Exascale: Power Is Not the Problem!

By Andrew Jones

August 29, 2011

To build exascale systems, power is probably the biggest technical hurdle on the hardware side. In terms of getting to exascale computing, demonstrating the value of supercomputing to funders and the public is a more urgent challenge. But the top roadblock for realizing the potential benefits from exascale is software.

That title is probably controversial to most readers. It is likely that if you asked members of the supercomputing community what is the single biggest challenge for exascale computing, the most common answer would be “power.” It is widely reported, widely talked about, and in many places, generally accepted that finding a few orders of magnitude improvement in power consumption is the biggest roadblock on the way to viable exascale computing. Otherwise, the first exascale computers will require 60MW, 120MW or 200MW — pick your favorite horror figure. I’m not so convinced.

I’m not saying the power estimates for exascale computing are not a problem — they are — but they are not the problem. Because, in the end, it is just a money problem. For most in the community, the objection is not so much to the fact of 60-plus MW supercomputers. Instead, the objection is the resulting operating costs of 60-plus MW supercomputers. We simply don’t want to pay $60 million each year for electricity (or more precisely we don’t want to have to justify to someone else — e.g., funding agencies — that we need to pay that much). But why are we so concerned about large power costs?

Are we really saying, with our concerns over power, that we simply don’t have a good enough case for supercomputing — the science case, business case, track record of innovation delivery, and so on? Surely if supercomputing is that essential, as we keep arguing, then the cost of the power is worth it.

There are several large scientific facilities that have comparable power requirements, often with much narrower missions — remember that supercomputing can advance almost all scientific disciplines — for example, LHC, ITER, NIF, and SNS. And indeed, most of the science communities behind those facilities are also large users of supercomputing.

I occasionally say, glibly and deliberately provocatively, if the scientific community can justify billions of dollars, 100MW of power, and thousands of staff in order to fire tiny particles that most people have never heard of around a big ring of magnets for a fairly narrow science purpose that most people will never understand, then how come we can’t make a case for a facility needing only half of those resources that can do wonders for a whole range of science problems and industrial applications?

[There is a partial answer to that, which I have addressed on my HPC Notes blog to avoid distraction here.]

But secondly, and more importantly, the power problem can be solved with enough money if we can make the case. Accepting huge increases in budgets would also go a long way toward solving several of the other challenges of exascale computing. For example, resiliency could be substantially helped if we could afford comprehensive redundancy and other advanced RAS features; data movement challenges could be helped if we could afford huge increases in memory bandwidth at all levels of the system; and so on.

Those technical challenges would not be totally solved but they would be substantially reduced by money. I don’t mean to trivialize those technical challenges, but certainly they could be made much less scary if we weren’t worried about the cost of solutions.

So, the biggest challenge for exascale computing might not be power (or your other favorite architectural roadblock) but rather our ability to justify enough budget to pay for the power, or more expensive hardware, etc. However, beyond even that, there is a class of challenges for which money alone is not enough.

Assume a huge budget meant an exascale computer with good enough resiliency, plenty of memory bandwidth and every other needed architectural attribute was delivered tomorrow, and never mind the power bills. Could we use it? No. Because of a series of challenges that need not only money, but also lots of time to solve, and in most cases need research because we just don’t know the solutions.

I am thinking of the software related challenges.

Even if we have highly favorable architectures (expensive systems with lots of bandwidth, good resiliency, etc.) I think the community and most, if not all, of the applications are still years away from having algorithms and software implementations that can exploit that scale of computing efficiently.

There is a reasonable effort underway to identify the software problems that we might face in using exascale computing (e.g., IESP and EESI). However, in most cases we can only identify the problems; we still don’t have much idea about the solutions. Even where we have a good idea of the way forward, sensible estimates of the effort required to implement software capable of using exascale computing — OS, tools, applications, post-processing, etc. — is measured in years with large teams.

It certainly requires money, but it needs other scarce resources too, specifically time and skills. That involves a large pool of skilled parallel software engineers, scientists with computational expertise, numerical algorithms research and so on. Scarce resources like these are possibly even harder to create than money!

Power is a problem for exascale computing, and with current budget expectations is probably the biggest technical challenge for the hardware. In terms of getting to exascale computing, demonstrating the value of increased investment in supercomputing to funders and the public/media is probably a more urgent challenge. But the top roadblock for achieving the hugely beneficial potential output from exascale computing is software. There are many challenges to do with the software ecosystem that will take years, lots of skilled workers, and sustained/predictable investment to solve.

That “sustained/predictable” is important. Ad-hoc research grants are not an efficient way to plan and conduct a many-year, many-person, community-wide software research and development agenda. Remember that agenda will consume a non-trivial portion of the careers of many of the individuals involved. And when the researchers start out on this necessary software journey, they need confidence that funding will be there all the way to production deployment and ongoing maintenance many years into the future.

About the Author

Andrew is Vice-President of HPC Services and Consulting at the Numerical Algorithms Group (NAG). He was originally a researcher using HPC and developing related software, later becoming involved in leadership of HPC services. He is also interested in exascale, manycore, skills development, broadening usage, and other future concerns of the HPC community.

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!

Q&A with Altair CEO James Scapa, an HPCwire Person to Watch in 2021

May 14, 2021

Chairman, CEO and co-founder of Altair James R. Scapa closed several acquisitions for the company in 2020, including the purchase and integration of Univa and Ellexus. Scapa founded Altair more than 35 years ago with two Read more…

HLRS HPC Helps to Model Muscle Movements

May 13, 2021

The growing scale of HPC is allowing simulation of more and more complex systems at greater detail than ever before, particularly in the biological research spheres. Now, researchers at the University of Stuttgart are le Read more…

Behind the Met Office’s Procurement of a Billion-Dollar Microsoft System

May 13, 2021

The UK’s national weather service, the Met Office, caused shockwaves of curiosity a few weeks ago when it formally announced that its forthcoming billion-dollar supercomputer – expected to be the most powerful weather and climate-focused supercomputer in the world when it launches in 2022... Read more…

AMD, GlobalFoundries Commit to $1.6 Billion Wafer Supply Deal

May 13, 2021

AMD plans to purchase $1.6 billion worth of wafers from GlobalFoundries in the 2022 to 2024 timeframe, the chipmaker revealed today (May 13) in an SEC filing. In the face of global semiconductor shortages and record-high demand, AMD is renegotiating its Wafer Supply Agreement and bumping up capacity. Read more…

Hyperion Offers Snapshot of Quantum Computing Market

May 13, 2021

The nascent quantum computer (QC) market will grow 27 percent annually (CAGR) reaching $830 million in 2024 according to an update provided today by analyst firm Hyperion Research at the HPC User Forum being held this we Read more…

AWS Solution Channel

Numerical weather prediction on AWS Graviton2

The Weather Research and Forecasting (WRF) model is a numerical weather prediction (NWP) system designed to serve both atmospheric research and operational forecasting needs. Read more…

Hyperion: HPC Server Market Ekes 1 Percent Gain in 2020, Storage Poised for ‘Tipping Point’

May 12, 2021

The HPC User Forum meeting taking place virtually this week (May 11-13) kicked off with Hyperion Research’s market update, covering the 2020 period. Although the HPC server market had been facing a 6.7 percent COVID-re Read more…

Behind the Met Office’s Procurement of a Billion-Dollar Microsoft System

May 13, 2021

The UK’s national weather service, the Met Office, caused shockwaves of curiosity a few weeks ago when it formally announced that its forthcoming billion-dollar supercomputer – expected to be the most powerful weather and climate-focused supercomputer in the world when it launches in 2022... Read more…

AMD, GlobalFoundries Commit to $1.6 Billion Wafer Supply Deal

May 13, 2021

AMD plans to purchase $1.6 billion worth of wafers from GlobalFoundries in the 2022 to 2024 timeframe, the chipmaker revealed today (May 13) in an SEC filing. In the face of global semiconductor shortages and record-high demand, AMD is renegotiating its Wafer Supply Agreement and bumping up capacity. Read more…

Hyperion Offers Snapshot of Quantum Computing Market

May 13, 2021

The nascent quantum computer (QC) market will grow 27 percent annually (CAGR) reaching $830 million in 2024 according to an update provided today by analyst fir Read more…

Hyperion: HPC Server Market Ekes 1 Percent Gain in 2020, Storage Poised for ‘Tipping Point’

May 12, 2021

The HPC User Forum meeting taking place virtually this week (May 11-13) kicked off with Hyperion Research’s market update, covering the 2020 period. Although Read more…

IBM Debuts Qiskit Runtime for Quantum Computing; Reports Dramatic Speed-up

May 11, 2021

In conjunction with its virtual Think event, IBM today introduced an enhanced Qiskit Runtime Software for quantum computing, which it says demonstrated 120x spe Read more…

AMD Chipmaker TSMC to Use AMD Chips for Chipmaking

May 8, 2021

TSMC has tapped AMD to support its major manufacturing and R&D workloads. AMD will provide its Epyc Rome 7702P CPUs – with 64 cores operating at a base cl Read more…

Fast Pass Through (Some of) the Quantum Landscape with ORNL’s Raphael Pooser

May 7, 2021

In a rather remarkable way, and despite the frequent hype, the behind-the-scenes work of developing quantum computing has dramatically accelerated in the past f Read more…

IBM Research Debuts 2nm Test Chip with 50 Billion Transistors

May 6, 2021

IBM Research today announced the successful prototyping of the world's first 2 nanometer chip, fabricated with silicon nanosheet technology on a standard 300mm Read more…

AMD Chipmaker TSMC to Use AMD Chips for Chipmaking

May 8, 2021

TSMC has tapped AMD to support its major manufacturing and R&D workloads. AMD will provide its Epyc Rome 7702P CPUs – with 64 cores operating at a base cl 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…

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…

CERN Is Betting Big on Exascale

April 1, 2021

The European Organization for Nuclear Research (CERN) involves 23 countries, 15,000 researchers, billions of dollars a year, and the biggest machine in the worl Read more…

HPE Launches Storage Line Loaded with IBM’s Spectrum Scale File System

April 6, 2021

HPE today launched a new family of storage solutions bundled with IBM’s Spectrum Scale Erasure Code Edition parallel file system (description below) and featu 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…

Saudi Aramco Unveils Dammam 7, Its New Top Ten Supercomputer

January 21, 2021

By revenue, oil and gas giant Saudi Aramco is one of the largest companies in the world, and it has historically employed commensurate amounts of supercomputing Read more…

Quantum Computer Start-up IonQ Plans IPO via SPAC

March 8, 2021

IonQ, a Maryland-based quantum computing start-up working with ion trap technology, plans to go public via a Special Purpose Acquisition Company (SPAC) merger a Read more…

Leading Solution Providers

Contributors

AMD Launches Epyc ‘Milan’ with 19 SKUs for HPC, Enterprise and Hyperscale

March 15, 2021

At a virtual launch event held today (Monday), AMD revealed its third-generation Epyc “Milan” CPU lineup: a set of 19 SKUs -- including the flagship 64-core, 280-watt 7763 part --  aimed at HPC, enterprise and cloud workloads. Notably, the third-gen Epyc Milan chips achieve 19 percent... Read more…

Can Deep Learning Replace Numerical Weather Prediction?

March 3, 2021

Numerical weather prediction (NWP) is a mainstay of supercomputing. Some of the first applications of the first supercomputers dealt with climate modeling, and Read more…

Livermore’s El Capitan Supercomputer to Debut HPE ‘Rabbit’ Near Node Local Storage

February 18, 2021

A near node local storage innovation called Rabbit factored heavily into Lawrence Livermore National Laboratory’s decision to select Cray’s proposal for its CORAL-2 machine, the lab’s first exascale-class supercomputer, El Capitan. Details of this new storage technology were revealed... Read more…

African Supercomputing Center Inaugurates ‘Toubkal,’ Most Powerful Supercomputer on the Continent

February 25, 2021

Historically, Africa hasn’t exactly been synonymous with supercomputing. There are only a handful of supercomputers on the continent, with few ranking on the Read more…

GTC21: Nvidia Launches cuQuantum; Dips a Toe in Quantum Computing

April 13, 2021

Yesterday Nvidia officially dipped a toe into quantum computing with the launch of cuQuantum SDK, a development platform for simulating quantum circuits on GPU-accelerated systems. As Nvidia CEO Jensen Huang emphasized in his keynote, Nvidia doesn’t plan to build... Read more…

New Deep Learning Algorithm Solves Rubik’s Cube

July 25, 2018

Solving (and attempting to solve) Rubik’s Cube has delighted millions of puzzle lovers since 1974 when the cube was invented by Hungarian sculptor and archite Read more…

The History of Supercomputing vs. COVID-19

March 9, 2021

The COVID-19 pandemic poses a greater challenge to the high-performance computing community than any before. HPCwire's coverage of the supercomputing response t Read more…

Microsoft to Provide World’s Most Powerful Weather & Climate Supercomputer for UK’s Met Office

April 22, 2021

More than 14 months ago, the UK government announced plans to invest £1.2 billion ($1.56 billion) into weather and climate supercomputing, including procuremen Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire