Utility HPC: What Every Enterprise Can Learn from Utility Supercomputing

By Jason Stowe

June 3, 2013

By Jason Stowe, CEO

I’m struck by the number of IT professionals I speak with that find unexpected uses for Utility Supercomputing. In fact, whether your compute demands warrant 50 cores of HPC, or 50,000 cores, the management challenges are quite similar. Cycle Computing is probably best known for the dramatic results our software has made possible in such compute-intensive applications as Computational Chemistry, Genome Sequencing, and Risk Analytics. For example, a Top 10 Pharma customer of ours built a 10,600 instance cluster – the equivalent of $44M in infrastructure – in just 2 hours, then used it to run 40 years of science in 11 hours for $4,372.

But many of our customers use our Utility HPC software to orchestrate workloads on clusters in the range of 10s – 100s of cores – most of which are hybrid clusters (private and public) at that. It turns out that the fact that we know how to prepare a cluster of 10,000 cores means we can actually create a small cluster that much more reliably.

So what lessons can any Enterprise IT organization learn from the experiences of their larger compute-consuming colleagues? 

1. Know thy workload to optimize costs.

Regardless of how large (or small) scale your compute requirements are, you must understand how parallelizable the applications you’ll be running on Cloud HPC resources are before you can  optimize the size and duration of the instances you procure to support them. For example, the more modular the job requests, the easier it is to parse them across low-cost spot instances of compute when they are available.

2. Play nice with others (Openness matters).

Proprietary approaches to orchestrating workloads across private and public HPC environments should be avoided in any enterprise. When looking for ways to automate and administer your HPC resources, why restrict your options in the areas of configuration or storage management, infrastructure and development tools? Even if you don’t anticipate your environment changing, it’s better to select an orchestration solution that is open and works with a wide range of supporting tools, such as Open Grid Scheduler, HTCondor and Chef, and works with applications developed in a variety of languages. Support for multiple cloud providers is also an important consideration.

3. Wherefore art thou, Data?

You don’t have to have “Big Data” requirements, to make data awareness an important part of your HPC orchestration strategy. Applications don’t live by compute alone – they inevitably require input and generate output, regardless of how large or small. Many organizations face a cost / latency tradeoff when it comes to data access: save money with lower cost, “cold storage” options such as Amazon’s Glacier which require users to wait days to restore archived data if and when they need it. Or store data in more expensive, readily available EC2 storage. It doesn’t have to be an all or nothing scenario however, if you have the ability to centrally orchestrate data movement and access as applications demand it. Another Top 10 Pharma customer is deploying Cycle’s DataManager to automate archival and retrieval of 75TB data sets to and from Amazon Glacier, without the need to re-code or disrupt their application’s workflow.

4. Manage from a central vantage point.

Not unlike an air traffic controller, Enterprise IT needs a 360⁰ view of the HPC resources at their disposal. The lack of visibility into what’s actually running where – whether on internal or external HPC clusters – forces many organizations to overprovision additional cores to handle unexpected peak loads. When organizations can manage all of their workloads from a central management console, they can readily harvest unused resources when needed. Additional resources can be cost-effectively provisioned on-demand, as required to support larger runs such as quarterly regulatory reporting risk analysis.

5. Security, Security, Security!

Security concerns are one of the most cited reasons organizations use to restrict which workloads they run in the cloud. The reality is that in fact, centrally orchestrated HPC environments afford greater control over how encryption is handled. User authentication can likewise be centrally governed and leverage existing LDAP or other established protocols to enforce consistent secure access to applications and data on-premise in the cloud. License keys are also centrally monitored so organizations can easily distinguish cloud-based access to licensed applications. This is a key benefit for IT organizations and ISVs looking to cloud-enable custom developed software without re-architecting their license key management approach. 

Applying these lessons proven successful in our real customer workloads, organizations can accelerate business analytic, product development, and scientific processes. Truly breaking through with utility HPC. For more information, please visit www.cyclecomputing.com or email info@cyclecomputing.com

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!

UCSD, AIST Forge Tighter Alliance with AI-Focused MOU

January 18, 2018

The rich history of collaboration between UC San Diego and AIST in Japan is getting richer. The organizations entered into a five-year memorandum of understanding on January 10. The MOU represents the continuation of a 1 Read more…

By Tiffany Trader

New Blueprint for Converging HPC, Big Data

January 18, 2018

After five annual workshops on Big Data and Extreme-Scale Computing (BDEC), a group of international HPC heavyweights including Jack Dongarra (University of Tennessee), Satoshi Matsuoka (Tokyo Institute of Technology), Read more…

By John Russell

Researchers Measure Impact of ‘Meltdown’ and ‘Spectre’ Patches on HPC Workloads

January 17, 2018

Computer scientists from the Center for Computational Research, State University of New York (SUNY), University at Buffalo have examined the effect of Meltdown and Spectre security updates on the performance of popular H Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

HPE and NREL Take Steps to Create a Sustainable, Energy-Efficient Data Center with an H2 Fuel Cell

As enterprises attempt to manage rising volumes of data, unplanned data center outages are becoming more common and more expensive. As the cost of downtime rises, enterprises lose out on productivity and valuable competitive advantage without access to their critical data. Read more…

Fostering Lustre Advancement Through Development and Contributions

January 17, 2018

Six months after organizational changes at Intel's High Performance Data (HPDD) division, most in the Lustre community have shed any initial apprehension around the potential changes that could affect or disrupt Lustre Read more…

By Carlos Aoki Thomaz

UCSD, AIST Forge Tighter Alliance with AI-Focused MOU

January 18, 2018

The rich history of collaboration between UC San Diego and AIST in Japan is getting richer. The organizations entered into a five-year memorandum of understandi Read more…

By Tiffany Trader

New Blueprint for Converging HPC, Big Data

January 18, 2018

After five annual workshops on Big Data and Extreme-Scale Computing (BDEC), a group of international HPC heavyweights including Jack Dongarra (University of Te Read more…

By John Russell

Researchers Measure Impact of ‘Meltdown’ and ‘Spectre’ Patches on HPC Workloads

January 17, 2018

Computer scientists from the Center for Computational Research, State University of New York (SUNY), University at Buffalo have examined the effect of Meltdown Read more…

By Tiffany Trader

Fostering Lustre Advancement Through Development and Contributions

January 17, 2018

Six months after organizational changes at Intel's High Performance Data (HPDD) division, most in the Lustre community have shed any initial apprehension aroun Read more…

By Carlos Aoki Thomaz

When the Chips Are Down

January 11, 2018

In the last article, "The High Stakes Semiconductor Game that Drives HPC Diversity," I alluded to the challenges facing the semiconductor industry and how that may impact the evolution of HPC systems over the next few years. I thought I’d lift the covers a little and look at some of the commercial challenges that impact the component technology we use in HPC. Read more…

By Dairsie Latimer

How Meltdown and Spectre Patches Will Affect HPC Workloads

January 10, 2018

There have been claims that the fixes for the Meltdown and Spectre security vulnerabilities, named the KPTI (aka KAISER) patches, are going to affect applicatio Read more…

By Rosemary Francis

Momentum Builds for US Exascale

January 9, 2018

2018 looks to be a great year for the U.S. exascale program. The last several months of 2017 revealed a number of important developments that help put the U.S. Read more…

By Alex R. Larzelere

ANL’s Rick Stevens on CANDLE, ARM, Quantum, and More

January 8, 2018

Late last year HPCwire caught up with Rick Stevens, associate laboratory director for computing, environment and life Sciences at Argonne National Laboratory, f Read more…

By John Russell

Inventor Claims to Have Solved Floating Point Error Problem

January 17, 2018

"The decades-old floating point error problem has been solved," proclaims a press release from inventor Alan Jorgensen. The computer scientist has filed for and Read more…

By Tiffany Trader

US Coalesces Plans for First Exascale Supercomputer: Aurora in 2021

September 27, 2017

At the Advanced Scientific Computing Advisory Committee (ASCAC) meeting, in Arlington, Va., yesterday (Sept. 26), it was revealed that the "Aurora" supercompute Read more…

By Tiffany Trader

Japan Unveils Quantum Neural Network

November 22, 2017

The U.S. and China are leading the race toward productive quantum computing, but it's early enough that ultimate leadership is still something of an open questi Read more…

By Tiffany Trader

AMD Showcases Growing Portfolio of EPYC and Radeon-based Systems at SC17

November 13, 2017

AMD’s charge back into HPC and the datacenter is on full display at SC17. Having launched the EPYC processor line in June along with its MI25 GPU the focus he Read more…

By John Russell

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

IBM Begins Power9 Rollout with Backing from DOE, Google

December 6, 2017

After over a year of buildup, IBM is unveiling its first Power9 system based on the same architecture as the Department of Energy CORAL supercomputers, Summit a Read more…

By Tiffany Trader

Fast Forward: Five HPC Predictions for 2018

December 21, 2017

What’s on your list of high (and low) lights for 2017? Volta 100’s arrival on the heels of the P100? Appearance, albeit late in the year, of IBM’s Power9? Read more…

By John Russell

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

Leading Solution Providers

Chip Flaws ‘Meltdown’ and ‘Spectre’ Loom Large

January 4, 2018

The HPC and wider tech community have been abuzz this week over the discovery of critical design flaws that impact virtually all contemporary microprocessors. T Read more…

By Tiffany Trader

Perspective: What Really Happened at SC17?

November 22, 2017

SC is over. Now comes the myriad of follow-ups. Inboxes are filled with templated emails from vendors and other exhibitors hoping to win a place in the post-SC thinking of booth visitors. Attendees of tutorials, workshops and other technical sessions will be inundated with requests for feedback. Read more…

By Andrew Jones

Tensors Come of Age: Why the AI Revolution Will Help HPC

November 13, 2017

Thirty years ago, parallel computing was coming of age. A bitter battle began between stalwart vector computing supporters and advocates of various approaches to parallel computing. IBM skeptic Alan Karp, reacting to announcements of nCUBE’s 1024-microprocessor system and Thinking Machines’ 65,536-element array, made a public $100 wager that no one could get a parallel speedup of over 200 on real HPC workloads. Read more…

By John Gustafson & Lenore Mullin

Delays, Smoke, Records & Markets – A Candid Conversation with Cray CEO Peter Ungaro

October 5, 2017

Earlier this month, Tom Tabor, publisher of HPCwire and I had a very personal conversation with Cray CEO Peter Ungaro. Cray has been on something of a Cinderell Read more…

By Tiffany Trader & Tom Tabor

Flipping the Flops and Reading the Top500 Tea Leaves

November 13, 2017

The 50th edition of the Top500 list, the biannual publication of the world’s fastest supercomputers based on public Linpack benchmarking results, was released Read more…

By Tiffany Trader

GlobalFoundries, Ayar Labs Team Up to Commercialize Optical I/O

December 4, 2017

GlobalFoundries (GF) and Ayar Labs, a startup focused on using light, instead of electricity, to transfer data between chips, today announced they've entered in Read more…

By Tiffany Trader

How Meltdown and Spectre Patches Will Affect HPC Workloads

January 10, 2018

There have been claims that the fixes for the Meltdown and Spectre security vulnerabilities, named the KPTI (aka KAISER) patches, are going to affect applicatio Read more…

By Rosemary Francis

HPC Chips – A Veritable Smorgasbord?

October 10, 2017

For the first time since AMD's ill-fated launch of Bulldozer the answer to the question, 'Which CPU will be in my next HPC system?' doesn't have to be 'Whichever variety of Intel Xeon E5 they are selling when we procure'. Read more…

By Dairsie Latimer

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