The Network as a Scientific Instrument

By Nicole Hemsoth

June 10, 2013

In June 2012, Greg Bell was named the head of the U.S. Department of Energy’s Energy Sciences Network, better known as ESnet.

Funded by the DOE Office of Science, and managed and operated by the ESnet team at Lawrence Berkeley National Laboratory, ESnet provides reliable, high-performance networking capabilities to thousands of researchers tackling many of the world’s most pressing scientific and engineering problems: finding sources of clean energy, understanding climate change, developing advanced materials, and discovering the fundamental nature of our universe. ESnet interconnects scientists at more than 40 DOE sites with experimental and computing facilities in the U.S. and abroad, and with collaborators around the world. 

Invited to give the closing keynote address at the 2012 NORDUnet conference in Oslo, Norway, Bell delivered a presentation entitled “Network as Instrument: The View from Berkeley,” in which he argued that it’s time to start thinking about research networks as instruments for discovery, not just infrastructures for service delivery. The talk struck a chord with the audience, and Bell has since been invited to give versions of the presentation at conferences in the United States and Canada. Most recently, he contributed the April 25 keynote address at the THINK Conference 2013 organized by ORION, the high-speed network linking 1.8 million researchers in Ontario, Canada.

A video of Bell giving a version of this presentation at a meeting on the genomics of energy and the environment, sponsored by the DOE Joint Genome Institute, can be found at the end of the article.

In this Q&A for HPCwire, Berkeley Lab Computing Sciences Communications Manager Jon Bashor talks with Bell about his vision, ESnet news and more.

Question: To start, can you give us a short description of ESnet?

Bell: We’re the Department of Energy’s high-performance networking facility, engineered and optimized for large-scale science. ESnet was created in 1986, making it one of the longest-operating research networks in the world.

ESnet interconnects the entire national lab system, including its supercomputer centers and dozens of large-scale user facilities. Thanks to ESnet, tens of thousands of scientists around the world can transfer data, access remote resources, and collaborate productively. 

ESnet is more than a network, though — it’s a collection of skilled and dedicated people, and a great place to work. Even though we’re located near Silicon Valley, we find it relatively easy to attract talent, because we do cutting-edge engineering in the service of scientific discovery. 

Q: In a sense, ESnet has always been at the forefront of handling Big Data, and now the rest of the community is catching up. How big is Big Data on ESnet?

Bell: Scientific data sets can be truly enormous, up to petabytes in size, and they’re growing rapidly. Sometimes we use the term “Extreme Data” to distinguish data at this scale from the Big Data you’ve read about in other contexts.

The advent of extreme-data science naturally has an impact on the amount of traffic ESnet carries. In fact, we’re growing about twice as fast as the commercial internet — our traffic doubles every 18 months. I don’t foresee this trend slowing down any time soon, because the underlying exponential drivers just keep cranking along.

Everyone reading this understands that high-performance computing changed the way large-scale science is conducted. It’s clear that data intensity will have an important impact as well. Modeling and simulation will continue to be critically important, but these tools will be supplemented by new techniques that can extract insight from complex data sets, exchanged and accessed over ultra-fast research networks.

Q: Although ESnet was created in 1986, its profile seems to have risen considerably in the past five years or so. What’s behind this?

Bell: More and more researchers are discovering that networks are critical to their science. Faster networks mean faster discovery. In addition, ESnet was lucky enough to receive significant stimulus funds a few years ago. That investment allowed us to build the world’s first 100 Gbps network at continental scale, in partnership with Internet2. We finished that project just in time: the previous-generation network was showing its age, and we were beginning to outgrow it. Our new architecture gives us lots of headroom, and the ability to develop new architectures for maximizing scientific productivity. 

We’ve also significantly ramped up our activity in the area of science engagement, partnership, and outreach. We understand that building the world’s fastest science network is not sufficient. We need to make it useful to scientists, and easy to use. That’s harder than it sounds, and we’re still developing models for helping scientists take full advantage of the “fast lanes” we’ve engineered for them. 

One final contributor is the success we’re having with applied research and innovation. This critical activity has been enhanced by our dedicated, national-scale 100 Gbps research testbed, which has supported dozens of researchers in the public and private sectors. We’re really trying to push the envelope on a range of topics — including software-defined networking, alternatives to TCP, and security models for 100 Gbps and faster networks. 

While we appreciate the recognition, it’s not really important unless it helps us advance our overall mission, which is to accelerate discovery for DOE’s Office of Science. And I do think it’s having that effect. Vendors are coming to us to ask about the unique challenges of supporting science, and our users are beginning to have much higher expectations of ESnet. These are both good developments. 

Q: You’ve also been busy. Your talk describing the network as an instrument of discovery has led to multiple invited presentations in North America and Europe — and most recently you gave a version of it as the April 25 keynote address at the THINK conference organized by ORION, the high-speed network in Ontario, Canada. What’s the gist of your presentation?

Bell: My overall goal is to inspire the audience to start thinking about networks differently. Modern research networks such as ESnet and Internet2 (and similar networks around the world) can do a lot more than most people imagine. I try to explain how certain collaborations have profited by incorporating advanced networks into their discovery processes. High-energy physics pioneered this model, and other fields are following. I make the argument that research networks such as ESnet have evolved into extensions of large-scale discovery instruments. For example, the discovery of the Higgs Boson would not have been possible without a worldwide grid computing infrastructure, interconnected by high-speed research networks. Harvey Newman at Caltech pioneered this idea years ago, and the world has finally caught up. 

In these presentations, I also give concrete advice about how people can improve networking in their own back yard. ESnet maintains a website devoted to this sort of simple, practical advice: fasterdata.es.net. If you want to start learning about how to use advanced networks more effectively, this is the place to start. It’s a very popular website, with more hits than www.es.net

Q: Why do you think the message has resonated so well in the networking community?

Bell: It’s not surprising that networkers like to hear that their work is important! But there are a couple of deeper reasons as well. In recent years, networking had become a little dull. Thanks to the challenges of extreme data (and also to the advent of software defined networking), it’s a really exciting place to be again. This new energy is very obvious at networking conferences, and in the academic research community. There are a lot of eyes on networking at the moment. 

Q: Last question: What is ESnet focusing on for the coming year? For the next five years?

Bell: Over the next five years, our challenge will be to accommodate the remarkable growth curve in DOE science traffic while simultaneously making the network useful to many more researchers. It’s hard to believe, but even with our new 100 Gbps network and access to underlying optical capacity to carry multiple terabits per second, we will begin to feel a little cramped by 2018-20. At that point, we think we’ll need to light up a new nationwide optical fiber footprint. Whatever else we do, we’re always in a mode of acceleration and growth!

In the coming year, we’ll focus on recruiting about eight new staff, most of them technical. When you consider that we now have about 40 employees, adding eight is significant. We take recruitment very seriously at ESnet. We look for people who are at the top of their game technically, but that’s not enough — they need to be flexible, great communicators, and exemplary colleagues. 

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

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

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

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

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

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

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