Utility Supercomputing Heats Up

By Nicole Hemsoth

February 28, 2013

The HPC in the cloud space continues to evolve and one of the companies leading that charge is Cycle Computing. The utility supercomputing vendor recently reported a record-breaking 2012, punctuated by several impressive big science endeavors. One of Cycle’s most significant projects was the creation of a 50,000-core utility supercomputer inside the Amazon Elastic Compute Cloud.

Built for pharmaceutical companies Schrödinger and Nimbus Discovery, the virtual mega-cluster was able to analyze 21 million drug compounds in just 3 hours for less than $4,900 per hour. The accomplishment caught the attention of IDC analysts Chirag Dekate and Steve Conway, who elected to honor Cycle with their firm’s HPC Innovation Excellence Award.

Research Manager of IDC’s High-Performance Systems Chirag Dekate explained the award recognizes those who have best applied HPC in the ecosystem to solve critical problems. More specifically, IDC is looking for scientific achievement, ROI, and a combination of these two elements.

HPCwire spoke with Cycle CEO Jason Stowe shortly after the award was announced about the growth in HPC cloud and his company. Stowe really sees 2012 as the turning point – both for the space and for Cycle Computing. “We’ve basically hit the hockey stick growth period where there’s more rapid adoption of the technology,” he says. “Relative to utility supercomputing and HPC cloud in general we are definitely seeing a lot of interest in the space.”

During the Amazon Web Services re:Invent show in November, some big-name customers, including Novartis, Johnson & Johnson, Life Technologies, along with Hartford Insurance Group and Pacific Life Insurance, came forward to discuss their use of Cycle’s cluster-building software. The companies highlighted many of their biggest use cases and described how HPC cloud helps move the needle for Fortune500.

“Utility supercomputing applies to a large variety of companies regardless of their industry,” says Stowe, “because it supports business analytics, it supports various forms of engineering simulations and helps get the science done.”

Cycle’s customer base is well-represented across disciplines. “The majority of the top 20 big pharma companies use our software; three of the five largest variable annuity businesses use our software internally and externally or in combination,” says the CEO. The vendor also counts several leading life science companies among its customer base, including Schrödinger, who in addition to their initial 50k core run, continues to use the Cycle-EC2 cluster for ongoing workloads. Manufacturing and energy companies are also plugging into the Cycle cloud.

There are still technical and cultural barriers to cloud adoption, however. Stowe concedes the point, but only half-jokingly he adds that Cycle has solved most of the technical challenges. At this juncture, he believes the lag is more on cultural side, but there are signs of progress.

“We have these traditional companies like Johnson & Johnson and Hartford Life transitioning to a cloud model. That’s a huge cultural indicator, and definitely a C-change from four-to-five years ago,” he says.

Next >> the Business Model

The Business Model

What about the long-term profit potential for a business that relies on data parallel workloads? The question is met with a three-part answer. First off, Stowe says that Cycle has always been profitable. As a bootstrapped company, they have no investors. They’ve built a business off of a real cash-flow stream. Second, he insists that the vast amount of growth in computation is in the area of data-parallel applications.

He considers business analytics, the entirety of big data and a majority of even traditional simulation codes to be strong candidates for the cloud or utility supercomputing model.

“Sure, people still use MPI, they still use fast interconnect – but we have cases (and we hope to publish soon) where folks are running Monte Carlo simulations as a data-parallel problem. There’s a small MPI cluster that’s running the simulation, but the overall structure of the computation is parallel,” says Stowe.

Stowe expects these kinds of data-parallel or high-throughput applications to make up the bulk of new commercial workloads. The activity is coming from a range of verticals: genomics, computational chemistry, even finite element analysis.

Stowe’s final point in the context of MPI applications might be surprising to some. Cycle has seen at least two examples of real-world MPI applications that ran as much as 40 percent better on the Amazon EC2 cloud than on an internal kit that used QDR InfiniBand.

“The only real test of whether or not cloud is right for you is to actually bench it in comparison to the kit you are using in-house,” he advises.

Stowe’s team was not particularly surprised. “A lot of MPI applications under the hood are essentially doing low-interconnect, master-worker kind of workloads,” he adds.

Stowe readily admits there are applications that require the fastest interconnects and highly-tuned systems – “like weather simulations, nuclear bomb testing, the stuff at Oak Ridge or Sandia” – but he contends that some of the newer applications, especially those written in-house or by a domain scientist as opposed to a computer scientist, often run faster on cloud.

“It’s so cheap to do a bench, so why not just verify it. I’m an engineer at heart, so I’m very practical. We can talk about the theory, but it’s hard to argue with results,” he adds.

Next >> Another Tool in the Toolbox

Another Tool in the Toolbox

So much of the discussion around HPC cloud focuses on the so-called I/O problem – the bandwidth and latency challenges associated with a general public cloud like Amazon. “What about performance?” critics will ask.

Stowe feels that questions like this point to cloud necessarily replacing large capability machines, but that’s not how he sees it.

“I think of it as a radically different kind of capability machine,” says Stowe. “The old kind of capability machine required millions of dollars and tons of planning and special environments to be created, heating/cooling/power, expert staff, and so on. These systems are used very heavily for a certain kind of application, and that’s the right thing to do.”

Stowe looks at utility supercomputing as another tool in the toolbox. It doesn’t need to replace traditional capability machines, which will still be needed for certain kinds of applications. In fact, he says you can think of the Cycle-AWS cloud as another kind of capability machine with an attractive set of benefits (on-demand, pay for what you use, scalable, elastic, lower overhead).

It’s a different branch of the same tree, he says.

IDC’s Dekate takes pretty much the same position. He sees HPC in the cloud and dedicated HPC clusters as complementary.

“The HPC ecosystem is diverse and there’s a class of applications that makes sense for utility supercomputing,” says Dekate. “Solving the diverse needs of the user community requires different kinds of technological capabilities, including dedicated hardware infrastructure and HPC cloud frameworks. Our argument is that one does not have to replace the other. It’s more important to find the right kind of matches for applications that work well in either or both of these cases.”

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!

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…

Nvidia Appoints Andy Grant as EMEA Director of Supercomputing, Higher Education, and AI

March 22, 2024

Nvidia recently appointed Andy Grant as Director, Supercomputing, Higher Education, and AI for Europe, the Middle East, and Africa (EMEA). With over 25 years of high-performance computing (HPC) experience, Grant brings a 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…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the fi 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