Hyperion (IDC) Paints a Bullish Picture of HPC Future

By John Russell

April 20, 2017

Hyperion Research – formerly IDC’s HPC group – yesterday painted a fascinating and complicated portrait of the HPC community’s health and prospects at the HPC User Forum held in Albuquerque, NM. HPC sales are up and growing ($22 billion, all HPC segments, 2016). Global exascale plans are solidifying (who, what, when, and how much ($)). The new kid on the block – all things ‘big’ data driven – is becoming an adolescent and behaving accordingly. And HPC ROI, at least as measured by Hyperion, is $551 per $1 invested (revenue growth) and $52 per $1 of profit invested.

This new version of HPC has been taking shape for some time and most of the themes are familiar (see HPCwire 2015 article, IDC: The Changing Face of HPC): industry consolidation, SGI’s acquisition by HPE along with the Dell EMC merger being the most recent; accelerated computing versus Moore’s Law; the growing appetite of HPC technology suppliers for expansion into the enterprise; big data’s transformation into a more nuanced multi-faceted blend of technologies and applications making it a form of HPC. These are just a few of the major trends laid out by Hyperion at its HPC User Forum.

All netted down, HPC is still expected to be a growth market, according to Earl Joseph, now CEO of Hyperion, which is expected to be acquired by year’s end. Joseph cited the following drivers:

  • Growing recognition of HPC’s strategic value.
  • HPDA, including ML/DL, cognitive and AI.
  • HPC in the cloud will lift the sector writ large.

“There’s a lot of growth in the upper half of the market and we are back to slowdown in the lower half of the market,” said Joseph. “Supercomputers are showing a very good recovery but they still haven’t hit the high point (~$5 billion) of three or four years ago.” They likely won’t get back to that level till 2022/2023 suggested Joseph.

Overall the HPC market segments have tended to hold their position. Storage ($4,316 million) remained the largest non-server segment and the fastest growing segment overall with a 7.8 percent annual growth expected over the next five years.

Vendor jockeying will continue he noted. Consolidation has been a major factor. HPE topped the revenue list in 2016 and will likely do so again in 2017 when SGI’s revenue is added. Dell EMC would no doubt question that and it will be interesting to watch this rivalry. IBM has never recovered its position after jettisoning its x86 businesses. The battle between x86 offerings, IBM Power, and ARM continues with both Europe and Japan making substantial bets on ARM for HPC uses. Indeed, the rise of heterogeneous computing generally is creating new opportunities for a variety of accelerators and accelerated systems.

These are the top HPC server suppliers by revenue ($ millions) according to Hyperion: HPE/HP ($3,878), Dell ($2,014), Lenovo ($909), IBM ($492), Cray ($461), Sugon ($315), Fujitsu ($226), SGI ($169), NEC ($166), Bull Atos ($118), and Other ($2,453). Interesting to note that “Other” is the second largest total revenue.

Not surprisingly, Hyperion looked closely at the intensifying race for exascale machines. China, for example, has three efforts on the path to exascale. Joseph expects China to be first to stand up an exascale. “They are saying 2019 but we’re not sure they will hit that date. We’re saying 2020,” said Joseph. The major players – U.S., EU, Japan, and China – are all speeding up their efforts. In the U.S., for example, Path Forward awards are expected soon.

Many questions remain. China is still selecting final vendors, something that was supposed to be done last fall said Joseph. Japan’s design is the closest to being “locked in” with the prime contractor Fujitsu having settled on an ARM-based architecture. But that project has experienced some delay and its financing method is not fixed.

“According to Japan’s latest announcement, their machine will be up in 2023 but we really expect it to be 2024. The cost may be a bit higher too, $800 million to $900-plus million range. Also, the Japanese government has not yet agreed to fund the whole system. They are funding it one year at time,” said Joseph.

Nevertheless, exascale funds are starting to flow and plans are taking firmer shape. As shown here, Hyperion has characterized the major exascale programs and forecast likely costs, technology choices, and timetables. Paul Messina, director of the U.S. Exascale Computing Project, provided an update at the HPC User Forum and HPCwire will have detailed coverage of the U.S. effort shortly.

Predictably, the Hyperion presentation covered a lot of ground drawn from Hyperion/IDC’s ongoing research efforts. Steve Conway, another IDC veteran and now Hyperion SVP research, reviewed the adoption of HPDA as well as zeroing in on two of its drivers, deep learning and machine learning. You may recall that IDC was one of the first to recognize the rise of data analytics as part of HPC. Clearly there are many potential uses cases Conway said. Today, the HPC-HPDA convergence is taken for granted and is depicted in the slide below.

Hyperion has just created four new data-intensive segments, bulleted here, with more to follow:

  • Fraud and anomaly detection. Two example use cases include government (intelligence, cyber security) and industry (credit card fraud, cyber security).
  • Affinity Marketing. Discern potential customers’ demographics, buying preferences and habits.
  • Business intelligence. Identify opportunities to advance market position and competitiveness.
  • Precision Medicine. Personalized approach to improve outcomes, control costs.

“Fraud and anomaly detection are the largest today. Business intelligence is growing quickly. The tortoise that will probably win the race is precision medicine because of the size of the health care over time,” said Conway, noting the HPDA market is growing two to three times faster than traditional overall HPC market.

Not surprisingly, deep learning is the darling of this frontier and also the most technically challenging. Singling out precision medicine as a promising area for DL, Conway said “IBM Watson is the name that’s known here but I promise you x86 clusters are doing the same thing.”

Making the machine learning to deep learning shift is a difficult journey said Conway. Having enough data both to train deep learning systems and also to infer high fidelity decisions when put into practice is the big challenge. “If you are in the realm of Google or Baidu or Facebook, you have plenty of data. If you are outside of that realm you are in trouble. In most of these realms you do not have enough data to do deep learning,” said Conway.

“One case in point, and we have many of them: We talked to the United Health Group which has about 100 million people that it covers; that’s not nearly enough to do the deep learning they need and they know it. They have built a facility in Cambridge, Mass., and invited competitors to come in and to pool anonymized data to try to get to the point where they can actually start playing with deep learning. This is a big issue.”

Aside from having enough data, there’s the computation challenge. Today, GPUs “rule the roost in these ecosystems, with the software built around them, but we expect to see other things like Intel Phis and the remarkable resurgence of FPGAs have a role. Another big issue vendors are having here is there really aren’t good benchmarks and they spend too much time just trying to decide what would be satisfactory results,” Conway said.

In earlier studies HPC user willingness to deploy in the cloud has often seemed tepid. Costs, security, adequate performance (data movement, computation, and storage) were all concerns, especially so in public cloud. Hyperion suggested attitudes seem to be changing and reported a jump in the number of HPC sites using public clouds – 64 percent now up from 13 percent in 2011. Conway cautioned that the size and number of jobs were still limited to a small proportion of any give user’s needs. Conversely, suggested Conway, private and hybrid cloud use was growing fast and held more near-term promise.

Despite the great flux within HPC many areas have changed little according to Hyperion. For example, software problems (management s/w, parallel s/w, license issues, etc.) remain the number one pain point to HPC adoption or use according to Hyperion research. This prompted a member of the audience to say, “Earl, this looks like exactly the same IDC slide I saw ten years ago.” It sort of is.

Storage access time was now the number two complaint, followed by clusters still too hard to use and manage.

Hyperion presented a fair amount of detail concerning its ROI study and is making the full data available to requesters. (Download Results: www.hpcuserforum.com/ROI)

Slides courtesy of Hyperion Research.

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!

RSC Reports 500Tflops, Hot Water Cooled System Deployed at JINR

April 18, 2018

RSC, developer of supercomputers and advanced HPC systems based in Russia, today reported deployment of “the world's first 100% ‘hot water’ liquid cooled supercomputer” at Joint Institute for Nuclear Research (JI Read more…

By Staff

New Device Spots Quantum Particle ‘Fingerprint’

April 18, 2018

Majorana particles have been observed by university researchers employing a device consisting of layers of magnetic insulators on a superconducting material. The advance opens the door to controlling the elusive particle Read more…

By George Leopold

Cray Rolls Out AMD-Based CS500; More to Follow?

April 18, 2018

Cray was the latest OEM to bring AMD back into the fold with introduction today of a CS500 option based on AMD’s Epyc processor line. The move follows Cray’s introduction of an ARM-based system (XC-50) last November. Read more…

By John Russell

HPE Extreme Performance Solutions

HPC and AI Convergence is Accelerating New Levels of Intelligence

Data analytics is the most valuable tool in the digital marketplace – so much so that organizations are employing high performance computing (HPC) capabilities to rapidly collect, share, and analyze endless streams of data. Read more…

Hennessy & Patterson: A New Golden Age for Computer Architecture

April 17, 2018

On Monday June 4, 2018, 2017 A.M. Turing Award Winners John L. Hennessy and David A. Patterson will deliver the Turing Lecture at the 45th International Symposium on Computer Architecture (ISCA) in Los Angeles. The Read more…

By Staff

Cray Rolls Out AMD-Based CS500; More to Follow?

April 18, 2018

Cray was the latest OEM to bring AMD back into the fold with introduction today of a CS500 option based on AMD’s Epyc processor line. The move follows Cray’ Read more…

By John Russell

IBM: Software Ecosystem for OpenPOWER is Ready for Prime Time

April 16, 2018

With key pieces of the IBM/OpenPOWER versus Intel/x86 gambit settling into place – e.g., the arrival of Power9 chips and Power9-based systems, hyperscaler sup Read more…

By John Russell

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

Cloud-Readiness and Looking Beyond Application Scaling

April 11, 2018

There are two aspects to consider when determining if an application is suitable for running in the cloud. The first, which we will discuss here under the title Read more…

By Chris Downing

Transitioning from Big Data to Discovery: Data Management as a Keystone Analytics Strategy

April 9, 2018

The past 10-15 years has seen a stark rise in the density, size, and diversity of scientific data being generated in every scientific discipline in the world. Key among the sciences has been the explosion of laboratory technologies that generate large amounts of data in life-sciences and healthcare research. Large amounts of data are now being stored in very large storage name spaces, with little to no organization and a general unease about how to approach analyzing it. Read more…

By Ari Berman, BioTeam, Inc.

IBM Expands Quantum Computing Network

April 5, 2018

IBM is positioning itself as a first mover in establishing the era of commercial quantum computing. The company believes in order for quantum to work, taming qu Read more…

By Tiffany Trader

FY18 Budget & CORAL-2 – Exascale USA Continues to Move Ahead

April 2, 2018

It was not pretty. However, despite some twists and turns, the federal government’s Fiscal Year 2018 (FY18) budget is complete and ended with some very positi Read more…

By Alex R. Larzelere

Nvidia Ups Hardware Game with 16-GPU DGX-2 Server and 18-Port NVSwitch

March 27, 2018

Nvidia unveiled a raft of new products from its annual technology conference in San Jose today, and despite not offering up a new chip architecture, there were still a few surprises in store for HPC hardware aficionados. Read more…

By Tiffany Trader

Inventor Claims to Have Solved Floating Point Error Problem

January 17, 2018

"The decades-old floating point error problem has been solved," proclaims a press release from inventor Alan Jorgensen. The computer scientist has filed for and Read more…

By Tiffany Trader

Researchers Measure Impact of ‘Meltdown’ and ‘Spectre’ Patches on HPC Workloads

January 17, 2018

Computer scientists from the Center for Computational Research, State University of New York (SUNY), University at Buffalo have examined the effect of Meltdown Read more…

By Tiffany Trader

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. Read more…

By Tiffany Trader

How the Cloud Is Falling Short for HPC

March 15, 2018

The last couple of years have seen cloud computing gradually build some legitimacy within the HPC world, but still the HPC industry lies far behind enterprise I Read more…

By Chris Downing

Fast Forward: Five HPC Predictions for 2018

December 21, 2017

What’s on your list of high (and low) lights for 2017? Volta 100’s arrival on the heels of the P100? Appearance, albeit late in the year, of IBM’s Power9? Read more…

By John Russell

Chip Flaws ‘Meltdown’ and ‘Spectre’ Loom Large

January 4, 2018

The HPC and wider tech community have been abuzz this week over the discovery of critical design flaws that impact virtually all contemporary microprocessors. T Read more…

By Tiffany Trader

How Meltdown and Spectre Patches Will Affect HPC Workloads

January 10, 2018

There have been claims that the fixes for the Meltdown and Spectre security vulnerabilities, named the KPTI (aka KAISER) patches, are going to affect applicatio Read more…

By Rosemary Francis

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

Leading Solution Providers

Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 19, 2018

Petaflop per second deep learning training performance on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer has given climate Read more…

By Rob Farber

Lenovo Unveils Warm Water Cooled ThinkSystem SD650 in Rampup to LRZ Install

February 22, 2018

This week Lenovo took the wraps off the ThinkSystem SD650 high-density server with third-generation direct water cooling technology developed in tandem with par Read more…

By Tiffany Trader

AI Cloud Competition Heats Up: Google’s TPUs, Amazon Building AI Chip

February 12, 2018

Competition in the white hot AI (and public cloud) market pits Google against Amazon this week, with Google offering AI hardware on its cloud platform intended Read more…

By Doug Black

HPC and AI – Two Communities Same Future

January 25, 2018

According to Al Gara (Intel Fellow, Data Center Group), high performance computing and artificial intelligence will increasingly intertwine as we transition to Read more…

By Rob Farber

New Blueprint for Converging HPC, Big Data

January 18, 2018

After five annual workshops on Big Data and Extreme-Scale Computing (BDEC), a group of international HPC heavyweights including Jack Dongarra (University of Te Read more…

By John Russell

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

Momentum Builds for US Exascale

January 9, 2018

2018 looks to be a great year for the U.S. exascale program. The last several months of 2017 revealed a number of important developments that help put the U.S. Read more…

By Alex R. Larzelere

Google Chases Quantum Supremacy with 72-Qubit Processor

March 7, 2018

Google pulled ahead of the pack this week in the race toward "quantum supremacy," with the introduction of a new 72-qubit quantum processor called Bristlecone. Read more…

By Tiffany Trader

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