SDSC’s ‘Trestles’ Supercomputer Still Going Strong Three+ Years Later

By Jan Zverina

December 21, 2018

Supercomputers typically have a useful life of about five years, as these high-performance systems, many running 24/7, slowly succumb to burn-out – of their nodes, that is – as well as steady advances in processing technologies.

Not so with Trestles, which was acquired more than three years ago by the Arkansas High Performance Computing Center (AHPCC) at the University of Arkansas after entering service at the San Diego Supercomputer Center (SDSC) at UC San Diego in mid-2011 under a $2.8 million National Science Foundation (NSF) grant.

(L to R) AHPCC Director David Chaffin; Director of Strategic Initiatives & User Services Jeff Pummill; and Senior Administrator/Program Director Pawel Wolinski, with the Trestles supercomputer. Image courtesy of AHPCC

Billed as a “high-productivity workhorse,” Trestles was based on the concept that by tailoring a system for the majority of modest-scale jobs rather than a handful of researchers who run jobs at thousands of core counts, users could achieve higher throughput and increased scientific productivity.

While at SDSC, Trestles users spanned a wide range of domain applications, including astronomy, biophysics, climate science, computational chemistry, materials science, and more. It was also recognized as a leading platform for science gateway applications; for example, the system served more than 650 users per month via the popular CIPRES phylogenetics portal alone.

“It’s terrific that University of Arkansas researchers have been able to use Trestles for several years beyond its decommissioning as a national NSF resource and to extend the scientific impact of NSF’s HPC investments,” said Richard Moore, the principal investigator for the Trestles award and SDSC’s now-retired deputy director.

Trestles continues to deliver on that strategy today, more than three years into its “next life” as a valuable research resource at the U of A. AHPCC’s latest estimates are that during that time, Trestles has provided more than 136 million CPU hours of service, with over 804,000 jobs run among almost 200 active users.

Trestles came to us at a time where computational needs were peaking in the form of explosive growth and demand in the faculty researcher community,” said AHPCC Director of Strategic Initiatives & User Services Jeff Pummill, who is also a Trestles user in the area of multi-omics, primarily with the U of A’s Biological Sciences and Agricultural departments. “Queue wait times were getting unacceptably long and jobs were stacking up. So the arrival of 8000+ compute cores was a welcome sight for all of us.”

Pummill noted that architecturally, Trestles has been ideal for work in the areas of bioinformatics and genomics, as its software is typically Shared Memory Parallel (SMP), which uses multiple processors on the same computer, as opposed to Distributed Memory Parallel (DMP), which uses multiple processors on either the same or multiple computers. “Trestles’ nodes are configured with 32 compute cores and 64 gigs of memory, which is ideal for smaller bacterial genome work, but useful for many aspects of larger eukaryotic genome work,” he added.


What’s in a name? Some Trestles Trivia

After being transferred to the Arkansas High Performance Computing Center, it was decided to keep the Trestles name. But why Trestles in the first place?

“I was taking up surfing at the time we proposed this system to the NSF, and thought that the Trestles Bridge in San Diego would be a nice way to acknowledge both the local aspect of the system, as well as the idea that it was a bridge to using high-performance computing,” according to Shawn Strande, SDSC’s deputy director.


Research Highlights

Some examples of research projects using Trestles at the U of A include:

  • Materials Engineering: A research team including Salvador Barraza-Lopez, associate professor of physics at the U of A, and Taneshwor Kaloni, a former post-doctoral researcher in Barraza-Lopez’s lab, shed light on the behavior of one of ultrathin materials known as tin telluride (SnTe). The study detailing their findings was published in the journal Advanced Materials.
  • Neurosciences: Vidit Agrawal, a graduate student in the U of A’s Physics Department has been using Trestles to perform simulations of large neural networks and conduct a statistical analysis on experimental results.
  • Supply chain analysis: Agrawal has also used Trestles to investigate the structural fragility of supply networks and explore its relationship with a firm’s equity risk. “AHPCC has been of great help to me as it has cut down my overall computation time from months to days.”
  • Microbiome research: Jiangchao Zhao, an assistant professor with the U of A’s Department of Animal Science, used Trestles to identify gut microbiome signatures that when associated with longevity provides a promising modulation target for healthy aging.

Additional research projects can be found here.

Re-use, Not Recycling

While many supercomputers still end up on the scrap heap, the continued operation of Trestles beyond its expected lifespan is just one example of lasting computational power and productivity.

In early 2017, SDSC and the Simons Foundation’s Flatiron Institute in New York reached an agreement under which the majority of SDSC’s data-intensive Gordon supercomputer would be used by Simons for ongoing research following completion of the system’s tenure as a NSF resource on March 31 of that year, following five years of service. While Gordon is now primarily used by the Simons Foundation, the system remains housed in SDSC’s data center.

“It’s very gratifying to see SDSC’s HPC systems continue to serve a wide range of researchers following their NSF tenures,” said SDSC Director Michael Norman. “For us, it’s testimony to designing a robust architecture from the start, which contributes to their useful lives well beyond what’s typical for such systems.”

In early 2018, the NSF extended the use of SDSC’s current petascale system, Comet, for a sixth year of service, into March of 2021. Comet is now one of the most widely used supercomputers in the NSF’s XSEDE program. Under a separate NSF award valued at about $900,000 SDSC recently doubled the number of graphic processing units (GPUs) on Comet in direct response to growing demand for GPU computing among a wide range of research domains.

About AHPCC

The Arkansas High Performance Computing Center, a core research facility under the Office of Research and Innovation at the University of Arkansas and founded in 2008, supports research for about 260 users in about 30 academic areas across the University of Arkansas campus, including bioinformatics, condensed matter physics, integrated nanoscience, computational chemistry, computational biomagnetics, materials science, spatial science, and economics among others.

About SDSC

As an Organized Research Unit of UC San Diego, SDSC is considered a leader in data-intensive computing and cyberinfrastructure, providing resources, services, and expertise to the national research community, including industry and academia. Cyberinfrastructure refers to an accessible, integrated network of computer-based resources and expertise, focused on accelerating scientific inquiry and discovery. SDSC supports hundreds of multidisciplinary programs spanning a wide variety of domains, from earth sciences and biology to astrophysics, bioinformatics, and health IT. SDSC’s petascale Comet supercomputer is a key resource within the National Science Foundation’s XSEDE (eXtreme Science and Engineering Discovery Environment) program.

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