Networking, Data Experts Design a Better Portal for Scientific Discovery

By Jon Bashor

January 29, 2018

Jan. 29, 2018 — These days, it’s easy to overlook the fact that the World Wide Web was created nearly 30 years ago primarily to help researchers access and share scientific data. Over the years, the web has evolved into a tool that helps us eat, shop, travel, watch movies and even monitor our homes.

The Science DMZ includes multiple DTNs that provide for high-speed transfer between network and storage. Portal functions run on a portal server, located on the institution’s enterprise network. The DTNs need only speak the API of the data management service (Globus in this case).

Meanwhile, scientific instruments have become much more powerful, generating massive datasets, and international collaborations have proliferated. In this new era, the web has become an essential part of the scientific process, but the most common method of sharing research data remains firmly attached to the earliest days of the web. This can be a huge impediment to scientific discovery.

That’s why a team of networking experts from the Department of Energy’s Energy Sciences Network (ESnet), with the Globus team from the University of Chicago and Argonne National Laboratory, has designed a new approach that makes data sharing faster, more reliable and more secure. In an article published Jan. 15 in Peer J Comp Sci, the team describes their “The Modern Research Data Portal: a design pattern for networked, data-intensive science.”

“Both the size of datasets and the quantity of data objects has exploded, but the typical design of a data portal hasn’t really changed,” said co-author Eli Dart, a network engineer with the Department of Energy’s Energy Sciences Network, or ESnet. “Our new design preserves that ease of use, but easily scales up to handle the huge amounts of data associated with today’s science.”

Data portals, sometimes called science gateways, are web-based interfaces for access data storage and computing systems, allowing authorized users to access data and perform shared computations. As science becomes increasingly data-driven and collaborative, data portals are advancing research in materials, physics, astrophysics, cosmology, climate science and other fields.

The traditional portal is driven by a web server that is connected to a storage system and a database and processes users’ requests for data. While this simple design was straightforward to develop 25 years ago, it has increasingly become an obstacle to performance, usability and security.

“The problem with using old technology is that these portals don’t provide fast access to the data and they aren’t very flexible,” said lead author Ian Foster, who is the Arthur Holly Compton Professor at the University of Chicago and Director of the Data Science and Learning Division at Argonne National Laboratory. “Since each portal is developed as its own silo, the organization therefore must implement, and then manage and support, multiple complete software stacks to support each portal.”

The new portal design is built on two approaches developed to simplify and speed up transfers of large datasets.

  • The Science DMZ, which Dart developed, is a high-performance network design that connects large-scale data servers directly to high-speed networks and is increasingly used by research institutions to better manage data transfers.
  • Globus is a cloud-based service to which developers of data portals and other science services can outsource responsibility for complex tasks like authentication, authorization, data movement, and data sharing. Globus can be used, in particular, to drive data transfers into and out of Science DMZs.

Kyle Chard, Foster, David Shiffett, Steven Tuecke and Jason Williams are co-authors of the paper and helped develop Globus at Argonne National Laboratory and the University of Chicago. In their paper, the authors note that the concept became feasible in 2015 as Globus and the Science DMZ became mature technologies.

“Together, Globus and the Science DMZ give researchers a powerful toolbox for conducting their research,” Dart said.

One portal incorporating the new design is the Research Data Archive managed by the National Center for Atmospheric Research, which contains a large and diverse collection of meteorological and oceanographic observations, operational and reanalysis model outputs, and remote sensing datasets to support atmospheric and geosciences research.

For example, a scientist working at a university could download data from the National Center for Atmospheric Research (NCAR) in Colorado and then use it to run simulations at DOE and NSF supercomputing centers in California and Illinois, and finally move the data to her home institution for analysis. To illustrate how the design works, Dart selected a 460-gigabyte dataset at NCAR, initiated a Globus transfer to DOE’s National Energy Research Scientific Computing Center at Lawrence Berkeley National Laboratory, logged in to his storage account and started the transfer. Four minutes later, the 5,141 files had been seamlessly transferred.

How the design works

The Modern Research Data Portal takes the single-server model of the traditional portal design and divides it among three distinct components.

  • A portal web server handles the search for and access to the specified data, and similar tasks.
  • The data servers, often called Data Transfer Nodes, are connected to high-speed networks through a specialized enclave, in this case the Science DMZ. The Science DMZ provides a dedicated, secure link to the data servers, but avoids common performance bottlenecks caused by typical designs not optimized for high-speed transfers.
  • Globus manages the authentication, data access and data transfers. Globus makes it possible for users to manage data irrespective of the location or storage system on which data reside and supports data transfer, sharing, and publication directly from those storage systems.

“The design pattern thus defines distinct roles for the web server, which manages who is allowed to do what; data servers, where authorized operations are performed on data; and external services, which orchestrate data access,” the authors wrote.

Globus is already used by tens of thousands of researchers worldwide with endpoints at more than 360 sites, so many researchers are familiar with its capabilities and rely on it on a regular basis. In fact, about 80 percent of major research universities and national labs in the U.S. use Globus.

At the same time, more than 100 research universities across the country have deployed Science DMZs, thanks to funding support through the National Science Foundation’s Campus Cyberinfrastructure Program.

A critical component of the system is “a little agent called Globus Connect, which is much like the Google Drive or Dropbox agents one would install on their own PCs,” Chard said. Globus Connect allows the Globus service to move data to and from the computer using high performance protocols and also HTTPS for direct access. It also allows users to share data dynamically with their peers.

According to Chard, the design provides research organizations with easy-to-use technology tools similar to those used by business startups to streamline development.

“If we look to industry, startup businesses can now build upon a suite of services to simplify what they need to build and manage themselves,” Chard said. “In a research setting, Globus has developed a stack of such capabilities that are needed by any research portal. Recently, we (Globus) have developed interfaces to make it trivial for developers to build upon these capabilities as a platform.”

“As a result of this design, users have a platform that allows them to easily place and transfer data without having to scale up the human effort as the amount of data scales up,” Dart said.

ESnet is a DOE Office of Science User Facility. Argonne and Lawrence Berkeley national laboratories are supported by the Office of Science of the U.S. Department of Energy. The Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time.  For more information, please visit science.energy.gov.

About Computing Sciences at Berkeley Lab

The Lawrence Berkeley National Laboratory (Berkeley LabComputing Sciences organization provides the computing and networking resources and expertise critical to advancing the Department of Energy’s research missions: developing new energy sources, improving energy efficiency, developing new materials and increasing our understanding of ourselves, our world and our universe.

ESnet, the Energy Sciences Network, provides the high-bandwidth, reliable connections that link scientists at 40 DOE research sites to each other and to experimental facilities and supercomputing centers around the country. The National Energy Research Scientific Computing Center (NERSC) powers the discoveries of 6,000 scientists at national laboratories and universities, including those at Berkeley Lab’s Computational Research Division (CRD). CRD conducts research and development in mathematical modeling and simulation, algorithm design, data storage, management and analysis, computer system architecture and high-performance software implementation. NERSC and ESnet are DOE Office of Science User Facilities.

Lawrence Berkeley National Laboratory addresses the world’s most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab’s scientific expertise has been recognized with 13 Nobel prizes. The University of California manages Berkeley Lab for the DOE’s Office of Science.

DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit science.energy.gov.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion XL — were added to the benchmark suite as MLPerf continues Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing power it brings to artificial intelligence.  Nvidia's DGX Read more…

Call for Participation in Workshop on Potential NSF CISE Quantum Initiative

March 26, 2024

Editor’s Note: Next month there will be a workshop to discuss what a quantum initiative led by NSF’s Computer, Information Science and Engineering (CISE) directorate could entail. The details are posted below in a Ca Read more…

Waseda U. Researchers Reports New Quantum Algorithm for Speeding Optimization

March 25, 2024

Optimization problems cover a wide range of applications and are often cited as good candidates for quantum computing. However, the execution time for constrained combinatorial optimization applications on quantum device Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at the network layer threatens to make bigger and brawnier pro Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HBM3E memory as well as the the ability to train 1 trillion pa Read more…

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HB Read more…

Nvidia Looks to Accelerate GenAI Adoption with NIM

March 19, 2024

Today at the GPU Technology Conference, Nvidia launched a new offering aimed at helping customers quickly deploy their generative AI applications in a secure, s Read more…

The Generative AI Future Is Now, Nvidia’s Huang Says

March 19, 2024

We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Intel Won’t Have a Xeon Max Chip with New Emerald Rapids CPU

December 14, 2023

As expected, Intel officially announced its 5th generation Xeon server chips codenamed Emerald Rapids at an event in New York City, where the focus was really o Read more…

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

December 4, 2023

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qu Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire