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!

TACC Helps ROSIE Bioscience Gateway Expand its Impact

April 26, 2017

Biomolecule structure prediction has long been challenging not least because the relevant software and workflows often require high-end HPC systems that many bioscience researchers lack easy access to. Read more…

By John Russell

Messina Update: The US Path to Exascale in 16 Slides

April 26, 2017

Paul Messina, director of the U.S. Exascale Computing Project, provided a wide-ranging review of ECP’s evolving plans last week at the HPC User Forum. Read more…

By John Russell

IBM, Nvidia, Stone Ridge Claim Gas & Oil Simulation Record

April 25, 2017

IBM, Nvidia, and Stone Ridge Technology today reported setting the performance record for a “billion cell” oil and gas reservoir simulation. Read more…

By John Russell

ASC17 Makes Splash at Wuxi Supercomputing Center

April 24, 2017

A record-breaking twenty student teams plus scores of company representatives, media professionals, staff and student volunteers transformed a formerly empty hall inside the Wuxi Supercomputing Center into a bustling hub of HPC activity, kicking off day one of 2017 Asia Student Supercomputer Challenge (ASC17). Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

Remote Visualization Optimizing Life Sciences Operations and Care Delivery

As patients continually demand a better quality of care and increasingly complex workloads challenge healthcare organizations to innovate, investing in the right technologies is key to ensuring growth and success. Read more…

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of a new generation of chips designed specifically for deep learning workloads. Read more…

By Alex Woodie

Musk’s Latest Startup Eyes Brain-Computer Links

April 21, 2017

Elon Musk, the auto and space entrepreneur and severe critic of artificial intelligence, is forming a new venture that reportedly will seek to develop an interface between the human brain and computers. Read more…

By George Leopold

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Engine (GCE) job. Sutherland ran the massive mathematics workload on 220,000 GCE cores using preemptible virtual machine instances. Read more…

By Tiffany Trader

NERSC Cori Shows the World How Many-Cores for the Masses Works

April 21, 2017

As its mission, the high performance computing center for the U.S. Department of Energy Office of Science, NERSC (the National Energy Research Supercomputer Center), supports a broad spectrum of forefront scientific research across diverse areas that includes climate, material science, chemistry, fusion energy, high-energy physics and many others. Read more…

By Rob Farber

Messina Update: The US Path to Exascale in 16 Slides

April 26, 2017

Paul Messina, director of the U.S. Exascale Computing Project, provided a wide-ranging review of ECP’s evolving plans last week at the HPC User Forum. Read more…

By John Russell

ASC17 Makes Splash at Wuxi Supercomputing Center

April 24, 2017

A record-breaking twenty student teams plus scores of company representatives, media professionals, staff and student volunteers transformed a formerly empty hall inside the Wuxi Supercomputing Center into a bustling hub of HPC activity, kicking off day one of 2017 Asia Student Supercomputer Challenge (ASC17). Read more…

By Tiffany Trader

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of a new generation of chips designed specifically for deep learning workloads. Read more…

By Alex Woodie

NERSC Cori Shows the World How Many-Cores for the Masses Works

April 21, 2017

As its mission, the high performance computing center for the U.S. Department of Energy Office of Science, NERSC (the National Energy Research Supercomputer Center), supports a broad spectrum of forefront scientific research across diverse areas that includes climate, material science, chemistry, fusion energy, high-energy physics and many others. Read more…

By Rob Farber

Hyperion (IDC) Paints a Bullish Picture of HPC Future

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). Read more…

By John Russell

Knights Landing Processor with Omni-Path Makes Cloud Debut

April 18, 2017

HPC cloud specialist Rescale is partnering with Intel and HPC resource provider R Systems to offer first-ever cloud access to Xeon Phi "Knights Landing" processors. The infrastructure is based on the 68-core Intel Knights Landing processor with integrated Omni-Path fabric (the 7250F Xeon Phi). Read more…

By Tiffany Trader

CERN openlab Explores New CPU/FPGA Processing Solutions

April 14, 2017

Through a CERN openlab project known as the ‘High-Throughput Computing Collaboration,’ researchers are investigating the use of various Intel technologies in data filtering and data acquisition systems. Read more…

By Linda Barney

DOE Supercomputer Achieves Record 45-Qubit Quantum Simulation

April 13, 2017

In order to simulate larger and larger quantum systems and usher in an age of “quantum supremacy,” researchers are stretching the limits of today’s most advanced supercomputers. Read more…

By Tiffany Trader

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference phase of neural networks (NN). Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. 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

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Leading Solution Providers

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

Facebook Open Sources Caffe2; Nvidia, Intel Rush to Optimize

April 18, 2017

From its F8 developer conference in San Jose, Calif., today, Facebook announced Caffe2, a new open-source, cross-platform framework for deep learning. Caffe2 is the successor to Caffe, the deep learning framework developed by Berkeley AI Research and community contributors. Read more…

By Tiffany Trader

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

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