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!

Why HPC Storage Matters More Now Than Ever: Analyst Q&A

September 17, 2021

With soaring data volumes and insatiable computing driving nearly every facet of economic, social and scientific progress, data storage is seizing the spotlight. Hyperion Research analyst and noted storage expert Mark No Read more…

GigaIO Gets $14.7M in Series B Funding to Expand Its Composable Fabric Technology to Customers

September 16, 2021

Just before the COVID-19 pandemic began in March 2020, GigaIO introduced its Universal Composable Fabric technology, which allows enterprises to bring together any HPC and AI resources and integrate them with networking, Read more…

What’s New in HPC Research: Solar Power, ExaWorks, Optane & More

September 16, 2021

In this regular feature, HPCwire highlights newly published research in the high-performance computing community and related domains. From parallel programming to exascale to quantum computing, the details are here. Read more…

Cerebras Brings Its Wafer-Scale Engine AI System to the Cloud

September 16, 2021

Five months ago, when Cerebras Systems debuted its second-generation wafer-scale silicon system (CS-2), co-founder and CEO Andrew Feldman hinted of the company’s coming cloud plans, and now those plans have come to fruition. Today, Cerebras and Cirrascale Cloud Services are launching... Read more…

AI Hardware Summit: Panel on Memory Looks Forward

September 15, 2021

What will system memory look like in five years? Good question. While Monday's panel, Designing AI Super-Chips at the Speed of Memory, at the AI Hardware Summit, tackled several topics, the panelists also took a brief glimpse into the future. Unlike compute, storage and networking, which... Read more…

AWS Solution Channel

Supporting Climate Model Simulations to Accelerate Climate Science

The Amazon Sustainability Data Initiative (ASDI), AWS is donating cloud resources, technical support, and access to scalable infrastructure and fast networking providing high performance computing (HPC) solutions to support simulations of near-term climate using the National Center for Atmospheric Research (NCAR) Community Earth System Model Version 2 (CESM2) and its Whole Atmosphere Community Climate Model (WACCM). Read more…

ECMWF Opens Bologna Datacenter in Preparation for Atos Supercomputer

September 14, 2021

In January 2020, the European Centre for Medium-Range Weather Forecasts (ECMWF) – a juggernaut in the weather forecasting scene – signed a four-year, $89-million contract with European tech firm Atos to quintuple its supercomputing capacity. With the deal approaching the two-year mark, ECMWF... Read more…

Why HPC Storage Matters More Now Than Ever: Analyst Q&A

September 17, 2021

With soaring data volumes and insatiable computing driving nearly every facet of economic, social and scientific progress, data storage is seizing the spotlight Read more…

Cerebras Brings Its Wafer-Scale Engine AI System to the Cloud

September 16, 2021

Five months ago, when Cerebras Systems debuted its second-generation wafer-scale silicon system (CS-2), co-founder and CEO Andrew Feldman hinted of the company’s coming cloud plans, and now those plans have come to fruition. Today, Cerebras and Cirrascale Cloud Services are launching... Read more…

AI Hardware Summit: Panel on Memory Looks Forward

September 15, 2021

What will system memory look like in five years? Good question. While Monday's panel, Designing AI Super-Chips at the Speed of Memory, at the AI Hardware Summit, tackled several topics, the panelists also took a brief glimpse into the future. Unlike compute, storage and networking, which... Read more…

ECMWF Opens Bologna Datacenter in Preparation for Atos Supercomputer

September 14, 2021

In January 2020, the European Centre for Medium-Range Weather Forecasts (ECMWF) – a juggernaut in the weather forecasting scene – signed a four-year, $89-million contract with European tech firm Atos to quintuple its supercomputing capacity. With the deal approaching the two-year mark, ECMWF... Read more…

Quantum Computer Market Headed to $830M in 2024

September 13, 2021

What is one to make of the quantum computing market? Energized (lots of funding) but still chaotic and advancing in unpredictable ways (e.g. competing qubit tec Read more…

Amazon, NCAR, SilverLining Team for Unprecedented Cloud Climate Simulations

September 10, 2021

Earth’s climate is, to put it mildly, not in a good place. In the wake of a damning report from the Intergovernmental Panel on Climate Change (IPCC), scientis Read more…

After Roadblocks and Renewals, EuroHPC Targets a Bigger, Quantum Future

September 9, 2021

The EuroHPC Joint Undertaking (JU) was formalized in 2018, beginning a new era of European supercomputing that began to bear fruit this year with the launch of several of the first EuroHPC systems. The undertaking, however, has not been without its speed bumps, and the Union faces an uphill... Read more…

How Argonne Is Preparing for Exascale in 2022

September 8, 2021

Additional details came to light on Argonne National Laboratory’s preparation for the 2022 Aurora exascale-class supercomputer, during the HPC User Forum, held virtually this week on account of pandemic. Exascale Computing Project director Doug Kothe reviewed some of the 'early exascale hardware' at Argonne, Oak Ridge and NERSC (Perlmutter), while Ti Leggett, Deputy Project Director & Deputy Director... Read more…

Ahead of ‘Dojo,’ Tesla Reveals Its Massive Precursor Supercomputer

June 22, 2021

In spring 2019, Tesla made cryptic reference to a project called Dojo, a “super-powerful training computer” for video data processing. Then, in summer 2020, Tesla CEO Elon Musk tweeted: “Tesla is developing a [neural network] training computer called Dojo to process truly vast amounts of video data. It’s a beast! … A truly useful exaflop at de facto FP32.” Read more…

Berkeley Lab Debuts Perlmutter, World’s Fastest AI Supercomputer

May 27, 2021

A ribbon-cutting ceremony held virtually at Berkeley Lab's National Energy Research Scientific Computing Center (NERSC) today marked the official launch of Perlmutter – aka NERSC-9 – the GPU-accelerated supercomputer built by HPE in partnership with Nvidia and AMD. Read more…

Esperanto, Silicon in Hand, Champions the Efficiency of Its 1,092-Core RISC-V Chip

August 27, 2021

Esperanto Technologies made waves last December when it announced ET-SoC-1, a new RISC-V-based chip aimed at machine learning that packed nearly 1,100 cores onto a package small enough to fit six times over on a single PCIe card. Now, Esperanto is back, silicon in-hand and taking aim... Read more…

Enter Dojo: Tesla Reveals Design for Modular Supercomputer & D1 Chip

August 20, 2021

Two months ago, Tesla revealed a massive GPU cluster that it said was “roughly the number five supercomputer in the world,” and which was just a precursor to Tesla’s real supercomputing moonshot: the long-rumored, little-detailed Dojo system. “We’ve been scaling our neural network training compute dramatically over the last few years,” said Milan Kovac, Tesla’s director of autopilot engineering. Read more…

CentOS Replacement Rocky Linux Is Now in GA and Under Independent Control

June 21, 2021

The Rocky Enterprise Software Foundation (RESF) is announcing the general availability of Rocky Linux, release 8.4, designed as a drop-in replacement for the soon-to-be discontinued CentOS. The GA release is launching six-and-a-half months after Red Hat deprecated its support for the widely popular, free CentOS server operating system. The Rocky Linux development effort... Read more…

Google Launches TPU v4 AI Chips

May 20, 2021

Google CEO Sundar Pichai spoke for only one minute and 42 seconds about the company’s latest TPU v4 Tensor Processing Units during his keynote at the Google I Read more…

Intel Completes LLVM Adoption; Will End Updates to Classic C/C++ Compilers in Future

August 10, 2021

Intel reported in a blog this week that its adoption of the open source LLVM architecture for Intel’s C/C++ compiler is complete. The transition is part of In Read more…

AMD-Xilinx Deal Gains UK, EU Approvals — China’s Decision Still Pending

July 1, 2021

AMD’s planned acquisition of FPGA maker Xilinx is now in the hands of Chinese regulators after needed antitrust approvals for the $35 billion deal were receiv Read more…

Leading Solution Providers

Contributors

Hot Chips: Here Come the DPUs and IPUs from Arm, Nvidia and Intel

August 25, 2021

The emergence of data processing units (DPU) and infrastructure processing units (IPU) as potentially important pieces in cloud and datacenter architectures was Read more…

Julia Update: Adoption Keeps Climbing; Is It a Python Challenger?

January 13, 2021

The rapid adoption of Julia, the open source, high level programing language with roots at MIT, shows no sign of slowing according to data from Julialang.org. I Read more…

10nm, 7nm, 5nm…. Should the Chip Nanometer Metric Be Replaced?

June 1, 2020

The biggest cool factor in server chips is the nanometer. AMD beating Intel to a CPU built on a 7nm process node* – with 5nm and 3nm on the way – has been i Read more…

HPE Wins $2B GreenLake HPC-as-a-Service Deal with NSA

September 1, 2021

In the heated, oft-contentious, government IT space, HPE has won a massive $2 billion contract to provide HPC and AI services to the United States’ National Security Agency (NSA). Following on the heels of the now-canceled $10 billion JEDI contract (reissued as JWCC) and a $10 billion... Read more…

Quantum Roundup: IBM, Rigetti, Phasecraft, Oxford QC, China, and More

July 13, 2021

IBM yesterday announced a proof for a quantum ML algorithm. A week ago, it unveiled a new topology for its quantum processors. Last Friday, the Technical Univer Read more…

Intel Launches 10nm ‘Ice Lake’ Datacenter CPU with Up to 40 Cores

April 6, 2021

The wait is over. Today Intel officially launched its 10nm datacenter CPU, the third-generation Intel Xeon Scalable processor, codenamed Ice Lake. With up to 40 Read more…

Frontier to Meet 20MW Exascale Power Target Set by DARPA in 2008

July 14, 2021

After more than a decade of planning, the United States’ first exascale computer, Frontier, is set to arrive at Oak Ridge National Laboratory (ORNL) later this year. Crossing this “1,000x” horizon required overcoming four major challenges: power demand, reliability, extreme parallelism and data movement. Read more…

Intel Unveils New Node Names; Sapphire Rapids Is Now an ‘Intel 7’ CPU

July 27, 2021

What's a preeminent chip company to do when its process node technology lags the competition by (roughly) one generation, but outmoded naming conventions make it seem like it's two nodes behind? For Intel, the response was to change how it refers to its nodes with the aim of better reflecting its positioning within the leadership semiconductor manufacturing space. Intel revealed its new node nomenclature, and... Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire