PRACEdays 2017 Wraps Up in Barcelona

By Kim McMahon

May 18, 2017

Guest contributor Kim McMahon shares highlights from the final day of the PRACEdays 2017 conference in Barcelona.

Barcelona has been absolutely lovely; the weather, the food, the people. I am, sadly, finishing my last day at PRACEdays 2017 with two sessions: an in-depth look at the oil and gas industry’s use of HPC and a panel discussion on bridging the gap between scientific code development and exascale technology.

Henri Calandra of Total SA spoke on the challenges of increased HPC complexity and value delivery for the oil and gas industry.

The main challenge Total and other oil and gas companies are finding is that discoveries of oil deposits are becoming more rare. To stay competitive, they need to first and foremost open new frontiers for oil discovery, but do this while reducing risk and costs.

In the 1980s, seismic data was reviewed in the 2 dimensional space. The 1990’s started development of 3D seismic depth imaging. Continuing into the 2000’s, 3D depth imaging was improved as wave equations were added to the traditional imaging. The 2010’s brought more physics, more accurate images, and more complex processes to visually view the seismic data.

Henri Calandra of Total SA – click to enlarge

The industry continues to see drastic improvements. A seismic simulation that in 2010 took four weeks to run, in 2016 takes one day. Images have significantly higher resolution and the amount of detail seen in the images enables Total to be more precise in identifying seismic fields and potential hazards in drilling.

If you look closely at the pictures (shown on the slide), you can make out improvements the image quality. Although it may seem slight to our eye, the geoscientist can see the small nuances in the images that help them be more precise, identify hazards, and achieve a better positive acquisition rate.

How did this change over the last 30+ years happen? Improved technology, integrating more advanced technologies, improved processes, more physics, more complex algorithms – basically more HPC.

Using HPC, Total has been able to reduce their risks, become more precise and selective on their explorations, identify potential oil fields faster, and optimize their seismic depth imaging.

What’s next: Opening new frontiers enabled by the better appraisal of potential new opportunities. HPC has enabled seismic depth imaging methods that can do more iterations, more physics, and more complex approximations. Models are larger, there are multiple resolutions, and 4D data. There is interactive processing happening during the drilling and these multi real-time simulations allow adjustments to the drilling, thus improving the success rate of finding oil.

Developing new algorithms is a long-term process and typically last across several generations of supercomputers. Of course, the oil and gas industry is looking forward to exascale. But the future is complex — in the compute in the form of manycore, with accelerators, and heterogeneous systems. Complexity in the storage with the abundance of data and movement between tiers of storage via multiple storage technologies. Complexity in the tools such as OpenCL, CUDA, OpenMP, OpenACC, and compilers. There is a need for standardized tools to hide the hardware complexity and help the users of the HPC systems.

None of this can be addressed without HPC specialists. Application development cannot be done without a strong collaboration between the physicist, scientist, and HPC team. This constant progress will continue to improve the predictions Total relies on for finding productive oil fields.

The second session of the day was a panel moderated by Inma Martinez: titled “Bridging the gap between scientific code development and exascale technology.” Much of the focus was on the software challenges for extreme scale computing faced by the community.

The panelists:

Henri Calandra: Total

Lee Margetts: NAFEMS

Erik Lindahl: PRACE Scientific Steering Committee

Frauke Gräter: Heidelberg Institute for Theoretical Studies

Thomas Skordas, European Commission

This highly anticipated session looked at the gap between hardware, software, and application advances and the role of industry, academia and the European Commission in the development of software for HPC systems.

Thomas Skordas pointed out that driving leadership in exascale is important and it’s about much more than hardware. It’s the next generation code, training, and understanding the opportunities exascale can accomplish.

Frauke Gräter sees data as a significant challenge; the accumulation of more and more data and the analysis of that data. In the end, scientists are looking for insights and research organizations will invest in science.

Parallelizing the algorithms is the key action according to Erik Lindahl. There is too much focus on the exascale machine but algorithms need to be good to make the best use of the hardware. Exascale, expected to happen around 2020, is not expected to be a staple in commercial datacenter until 2035. There is not a supercomputer in the world that does not run open source software, and exascale machines will follow this practice.

Lee Margetts talked of “monster machines” — the large compute clusters in every datacenter. As large vendors adopt artificial intelligence and machine learning, will we see the end of the road for the large “monster” machines? We have very sophisticated algorithms and are using very sophisticated computing. What if this technology that is used in something like oil and gas were used to predict volcanoes or earthquakes — the point being, can technologies be used for more than one science?

Henri Calandra noted that data analytics and storage will become a huge issue. If we move to exascale, we’ll have to deal with thousands of compute nodes and update code for all these machines.

The biggest challenge is the software challenge.

When asked about the new science we will see, the panel had answers that fit their sphere of knowledge. Thomas spoke of brain modeling and self-driving cars. Frauke added genome assembly and new scientific disciplines such as personalized medicine. She says, “To attract young people, we need to marry machine learning and deep learning into HPC.” Erik notes that we have a revolution of data because of accelerators. Data and accelerators enabling genome resource will drive research in this area. Lee spoke of integrating machine learning into manufacturing processes.

Kim McMahon, XAND McMahon

As Lee said, “Diversity in funding through the European commission is really important – we need to fund the mavericks as well as the crazy ones.”

My takeaway is that the accomplishment of an exascale machine is not the goal that will drive the technology forward. It’s the analysis of the data. The algorithms. Parallelizing code. There will be some who will buy the exascale machine, but it will be years after it’s available before it’s broadly accepted. As Lee said, “the focus is not the machine, the algorithms or the software, but delivering on the science. Most people in HPC are domain scientists who are trying to solve a problem.”

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!

AI-Focused ‘Genius’ Supercomputer Installed at KU Leuven

April 24, 2018

Hewlett Packard Enterprise has deployed a new approximately half-petaflops supercomputer, named Genius, at Flemish research university KU Leuven. The system is built to run artificial intelligence (AI) workloads and, as Read more…

By Tiffany Trader

New Exascale System for Earth Simulation Introduced

April 23, 2018

After four years of development, the Energy Exascale Earth System Model (E3SM) will be unveiled today and released to the broader scientific community this month. The E3SM project is supported by the Department of Energy Read more…

By Staff

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

HPE Extreme Performance Solutions

Hybrid HPC is Speeding Time to Insight and Revolutionizing Medicine

High performance computing (HPC) is a key driver of success in many verticals today, and health and life science industries are extensively leveraging these capabilities. Read more…

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

AI-Focused ‘Genius’ Supercomputer Installed at KU Leuven

April 24, 2018

Hewlett Packard Enterprise has deployed a new approximately half-petaflops supercomputer, named Genius, at Flemish research university KU Leuven. The system is Read more…

By Tiffany Trader

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

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

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

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

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

Leading Solution Providers

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

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