When Is the Cloud Right for HPC?

By Tiffany Trader

April 16, 2013

In discussions of cloud computing, as with most discourse today, strong opinions are par for the course. Cloud is either the way of the future or an unrealistic marketing ploy, and when the topic at hand moves to running HPC applications in the cloud, viewpoints are if anything even more contentious.

Questions such as “should I rent or buy?” don’t mean much without a specific example to refer to, and this is true regardless of the application being considered. The best answer usually starts with “it depends…”

A recent article from Jeff Layton, a well-known industry technologist, demonstrates a more balanced approach to the subject of HPC cloud. He writes:

I don’t think the shift to cloud computing for some HPC applications is happening because a CIO or director of research computing watched a cloud computing commercial and thinks it sounds really cool. Rather, I think HPC has existing workloads that fit well into cloud computing and can actually save money over traditional solutions. Perhaps more importantly, I think HPC has evolved to include non-traditional workloads and is adapting to meet those workloads, in many cases using cloud computing to do so.

Layton backs up his point with two examples. The first scenario is massively concurrent runs. At an HPC center, a group of researchers needs to examine 25,000 to 30,000 different data sets as part of a perimeter sweep. Most of the time, these are applications that take only a couple of minutes and do not produce a lot of data. A second group of OS and security researchers are exploring different simulations with different inputs. The process involves running thousands of jobs simultaneously and then looking for results. Both groups need somewhere between 50,000 and 100,000 cores to run their applications. The important metric for them is core count and not per-core performance, says Layton.

Layton adds that he originally thought this HPC center had a unique workload, but he has since encountered more users with similar requirements. “Although this might not describe your particular workload,” writes Layton, “a number of centers fit this scenario, and this number is growing rapidly.”

The second use case is Web services. No, this isn’t an HPC use case in the traditional sense, but there is, according to Layton, an “increasing need for hosting servers for classes or training, for websites (internal and external), and for other general research-related computing in which the applications are not parallel or might not even be ‘scientific.'” Layton says some people have dubbed this “Ash and Trash computing,” to distinguish it from bread-and-butter HPC apps. [Editor’s note: A Google sanity-check came up short on the term “ash-and-trash” in the context of IT speak, but according to this Vietnam War jargon website, the term referred to any type of non-combat aviation mission.]

Layton goes on to outline several scenarios where renting cycles on-demand makes more sense than doing the work in-house. Using a real-world example from Cycle Computing, he determines that “cloud computing works out to half the cost of a dedicated [virtualized] system for these workloads.”

One of the takehome points from this article is that HPC workloads are changing. They have a different set of characteristics and requirements compared to traditional HPC applications, and in many cases it proves advantageous to run these workloads in an off-site (public) cloud. Benefits include reduced cost and the freeing up of on-site resources for traditional HPC workloads.

Layton writes:

“At first it was fairly easy to dismiss cloud computing for traditional HPC workloads. The “HP,” after all, stands for “high performance,” and doing anything to reduce performance is counterproductive. You are paying more and getting less. However, new workloads are being added to HPC all of the time that might be very different from the classic MPI applications in HPC and have different characteristics. The amount of computation in these new workloads is increasing at an alarming rate – so much so, that I think HPC is giving way to RC (research computing).”

Many of these research computing applications share similar resource requirements. Productivity for this class of workloads has less to do with improving per-core performance, and is instead achieved by running many instances of the application at once – something that public cloud with the illusion of unlimited cycles does well. As is so often the case in HPC, the optimal approach is the one that best fits the application at hand.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

SC17 Preview: Invited Talk Lineup Includes Gordon Bell, Paul Messina and Many Others

September 25, 2017

With the addition of esteemed supercomputing pioneer Gordon Bell to its invited talk lineup, SC17 now boasts a total of 12 invited talks on its agenda. As SC explains, "Invited Talks are a premier component of the SC Read more…

By Tiffany Trader

GlobalFoundries Puts Wind in AMD’s Sails with 12nm FinFET

September 24, 2017

From its annual tech conference last week (Sept. 20), where GlobalFoundries welcomed more than 600 semiconductor professionals (reaching the Santa Clara venue’s max capacity and doubling 2016 attendee numbers), the one Read more…

By Tiffany Trader

Machine Learning at HPC User Forum: Drilling into Specific Use Cases

September 22, 2017

The 66th HPC User Forum held September 5-7, in Milwaukee, Wisconsin, at the elegant and historic Pfister Hotel, highlighting the 1893 Victorian décor and art of “The Grand Hotel Of The West,” contrasted nicely with Read more…

By Arno Kolster

HPE Extreme Performance Solutions

HPE Prepares Customers for Success with the HPC Software Portfolio

High performance computing (HPC) software is key to harnessing the full power of HPC environments. Development and management tools enable IT departments to streamline installation and maintenance of their systems as well as create, optimize, and run their HPC applications. Read more…

Google Cloud Makes Good on Promise to Add Nvidia P100 GPUs

September 21, 2017

Google has taken down the notice on its cloud platform website that says Nvidia Tesla P100s are “coming soon.” That's because the search giant has announced the beta launch of the high-end P100 Nvidia Tesla GPUs on t Read more…

By George Leopold

GlobalFoundries Puts Wind in AMD’s Sails with 12nm FinFET

September 24, 2017

From its annual tech conference last week (Sept. 20), where GlobalFoundries welcomed more than 600 semiconductor professionals (reaching the Santa Clara venue Read more…

By Tiffany Trader

Machine Learning at HPC User Forum: Drilling into Specific Use Cases

September 22, 2017

The 66th HPC User Forum held September 5-7, in Milwaukee, Wisconsin, at the elegant and historic Pfister Hotel, highlighting the 1893 Victorian décor and art o Read more…

By Arno Kolster

Stanford University and UberCloud Achieve Breakthrough in Living Heart Simulations

September 21, 2017

Cardiac arrhythmia can be an undesirable and potentially lethal side effect of drugs. During this condition, the electrical activity of the heart turns chaotic, Read more…

By Wolfgang Gentzsch, UberCloud, and Francisco Sahli, Stanford University

PNNL’s Center for Advanced Tech Evaluation Seeks Wider HPC Community Ties

September 21, 2017

Two years ago the Department of Energy established the Center for Advanced Technology Evaluation (CENATE) at Pacific Northwest National Laboratory (PNNL). CENAT Read more…

By John Russell

Exascale Computing Project Names Doug Kothe as Director

September 20, 2017

The Department of Energy’s Exascale Computing Project (ECP) has named Doug Kothe as its new director effective October 1. He replaces Paul Messina, who is stepping down after two years to return to Argonne National Laboratory. Kothe is a 32-year veteran of DOE’s National Laboratory System. Read more…

Takeaways from the Milwaukee HPC User Forum

September 19, 2017

Milwaukee’s elegant Pfister Hotel hosted approximately 100 attendees for the 66th HPC User Forum (September 5-7, 2017). In the original home city of Pabst Blu Read more…

By Merle Giles

Kathy Yelick Charts the Promise and Progress of Exascale Science

September 15, 2017

On Friday, Sept. 8, Kathy Yelick of Lawrence Berkeley National Laboratory and the University of California, Berkeley, delivered the keynote address on “Breakthrough Science at the Exascale” at the ACM Europe Conference in Barcelona. In conjunction with her presentation, Yelick agreed to a short Q&A discussion with HPCwire. Read more…

By Tiffany Trader

DARPA Pledges Another $300 Million for Post-Moore’s Readiness

September 14, 2017

The Defense Advanced Research Projects Agency (DARPA) launched a giant funding effort to ensure the United States can sustain the pace of electronic innovation vital to both a flourishing economy and a secure military. Under the banner of the Electronics Resurgence Initiative (ERI), some $500-$800 million will be invested in post-Moore’s Law technologies. Read more…

By Tiffany Trader

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

NERSC Scales Scientific Deep Learning to 15 Petaflops

August 28, 2017

A collaborative effort between Intel, NERSC and Stanford has delivered the first 15-petaflops deep learning software running on HPC platforms and is, according Read more…

By Rob Farber

Oracle Layoffs Reportedly Hit SPARC and Solaris Hard

September 7, 2017

Oracle’s latest layoffs have many wondering if this is the end of the line for the SPARC processor and Solaris OS development. As reported by multiple sources Read more…

By John Russell

Six Exascale PathForward Vendors Selected; DoE Providing $258M

June 15, 2017

The much-anticipated PathForward awards for hardware R&D in support of the Exascale Computing Project were announced today with six vendors selected – AMD Read more…

By John Russell

Top500 Results: Latest List Trends and What’s in Store

June 19, 2017

Greetings from Frankfurt and the 2017 International Supercomputing Conference where the latest Top500 list has just been revealed. Although there were no major Read more…

By Tiffany Trader

IBM Clears Path to 5nm with Silicon Nanosheets

June 5, 2017

Two years since announcing the industry’s first 7nm node test chip, IBM and its research alliance partners GlobalFoundries and Samsung have developed a proces Read more…

By Tiffany Trader

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Leading Solution Providers

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

Google Releases Deeplearn.js to Further Democratize Machine Learning

August 17, 2017

Spreading the use of machine learning tools is one of the goals of Google’s PAIR (People + AI Research) initiative, which was introduced in early July. Last w Read more…

By John Russell

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurrencies like Bitcoin, along with classified government communications and other sensitive digital transfers. Read more…

By Doug Black

EU Funds 20 Million Euro ARM+FPGA Exascale Project

September 7, 2017

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development. Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work... Read more…

By Tiffany Trader

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

Amazon Debuts New AMD-based GPU Instances for Graphics Acceleration

September 12, 2017

Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The Read more…

By John Russell

Cray Moves to Acquire the Seagate ClusterStor Line

July 28, 2017

This week Cray announced that it is picking up Seagate's ClusterStor HPC storage array business for an undisclosed sum. "In short we're effectively transitioning the bulk of the ClusterStor product line to Cray," said CEO Peter Ungaro. Read more…

By Tiffany Trader

IBM Advances Web-based Quantum Programming

September 5, 2017

IBM Research is pairing its Jupyter-based Data Science Experience notebook environment with its cloud-based quantum computer, IBM Q, in hopes of encouraging a new class of entrepreneurial user to solve intractable problems that even exceed the capabilities of the best AI systems. Read more…

By Alex Woodie

  • arrow
  • Click Here for More Headlines
  • arrow
Share This