Stampede1 Reborn as BigTex, a Supercomputer for the Federal Reserve

By Aaron Dubrow

June 18, 2020

Alex Richter, a research economist from the Federal Reserve Bank of Dallas, seeks to unravel the non-linear impacts of the business cycle and monetary policy.

His research requires advanced computing to solve complicated mathematical and statistical problems. For several years, he used the modest-sized high performance computing cluster operated by the Federal Reserve Bank of Kansas City, the Ganymede cluster at the University of Texas at Dallas, as well as Stampede1 and Stampede2 at the Texas Advanced Computing Center (TACC). But he found himself needing more compute time. Moreover, he suspected there were many other research economists in the Federal Reserve System who could benefit additional computing resources.

Knowing that TACC — 200 miles south in Austin — operated several of the world’s largest supercomputers for open science research, in July 2017, Richter travelled to the center to see if he and his colleagues could gain greater access to the supercomputers there.

“I originally went down there thinking, since we’re in Dallas, and TACC is in Austin, maybe there’s a way that we could have some sort of partnership where we could get dedicated access to use Stampede,” Richter said.

He met with Dan Stanzione, TACC’s executive director, and, during a tour of the data center, noticed that several racks that had previously been part of Stampede1 were unplugged.

Cold-aisle containment for BigTex. (Credit: TACC)

The system — an Intel/Dell supercomputer with a peak speed of nearly 10 petaflops that debuted in 2012 as the seventh most powerful machine in the world — had recently been decommissioned, he learned. Twenty racks were available for donation. Would Richter be interested in taking them?

Richter was intrigued, but the idea was not without its challenges. For one, the Federal Reserve of Dallas did not have the IT support needed to set up and run the machines, nor a data center to host it.

However, Richter was undeterred. The Federal Reserve accepted the donated equipment, and he spearheaded an effort to get support for a proof-of-concept experiment. TACC would provide the hardware; Chris Simmons, UT Dallas head of research computing, would provide user support and assistance in standing up the machine; the Dallas Fed would establish a hosting environment. The end result of this collaboration would allow Federal Reserve economists from across the country to be able to use the system.

The Dallas Fed rented out space in a local datacenter, purchased two new servers to serve as a master login node and a temporary storage system, and set about creating BigTex, a supercomputer for Federal Reserve economists.

Economists Compute

Previously, the Federal Reserve System had operated several high performance computing environments that contained, in total, about 5,400 compute cores. BigTex, which came online in July 2019, added 15,000 cores — or about 3 times the capacity.

The Federal Reserve is the largest employer of research economists in the U.S. with 400 PhD-level staff. In less than a year, eight of the 13 Federal Reserve banks have signed up to use BigTex and 60 of the 400 economists have used the system to date.

Some researchers, including Richter, are using BigTex to model the non-linear impacts of policy decisions or shocks to the system. In the past, economic models either assumed simplified, linear effects to changes in interest rates or the state of the economy. But with BigTex, researchers are able to tackle more realistic scenarios.

A recent paper from Richter and his collaborators forthcoming in the Journal of Monetary Economics explores various algorithms for estimating non-linear models in cases where the short-term nominal interest rate sinks to zero, creating a ‘kink’ in most models.

“The study asks how well nonlinear solution and estimation techniques compare to linear and quasi-linear methods” Richter said. “It was our most numerically intensive project to date.”

A team from the Federal Reserve of New York, led by Marco Del Negro, is developing algorithms that allow one to quickly update previously trained and tested estimators using new data. This allows economists to rapidly determine what an outcome of a new economic decision could be based on the latest information, without having to re-analyze decades of data. These algorithms make heavy use of parallel computing and hence of BigTex.

They described their results in the Federal Reserve Bank of New York Staff Reports, August 2019.

“BigTex was a game-changer for us,” Del Negro said. “Without it we could have never finished our project.”

Serdar Birinci, an economist with the Federal Reserve Bank of St. Louis, has been exploring the best possible design of unemployment insurance (UI) payments during recessions and expansions. A more generous UI system mitigates the negative effects of job loss, but at the same time incentives staying unemployed. Using BigTex, he found that the best design of the system features more generous payment amounts and much longer payment durations in recessions, as in European policies.

“Analyzing the best design of UI system requires solving a complex economic model under different values of UI replacement rates and UI payment durations,” Birinci said. “A joint determination of these two policy instruments requires solving the model thousands of times. Without having access to BigTex, this would be almost impossible.”

“My colleagues are really happy with BigTex,” Richter said. “It opens the door to research that was previously not able to be done. It’s more efficient and people are benefitting.”

The burgeoning relationship with UT Dallas, TACC, and data center operators is another success. “The fact that we built these partnerships is a very big deal,” he said. “We took an initiative at the local level and turned it into something that has benefited the organization at the national level.”

Not only does the research help economists at the Federal Reserve — it serves as a model for economics researchers in academia and industry.

“TACC produces pie charts of who’s using their resources. One thing that stands out… economists aren’t in them,” Richter said. “It’s important to get more economists and social scientists into the advanced computing fold. I think that’s something worth continuing.”

Header image: BigTex at Flexential Plano data center.

About the Author

Aaron Dubrow is a Science And Technology Writer with the Communications, Media & Design Group at the Texas Advanced Computing Center.

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!

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that have occurred about once a decade. With this in mind, the ISC Read more…

2024 Winter Classic: Texas Two Step

April 18, 2024

Texas Tech University. Their middle name is ‘tech’, so it’s no surprise that they’ve been fielding not one, but two teams in the last three Winter Classic cluster competitions. Their teams, dubbed Matador and Red Read more…

2024 Winter Classic: The Return of Team Fayetteville

April 18, 2024

Hailing from Fayetteville, NC, Fayetteville State University stayed under the radar in their first Winter Classic competition in 2022. Solid students for sure, but not a lot of HPC experience. All good. They didn’t Read more…

Software Specialist Horizon Quantum to Build First-of-a-Kind Hardware Testbed

April 18, 2024

Horizon Quantum Computing, a Singapore-based quantum software start-up, announced today it would build its own testbed of quantum computers, starting with use of Rigetti’s Novera 9-qubit QPU. The approach by a quantum Read more…

2024 Winter Classic: Meet Team Morehouse

April 17, 2024

Morehouse College? The university is well-known for their long list of illustrious graduates, the rigor of their academics, and the quality of the instruction. They were one of the first schools to sign up for the Winter Read more…

MLCommons Launches New AI Safety Benchmark Initiative

April 16, 2024

MLCommons, organizer of the popular MLPerf benchmarking exercises (training and inference), is starting a new effort to benchmark AI Safety, one of the most pressing needs and hurdles to widespread AI adoption. The sudde Read more…

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that ha Read more…

Software Specialist Horizon Quantum to Build First-of-a-Kind Hardware Testbed

April 18, 2024

Horizon Quantum Computing, a Singapore-based quantum software start-up, announced today it would build its own testbed of quantum computers, starting with use o Read more…

MLCommons Launches New AI Safety Benchmark Initiative

April 16, 2024

MLCommons, organizer of the popular MLPerf benchmarking exercises (training and inference), is starting a new effort to benchmark AI Safety, one of the most pre Read more…

Exciting Updates From Stanford HAI’s Seventh Annual AI Index Report

April 15, 2024

As the AI revolution marches on, it is vital to continually reassess how this technology is reshaping our world. To that end, researchers at Stanford’s Instit Read more…

Intel’s Vision Advantage: Chips Are Available Off-the-Shelf

April 11, 2024

The chip market is facing a crisis: chip development is now concentrated in the hands of the few. A confluence of events this week reminded us how few chips Read more…

The VC View: Quantonation’s Deep Dive into Funding Quantum Start-ups

April 11, 2024

Yesterday Quantonation — which promotes itself as a one-of-a-kind venture capital (VC) company specializing in quantum science and deep physics  — announce Read more…

Nvidia’s GTC Is the New Intel IDF

April 9, 2024

After many years, Nvidia's GPU Technology Conference (GTC) was back in person and has become the conference for those who care about semiconductors and AI. I Read more…

Google Announces Homegrown ARM-based CPUs 

April 9, 2024

Google sprang a surprise at the ongoing Google Next Cloud conference by introducing its own ARM-based CPU called Axion, which will be offered to customers in it 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…

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…

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…

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…

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…

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…

Leading Solution Providers

Contributors

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…

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…

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…

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…

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…

Eyes on the Quantum Prize – D-Wave Says its Time is Now

January 30, 2024

Early quantum computing pioneer D-Wave again asserted – that at least for D-Wave – the commercial quantum era has begun. Speaking at its first in-person Ana Read more…

GenAI Having Major Impact on Data Culture, Survey Says

February 21, 2024

While 2023 was the year of GenAI, the adoption rates for GenAI did not match expectations. Most organizations are continuing to invest in GenAI but are yet to Read more…

The GenAI Datacenter Squeeze Is Here

February 1, 2024

The immediate effect of the GenAI GPU Squeeze was to reduce availability, either direct purchase or cloud access, increase cost, and push demand through the roof. A secondary issue has been developing over the last several years. Even though your organization secured several racks... Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire