Swiss Researchers Propose ‘GreenIT’ Methodology for HPC

By Nicole Hemsoth

November 19, 2010

The latest Green500 list announced this week at SC10 is once again shining the spotlight on the energy efficiency of the world’s top supercomputers. But the path to more efficient high performance computing goes beyond this simple benchmark-based approach. Ralf Gruber and Vincent Keller, both from École Polytechnique Fédérale de Lausanne (EPFL), describe a holistic approach to more energy-efficient HPC operations in their book, HPC@GreenIT. HPCwire contributor Steve Conway interviewed the Swiss duo about their ideas, including a new benchmark.

HPCwire: Why did you write a book on “green” high performance computing methods?

Ralf Gruber: There was no theory on how to couple application needs to hardware offers. In the book, we try to set up a theory by defining parameters to characterize resources and applications. This parameterization is then used to develop models to predict if a computer architecture is well suited for an application or not. These models can also be used to detect poor application implementations, to redesign computer architectures, to detect resources that should be switched off, to run on the same resource two or more complementary applications that optimally use the different parts, or to simply recognize the best-suited machine for a given application.

Vincent Keller: Finally, we used these models to interact with the DVS-able processors in order to tune the frequency of the processor. Measurements on a Nehalem already show overall energy reductions of up to 30 percent for main memory access-dominated applications.

HPCwire: You make recommendations in several areas. What are your application-oriented recommendations?

Gruber: Together with an efficient monitoring, the parameterization of the applications leads to models that are used to understand how well an application runs on different computers. The models — for instance the one on the complexity — also help to detect an unexpected behavior that can then be corrected.

Keller: We also make a recommendation to the vendors and the main HPC actors to create a new application-oriented REAL500 list, based on the observation that the current TOP500 list is largely used for marketing purposes and does not reflect the real applications anymore. At a certain point, it is counter-productive for making better usage of large-scale architectures.

HPCwire: How about your recommendations for system software?

Keller: System software should be able to easily measure the behavior of an application. Also, it should then be possible to act on the hardware parts during execution, such as switching off unused cores, reducing resource frequencies, or disabling unused main memory.

HPCwire: Sum up your recommendations for reducing energy use.

Keller: Energy reduction can be achieved through improving the efficiency of the application, through frequency reductions — four times more resources running at four times smaller frequency consume four times less energy — and by switching off unused parts, or by choosing a better-suited computer for the application to run on.

HPCwire: You mention that the TOP500 list and the derivative Green500 list are based on the narrow High Performance Linpack benchmark. What do you propose as an alternative to better measure energy efficiency?

Gruber: The parameterization and the models described in the book enable people to predict the behavior of an application on a different hardware platform, if one knows some timings of a few characteristic test applications. Thus, it would be perfect to perform measurements of processor, main memory, and network test cases for which the application-oriented parameters are exactly known.

Keller: Typical test cases are applications such as matrix*matrix-dominated, HPL-like codes, matrix*vector-dominated codes that are iteratively solved, Poisson problems described by sparse matrices, multicast communications dominated CP2K codes, and point-to-point-dominated, SpecuLOOS codes. Then, it would be possible to predict the behavior of your own application on the new hardware.

Keller: As a consequence, the new REAL500 classification would not be based on a single value, as is the case with today’s TOP500, but on several metrics, including pure CPU performance, the ratio of CPU performance to memory bandwidth, multicast communication performance, point-to-point communication performance, and network latency. At this point, knowing the applications ecosystem, it is possible to choose the right machine, or a set of the right machines to fit to the application component needs and achieve the greenest, most performant results.

HPCwire: Worldwide studies by IDC and Avetec showed that 69 percent of HPC datacenters do not actively measure energy efficiency today, and 80 percent have no strong mandate to improve energy efficiency. What will change this situation?

Keller: As a first comment, if 69 percent of the centers do not measure the energy, it is understandable that 80 percent of them have no mandate to improve energy efficiency. By providing them the right tools to show that it is possible to reduce the energy bill for hardware and cooling with no loss of computational performance, we are convinced that their financial departments will consider the question as important and act. The situation is already on a wind of change. It is not uncommon to see a datacenter that would like to extend its computing capacity but cannot because of a power supply limitation. The demand in computing power increases, but energy consumption should not.

HPCwire: John Gustafson of Intel Labs says that by 2018, we’ll have an exaflop computer and the memory bandwidth will consume half of the power. How important is it to create new strategies to minimize data movement?

Gruber: Main memory is already the big issue now. When we reduce the frequency of the processor during execution, for instance on a Nehalem, the main memory consumes most of the energy, and this happens not only in 2018. The major problem is the small parallelism in data access. We should highly increase access parallelism by increasing the number of memory banks as in the old vector machines, and by increasing the bit stream. Then, it will be possible to decrease the frequency and the energy consumption.

HPCwire: Is cloud computing more or less energy-efficient than in-house computing?

Keller: Cloud computing is a buzzword. It is little more than grid computing plus a business model, and the latest strategy of scientists to raise funding for academic research. Grid computing was a big dream and a big failure. Why? Because the question of “who pays?” was never taken into account.

Cloud computing is different in that sense. A provider gives a certain quality of service: “I will provide you 1 gigaflops with a memory bandwidth of 1 GB/second for $1/hour.” Thanks to virtualization, the cloud computing providers, such as Amazon, Salesforce or Google, can offer computing power to their customers at a lower price, with multiple customers on the same hardware. We’ve known since the mainframe era that shared resources are cheaper and more energy-efficient than distributed resources that are left idle part of the time. In that specific sense of re-implementing old concepts, cloud computing could be more energy-efficient than in-house computing.

Last but not least, the data transfer from the customer to the provider and back is not taken into account in the final bill. It is more or less like living in Geneva: Swiss people know that food is less expensive in France than in Switzerland, but they have to take into account the round trip. How much food would make it less expensive, with the transport costs included, to buy in France rather than in Switzerland?

HPCwire: What tips do you have for choosing a new supercomputer that will use energy wisely?

Keller: In a recent publication [1], we propose a GPU-based supercomputer that uses only a few cores, with the others switched off, and runs these at a four times lower frequency, This would reduce energy consumption by a factor of 16. To compensate for the performance reduction, four times more units must then be purchased. Together with the fact that the amount of main memory per processor can be reduced by a factor of four, the overall energy consumption can be estimated to drop by an overall factor of nine, and this by simply downgrading the resources.

Gruber: We also realized that the overall costs over four years could be cheaper for the downgraded hardware. In addition, decreasing the temperature by about 30° C increases the MTBF by a factor of 8. This is another important issue for exaflop machines. We were told that multiplying the number of functional units by four is unacceptable. We believe that running with one million of cores or with four million of cores is not an issue, but consuming nine times less energy, and increasing MTBF by eight are very important issues. The question we have to ask the hardware companies is clear: Will they agree to downgrade their computers to increase energy efficiency?

[1] Keller, V. and Gruber R. One Joule per GFlop for BLAS2 Now!, ICNAAM 2010 proceedings, pp. 1321-1324, ISBN: 978-0-7354-0834-0

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!

Pattern Computer – Startup Claims Breakthrough in ‘Pattern Discovery’ Technology

May 23, 2018

If it weren’t for the heavy-hitter technology team behind start-up Pattern Computer, which emerged from stealth today in a live-streamed event from San Francisco, one would be tempted to dismiss its claims of inventing Read more…

By John Russell

Silicon Startup Raises ‘Prodigy’ for Hyperscale/AI Workloads

May 23, 2018

There's another silicon startup coming onto the HPC/hyperscale scene with some intriguing and bold claims. Silicon Valley-based Tachyum Inc., which has been emerging from stealth over the last year and a half, is unveili Read more…

By Tiffany Trader

Scientists Conduct First Quantum Simulation of Atomic Nucleus

May 23, 2018

OAK RIDGE, Tenn., May 23, 2018—Scientists at the Department of Energy’s Oak Ridge National Laboratory are the first to successfully simulate an atomic nucleus using a quantum computer. The results, published in Ph Read more…

By Rachel Harken, ORNL

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…

IBM Accelerated Insights

Mastering the Big Data Challenge in Cognitive Healthcare

Patrick Chain, genomics researcher at Los Alamos National Laboratory, posed a question in a recent blog: What if a nurse could swipe a patient’s saliva and run a quick genetic test to determine if the patient’s sore throat was caused by a cold virus or a bacterial infection? Read more…

First Xeon-FPGA Integration Launched by Intel

May 22, 2018

Ever since Intel’s acquisition of FPGA specialist Altera in 2015 for $16.7 billion, it’s been widely acknowledged that some day, Intel would release a processor that integrates its mainstream Xeon CPU server chip wit Read more…

By Doug Black

Pattern Computer – Startup Claims Breakthrough in ‘Pattern Discovery’ Technology

May 23, 2018

If it weren’t for the heavy-hitter technology team behind start-up Pattern Computer, which emerged from stealth today in a live-streamed event from San Franci Read more…

By John Russell

Silicon Startup Raises ‘Prodigy’ for Hyperscale/AI Workloads

May 23, 2018

There's another silicon startup coming onto the HPC/hyperscale scene with some intriguing and bold claims. Silicon Valley-based Tachyum Inc., which has been eme Read more…

By Tiffany Trader

Japan Meteorological Agency Takes Delivery of Pair of Crays

May 21, 2018

Cray has supplied two identical Cray XC50 supercomputers to the Japan Meteorological Agency (JMA) in northwestern Tokyo. Boasting more than 18 petaflops combine Read more…

By Tiffany Trader

ASC18: Final Results Revealed & Wrapped Up

May 17, 2018

It was an exciting week at ASC18 in Nanyang, China. The student teams braved extreme heat, extremely difficult applications, and extreme competition in order to cross the cluster competition finish line. The gala awards ceremony took place on Wednesday. The auditorium was packed with student teams, various dignitaries, the media, and other interested parties. So what happened? Read more…

By Dan Olds

Spring Meetings Underscore Quantum Computing’s Rise

May 17, 2018

The month of April 2018 saw four very important and interesting meetings to discuss the state of quantum computing technologies, their potential impacts, and th Read more…

By Alex R. Larzelere

Quantum Network Hub Opens in Japan

May 17, 2018

Following on the launch of its Q Commercial quantum network last December with 12 industrial and academic partners, the official Japanese hub at Keio University is now open to facilitate the exploration of quantum applications important to science and business. The news comes a week after IBM announced that North Carolina State University was the first U.S. university to join its Q Network. Read more…

By Tiffany Trader

Democratizing HPC: OSC Releases Version 1.3 of OnDemand

May 16, 2018

Making HPC resources readily available and easier to use for scientists who may have less HPC expertise is an ongoing challenge. Open OnDemand is a project by t Read more…

By John Russell

PRACE 2017 Annual Report: Exascale Aspirations; Industry Collaboration; HPC Training

May 15, 2018

The Partnership for Advanced Computing in Europe (PRACE) today released its annual report showcasing 2017 activities and providing a glimpse into thinking about Read more…

By John Russell

MLPerf – Will New Machine Learning Benchmark Help Propel AI Forward?

May 2, 2018

Let the AI benchmarking wars begin. Today, a diverse group from academia and industry – Google, Baidu, Intel, AMD, Harvard, and Stanford among them – releas Read more…

By John Russell

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

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

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

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

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

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

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

Leading Solution Providers

SC17 Booth Video Tours Playlist

Altair @ SC17

Altair

AMD @ SC17

AMD

ASRock Rack @ SC17

ASRock Rack

CEJN @ SC17

CEJN

DDN Storage @ SC17

DDN Storage

Huawei @ SC17

Huawei

IBM @ SC17

IBM

IBM Power Systems @ SC17

IBM Power Systems

Intel @ SC17

Intel

Lenovo @ SC17

Lenovo

Mellanox Technologies @ SC17

Mellanox Technologies

Microsoft @ SC17

Microsoft

Penguin Computing @ SC17

Penguin Computing

Pure Storage @ SC17

Pure Storage

Supericro @ SC17

Supericro

Tyan @ SC17

Tyan

Univa @ SC17

Univa

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

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

CFO Steps down in Executive Shuffle at Supermicro

January 31, 2018

Supermicro yesterday announced senior management shuffling including prominent departures, the completion of an audit linked to its delayed Nasdaq filings, and Read more…

By John Russell

HPE Wins $57 Million DoD Supercomputing Contract

February 20, 2018

Hewlett Packard Enterprise (HPE) today revealed details of its massive $57 million HPC contract with the U.S. Department of Defense (DoD). The deal calls for HP Read more…

By Tiffany Trader

Deep Learning Portends ‘Sea Change’ for Oil and Gas Sector

February 1, 2018

The billowing compute and data demands that spurred the oil and gas industry to be the largest commercial users of high-performance computing are now propelling Read more…

By Tiffany Trader

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

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 Sympo Read more…

By Staff

Part One: Deep Dive into 2018 Trends in Life Sciences HPC

March 1, 2018

Life sciences is an interesting lens through which to see HPC. It is perhaps not an obvious choice, given life sciences’ relative newness as a heavy user of H Read more…

By John Russell

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