The Case for an Edge-Driven Future for Supercomputing

By Oliver Peckham

September 24, 2021

“Exascale only becomes valuable when it’s creating and using data that we care about,” said Pete Beckman, co-director of the Northwestern-Argonne Institute of Science and Engineering (NAISE), at the most recent HPC User Forum. Beckman, head of an Argonne National Laboratory edge computing project called Waggle, was insistent on one thing: edge computing is a crucial part of delivering that value for exascale.

Beckman had opened with a quote from computer architect Ken Batcher: “A supercomputer is a device for turning compute-bound problems into I/O-bound problems.” “In many ways, that is still true today,” Beckman said. “What we expect from supercomputers is that they’re so blindingly fast that really it’s bottlenecked on either reading or writing from input or output.”

“If we take that concept, though, and flip it over,” he added, “then we end up with this idea that edge computing, therefore, is a device for turning an I/O-bound problem into a compute-bound problem.”

Beckman outlined what he viewed as the new paradigm of high-performance computing: one defined by extreme data production – more than could ever be efficiently moved to supercomputers – by massive detectors and instruments like the Large Hadron Collider and radio telescopes. This paradigm, he said, resulted in a series of research problems where it would be more efficient to examine data at the edge and filter only the important or interesting data to supercomputers for heavy-duty analysis.

There were a number of reasons, Beckman explained, why edge processing might be preferable: more data than bandwidth, of course – but also a need for low latency and quick actuation, as in self-driving cars; privacy or security requirements that prevent the transfer of sensitive or personalized data; a desire for additional resilience through distributed processing; or energy efficiency.

Beckman, for his part, advances this new paradigm – which he said “has been made possible largely because of AI” – through Waggle, which began as a wireless sensor system aimed at enabling smarter urban and environmental research. With Waggle, Beckman said, “the idea was to understand the dynamics of a city” through pedestrian monitoring, air quality analysis and more. The initial generation of sensors had been installed all around Chicago, generating data that was then shared with scientists.

The newest version of the Waggle sensor, Beckman said, has just been developed and is much beefier: an AI-enabled edge computing platform that crunches incoming data using an Nvidia Xavier NX GPU. The platform is equipped with sky- and ground-facing cameras, atmospheric sensors, rain sensors and mountain points for even more sensors. Beckman added that Lawrence Berkeley National Laboratory is working on its own Waggle node configuration for one of its projects.

The newest version of the Waggle sensor platform. Image courtesy of Pete Beckman.

These Waggle sensors, Beckman explained, are building toward an even bigger vision – one embodied by the NSF-funded Sage project out of Northwestern University (also led by Beckman). Through Sage, he said, the goal was “to take these kinds of edge sensors and use them in networks across the United States to build what we call software-defined sensors,” flexible edge computers that are subsequently specialized for a purpose.

“The architecture for Sage … is pretty straightforward,” Beckman said. “At the edge, we’re processing data. … The data that’s extracted from an edge AI goes into the repository, the repository then can share that data with HPC apps, which can then process that data.” The Sage-enabled Waggle networks, Beckman said, were simple and secure, with no open ports. “You can’t connect to a Waggle node,” he said. “Nodes only phone home.”

The architecture for the Sage project. Image courtesy of Pete Beckman.

Through Sage and Waggle, Beckman outlined a number of ongoing and prospective use cases. Huts equipped with Sage tech, he said, had already been installed alongside the ecological monitoring equipment for the 81-site, NSF-run NEON project, which has been running since 2000. Various other partnerships – including one between Sage and ALERTWildfire – were using edge processing tech like Waggle to advance low latency wildfire detection and data reporting. Other projects ranged from identifying pedestrian flow to classifying snowflakes to gauging policies’ effects on social distancing and mask-wearing during the pandemic.

“Really most of HPC has been focused on an input deck – some data that you get in, and then you compute and you make a visualization,” Beckman said. “It’s clear that the future of large HPC systems is in-the-loop processing, where data will come in, be processed, and it’s a live feed from the edge which is running the first layer of that HPC code.”

“Every group that we talk to about edge computing has a different idea. That’s what’s been so much fun about the concept of a software-defined sensor,” he added. “Being able to run that software stack on edge devices and report back by doing AI at the edge is a very new area, and we’re interested in seeing new use cases and what problems you might have – what ways you might connect your supercomputer with the edge.”

Header image: Waggle nodes. Image courtesy of Argonne National Laboratory.

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