips that contain multiple cores, which are, in turn, harnessed into clusters. In a multiprocessing environment, other metrics such as power efficiency start becoming more important, according to TBR’s Spooner. “Because energy costs are such a big proportion of the expense of running a large data center, businesses now want to maximize the amount of work they get done for each unit of electricity they pay for,” he explains.

Indeed, some companies are finding that the hard limitation of their HPC computing isn’t raw performance but the amount of electricity they can get piped into their data center. Cayton relates an experience he recently had with a Manhattan firm that is doing financial analysis but has only a limited amount of power coming into the building. “It therefore is more concerned with how effectively its HPC system uses power than it is about how quickly one element of the system can perform calculations,” Cayton explains.

Architecture and Performance
With multiprocessing and clustering, the speed of an individual core is often far less important than the ability to move data around between the various chips, explains Jordan Selburn, principal analyst at the market research firm iSuppli.

“In a lot of areas and applications, raw horsepower isn’t a significant factor, because other standards drive the degree of speed needed and anything excess is just that: excess,” Selburn explains. “The key in HPC applications is how efficiently you can perform the needed function.”

And that efficiency is intimately tied to the underlying architecture of the CPU chip, according to Einar Rustad, vice president of business development at Numascale, a company that makes chip sets that link multiple CPUs into HPC clusters. “The challenge with multiprocessing is keeping everything in sync, which means that each CPU must have swift access to the data that’s been processed by the other CPUs,” he explains.

To accomplish this, the cluster must be able to move data around quickly, something the HyperTransport™ architecture that AMD uses makes relatively easy. “With other chip architectures, you have to move data around by using the front-side bus, which is not only ungainly from an electronics viewpoint but also incurs a lot of overhead and prevents a true shared memory architecture with cache coherence,” says Rustad. “AMD’s HyperTransport technology, by contrast, makes it easier to connect CPUs together in a way that enables programmers to address the combined memory space and to benefit from the aggregated memory bandwidth.”

One benefit of directly connecting the chips is a potential decrease in data latency, which means that each CPU in the cluster will spend less time idling and more time actually processing data, according to Gilad Shainer, director of technical marketing for Mellanox Technologies, a leading supplier of semiconductor-based server and storage interconnect products.

“AMD has a good vision of how HPC should be handled,” Shainer says. “Its technological architecture provides value for many applications and end users, which is why we’re happy to collaborate with it to build the kind of balanced systems that companies want to buy.”

Real-Life Productivity
A chip architecture that handles data more efficiently can also make life easier for HPC programmers—an important issue in IT groups that may have limited access to top programming talent.

“One of the big limitations in HPC is adapting programs to run in parallel,” says Dell’s Layton. “The computer industry has been struggling for years with limitations on memory bandwidth per core, but that’s finally beginning to ease up, largely as the result of improvements in basic CPU architecture.”

Because programming for HPC is becoming easier, it’s beginning to show up in more industries and application areas. And that, in turn, has further lessened the importance of raw computing power as the primary HPC benchmark, because every industry has different requirements when it comes to the type of computing power that’s applicable to that industry. For example, financial HPC applications make extensive use of floating point, an area in which AMD’s architecture has a “slight edge” over other architectures, according to Christian Heidarson, an analyst at the market research firm Gartner.

HPC-friendly chip architecture can also make a future upgrade path easier. “Because HPC applications tend to be complex, companies are leery of pulling out their current systems and replacing them with new ones,” explains Layton, who notes that AMD has been designing CPU architectures that are socket-compatible, making it possible to upgrade a system without reloading and reconfiguring the software. The only change to the system that’s required is a BIOS upgrade, which takes a few minutes as opposed to the hours or days it might take to completely reconstruct a clustered system. “This makes it possible for a company to upgrade while limiting the downtime and cost risks inherent in re-creating and reinitializing the entire cluster,” says Layton.

In short, the raw performance of a single CPU may not be the best measurement of HPC. Rather, a metric such as the total cost of ownership (TCO) can provide a better baseline by which to judge systems and their underlying chip architecture.

“It’s a big change from the way people are used to thinking about HPC,” says AMD’s Schultz. “However, focusing on productivity means that companies can purchase their computer power more wisely and get the most benefit from their IT dollars.

For more on HPC solutions based on AMD Opteron™ processors go to www.amd.com/istanbulsolutions.

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

Intel and Trump Announce $7B for Fab 42 Targeting 7nm

February 8, 2017

In what may be an attempt by President Trump to reset his turbulent relationship with the high tech industry, he and Intel CEO Brian Krzanich today announced plans to invest more than $7 billion to complete Fab 42. Read more…

By John Russell

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