IDC: Will the Real Exascale Race Please Stand Up?

By Bob Sorensen, IDC

February 21, 2017

 

Editor’s note: In this commentary, Bob Sorensen, research vice president, IDC High Performance Computing group, argues it’s clear we’ll get to exascale soon, but it’s hardly clear exactly what that will look like. In fact, says Sorensen, there will likely be several flavors of exascale, each favoring different applications and different technologies.

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. Meanwhile commercial concerns, either working in conjunction with a government partner, or going it alone, are also looking at similar development agendas. So it’s a pretty safe bet that someone will stand up an exascale system in the next few years. Some will celebrate while others will gnash their teeth. So while we can all agree that there is an exascale race, based on a look at the various visions for such a system, most seem to have their own idea of where the finish line is.

In the past when the HPC community went through its periodic assault on computer performance expressed in scientific notation (gflops, tflops, pflops, etc.), HPC systems had relatively narrow use cases, and computation capability – the ability to churn floating point operations was the undisputed king of performance metrics. That’s what made benchmarks like the Livermore Loops and later the more enduring LINPACK metric – and its related TOP500 list – widely adopted, frequently executed, and frankly over quoted. But at least for most of these earlier generations, the benchmarks were grounded in a broad base of typical HPC workloads. And while the race may not have always gone to the swift, everyone was at least running in the same direction.

Bob Sorensen, IDC

For the exascale race, that is simply no longer the case. The profusion of new and evolving HPC use cases, applications, and related architectures that are all being collectively jammed under the exascale umbrella makes that impossible. A few examples here should suffice:

High performance data analytics is a legitimate and growing segment of the HPC universe, but there the rapid growth of data sets, the addition of new unstructured data such as voice, video, and IoT input, and the need for real-time analytics clearly trump pure processor speed. Performance metrics for HPDA applications abound, but the most relevant simply do not pin their hopes on floating point rates. In addition, an interesting force behind the evolution of HPDA development will be growing legions of traditional – and decidedly non-HPC – business analytics users who are being pushed into the HPDA realm due to the spate of new business opportunities in this space. This group has little interest in the future of HPC as a technological driver and simply wants whatever solves the problem.

Likewise, deep learning is one of the latest and most promising HPC use cases, but there, training applications typically involve long but relatively straightforward computations – indeed often using only 16-bit floating point – to extract insights from data. These systems rely on more simple but high-core count processors with less rigorous capabilities in memory and bandwidth. As such, deep learning systems are well suited to win their version of the exascale race, but it is clear that such systems will not become the sine qua non for all exascale applications.

Large servers that sit in hyperscale data centers likely will also soon be able to lay claim to being exascale systems in that they possess the aggregate processing power and necessary network capability to meet the definition. This is an undeniable effect of the use of mass clustered COT-like systems to achieve high computational capability, but in most cases it is safe to conclude that these exascale systems will not be used as a single user asset but instead be routinely partitioned across very many users: they may benchmark as exascale, but they will not be used as exascale.

Even within the traditional HPC modeling and simulation sector, users are increasingly turning to more sophisticated metrics for what they want out of an exascale HPC, such as efficiency (flops/watt), or data center space requirements (flops/rack). Likewise, more and more exascale plans cite the need for new machines to achieve not peak exascale, but sustained exascale on typical workloads, and even specific improvements in time to solution for an existing suite of applications. The intent of many of these new progressive requirements is to push the emphasis of exascale architectures away from pure computational performance and to instead highlight the need for a more comprehensive hardware and software ecosystem that can underwrite an effective exascale workflow. In such environments, the exascale goal means more about overall system solution value and utility than any single hardware or software metric.

Because there are so many paths to an exascale system, the field will over the next few years be filled with announcements of a first, second, and eventually an nth exascale rollout. Careful examination of what finish line each machine crossed can only help to provide insights as to what the true value of that system is and how effectively it adds to the body of knowledge within the HPC world. Each new system will no doubt serve a valuable function in its own right, but it is clear that the sector has moved beyond a one size fits all mentality, and that decision makers – both within the commercial and government sectors – need to remember this when making plans about new HPC developments, at least until the next triple in scientific notation comes along. That would be zettaflops.

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!

Researchers Scale COSMO Climate Code to 4888 GPUs on Piz Daint

October 17, 2017

Effective global climate simulation, sorely needed to anticipate and cope with global warming, has long been computationally challenging. Two of the major obstacles are the needed resolution and prolonged time to compute Read more…

By John Russell

Student Cluster Competition Coverage New Home

October 16, 2017

Hello computer sports fans! This is the first of many (many!) articles covering the world-wide phenomenon of Student Cluster Competitions. Finally, the Student Cluster Competition coverage has come to its natural home: H Read more…

By Dan Olds

UCSD Web-based Tool Tracking CA Wildfires Generates 1.5M Views

October 16, 2017

Tracking the wildfires raging in northern CA is an unpleasant but necessary part of guiding efforts to fight the fires and safely evacuate affected residents. One such tool – Firemap – is a web-based tool developed b Read more…

By John Russell

HPE Extreme Performance Solutions

Transforming Genomic Analytics with HPC-Accelerated Insights

Advancements in the field of genomics are revolutionizing our understanding of human biology, rapidly accelerating the discovery and treatment of genetic diseases, and dramatically improving human health. Read more…

Exascale Imperative: New Movie from HPE Makes a Compelling Case

October 13, 2017

Why is pursuing exascale computing so important? In a new video – Hewlett Packard Enterprise: Eighteen Zeros – four HPE executives, a prominent national lab HPC researcher, and HPCwire managing editor Tiffany Trader Read more…

By John Russell

Student Cluster Competition Coverage New Home

October 16, 2017

Hello computer sports fans! This is the first of many (many!) articles covering the world-wide phenomenon of Student Cluster Competitions. Finally, the Student Read more…

By Dan Olds

Intel Delivers 17-Qubit Quantum Chip to European Research Partner

October 10, 2017

On Tuesday, Intel delivered a 17-qubit superconducting test chip to research partner QuTech, the quantum research institute of Delft University of Technology (TU Delft) in the Netherlands. The announcement marks a major milestone in the 10-year, $50-million collaborative relationship with TU Delft and TNO, the Dutch Organization for Applied Research, to accelerate advancements in quantum computing. Read more…

By Tiffany Trader

Fujitsu Tapped to Build 37-Petaflops ABCI System for AIST

October 10, 2017

Fujitsu announced today it will build the long-planned AI Bridging Cloud Infrastructure (ABCI) which is set to become the fastest supercomputer system in Japan Read more…

By John Russell

HPC Chips – A Veritable Smorgasbord?

October 10, 2017

For the first time since AMD's ill-fated launch of Bulldozer the answer to the question, 'Which CPU will be in my next HPC system?' doesn't have to be 'Whichever variety of Intel Xeon E5 they are selling when we procure'. Read more…

By Dairsie Latimer

Delays, Smoke, Records & Markets – A Candid Conversation with Cray CEO Peter Ungaro

October 5, 2017

Earlier this month, Tom Tabor, publisher of HPCwire and I had a very personal conversation with Cray CEO Peter Ungaro. Cray has been on something of a Cinderell Read more…

By Tiffany Trader & Tom Tabor

Intel Debuts Programmable Acceleration Card

October 5, 2017

With a view toward supporting complex, data-intensive applications, such as AI inference, video streaming analytics, database acceleration and genomics, Intel i Read more…

By Doug Black

OLCF’s 200 Petaflops Summit Machine Still Slated for 2018 Start-up

October 3, 2017

The Department of Energy’s planned 200 petaflops Summit computer, which is currently being installed at Oak Ridge Leadership Computing Facility, is on track t Read more…

By John Russell

US Exascale Program – Some Additional Clarity

September 28, 2017

The last time we left the Department of Energy’s exascale computing program in July, things were looking very positive. Both the U.S. House and Senate had pas Read more…

By Alex R. Larzelere

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

NERSC Scales Scientific Deep Learning to 15 Petaflops

August 28, 2017

A collaborative effort between Intel, NERSC and Stanford has delivered the first 15-petaflops deep learning software running on HPC platforms and is, according Read more…

By Rob Farber

Oracle Layoffs Reportedly Hit SPARC and Solaris Hard

September 7, 2017

Oracle’s latest layoffs have many wondering if this is the end of the line for the SPARC processor and Solaris OS development. As reported by multiple sources Read more…

By John Russell

US Coalesces Plans for First Exascale Supercomputer: Aurora in 2021

September 27, 2017

At the Advanced Scientific Computing Advisory Committee (ASCAC) meeting, in Arlington, Va., yesterday (Sept. 26), it was revealed that the "Aurora" supercompute Read more…

By Tiffany Trader

Google Releases Deeplearn.js to Further Democratize Machine Learning

August 17, 2017

Spreading the use of machine learning tools is one of the goals of Google’s PAIR (People + AI Research) initiative, which was introduced in early July. Last w Read more…

By John Russell

GlobalFoundries Puts Wind in AMD’s Sails with 12nm FinFET

September 24, 2017

From its annual tech conference last week (Sept. 20), where GlobalFoundries welcomed more than 600 semiconductor professionals (reaching the Santa Clara venue Read more…

By Tiffany Trader

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

Leading Solution Providers

Amazon Debuts New AMD-based GPU Instances for Graphics Acceleration

September 12, 2017

Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The Read more…

By John Russell

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

EU Funds 20 Million Euro ARM+FPGA Exascale Project

September 7, 2017

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development. Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work... Read more…

By Tiffany Trader

Delays, Smoke, Records & Markets – A Candid Conversation with Cray CEO Peter Ungaro

October 5, 2017

Earlier this month, Tom Tabor, publisher of HPCwire and I had a very personal conversation with Cray CEO Peter Ungaro. Cray has been on something of a Cinderell Read more…

By Tiffany Trader & Tom Tabor

Cray Moves to Acquire the Seagate ClusterStor Line

July 28, 2017

This week Cray announced that it is picking up Seagate's ClusterStor HPC storage array business for an undisclosed sum. "In short we're effectively transitioning the bulk of the ClusterStor product line to Cray," said CEO Peter Ungaro. Read more…

By Tiffany Trader

Intel Launches Software Tools to Ease FPGA Programming

September 5, 2017

Field Programmable Gate Arrays (FPGAs) have a reputation for being difficult to program, requiring expertise in specialty languages, like Verilog or VHDL. Easin Read more…

By Tiffany Trader

IBM Advances Web-based Quantum Programming

September 5, 2017

IBM Research is pairing its Jupyter-based Data Science Experience notebook environment with its cloud-based quantum computer, IBM Q, in hopes of encouraging a new class of entrepreneurial user to solve intractable problems that even exceed the capabilities of the best AI systems. Read more…

By Alex Woodie

Intel, NERSC and University Partners Launch New Big Data Center

August 17, 2017

A collaboration between the Department of Energy’s National Energy Research Scientific Computing Center (NERSC), Intel and five Intel Parallel Computing Cente Read more…

By Linda Barney

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