Perfect Storm Brewing for Government HPC

By Nicole Hemsoth

January 13, 2014

It’s been a rocky couple of years for the United States government on all fronts, with dwindling budgets tripping over increased demand for maintenance and growth across the board. Despite these concerns, the growth of high performance computing as a dominant part of federal and state organizations remains steady, according to Patrick Dreher, DRC’s Chief Scientist of their High Performance Technologies Group.

“We are seeing strong demand for HPC from state and federal departments and agencies where it is almost universally recognized that HPC is a cost effective tool for not only simulations in science and engineering, but also for development and prototyping,” said Dreher. “HPC has been branching beyond the domain of chemists, physicists and mathematician—and the development is focused on new types of applications that are finding their way into many key areas.”

Few other companies have the insight that DRC has about the actual constraints, concerns and trends for government-fed high performance computing across agencies. DRC, which has been in the government technology consulting and training business since the black and white era, has an insider view on system decisions for the Department of Defense, Department of Energy, as well as a number of military, health, and regulatory agencies.

Given their observations in recent years, DRC has found that the real issue for government organizations when it comes to HPC is dealing with the “perfect storm” of system and application needs. On the one hand, agencies and departments are seeking new architectures that will lend to better efficiency, higher productivity, and better results—all of which need to be wrapped around a very compelling, proven financial story. However, with new architectures comes the need for advancements on the software side, which are far more time consuming and costly than some realize, says Dreher.

While power consumption, hardware and system upgrades are costly, one of the most profound costs agencies face is on the software side, even if it tends to be the hardware upgrades and shifts in architecture that tend to garner the most attention from those watching spending. For instance, a federal department or agency may decide that the moving from a system with around 1000 cores to one with 10,000 or even 100,000 might make good sense for productivity, the software costs of making sure that the application runs smoothly by retuning the file system and addressing I/O and other issues adds significantly to the project’s bottom line, notes Dreher. As another example, while the model for GPUs might be evaluated in terms of hardware costs, Dreher says it’s surprising what such a move can mean cost-wise when entire, stable applications need to be reworked entirely, but it’s a factor they always consider when evaluating the cost-effectiveness of a proposal.

The hardware and software “storm” has another heavy cloud on the horizon, says Dreher. Add the architectural and software concerns to another item on the government HPC agenda—data. Whether agencies are creating new, more robust models or making use of new machines (genomic sequencers, for example) or simply adding cores to boost an application’s capability, this all means the creation (and subsequent storage, processing and curating) of even more data. The biggest problem for agencies is finding ways to manage and extract valuable insight from the influx, Dreher notes. While there are some noteworthy technologies for solving these problems (he pointed to YarcData’s systems as a prime example) this in itself creates another factor to consider.

“One of the biggest concerns among users now, and I imagine in the future, is that they are going to be left with different machines for different problems.” In other words, Dreher says that agencies are finding that they will need to dedicate specific systems to processing data, certain machines for simple number crunching, and others that are specifically geared toward their research. Users want these capabilities in one system but a solution to that problem has yet to emerge.

The storm, which has elements of data, new architectures, the need for more cores and better performance, as well as the inherent software tweaks required that add time and expense, continues to float overhead. Interestingly, this same set of considerations isn’t much different than those that are coming from large companies who are facing similar challenges in relation to cost, productivity, and a constant need for more compute and data handling capability. If one is taking a market view of this from an HPC perspective, this is not just the perfect storm of concerns for users—it’s a perfect moment to capitalize on an undisputed set of needs for a system that considers these elements as a whole to provide an integrated solution.

“The U.S. government is clearly under budget pressure and at the same time, there is pressure from the users and agencies to use HPC to get better productivity and make new discoveries. Up until about 10 years ago, the agencies and departments could count on the vendors to come out with a new and advanced archicture. The users would then count on the fact that they would just make a few small change– they’d up the clock frequencies, up the transistor count. But that trend came to an end since you can’t keep upping the clock frequency, for example—they need to find other ways to get better performance,” said Dreher.

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