Opening Sequences for HPC on Demand

By Nicole Hemsoth

May 11, 2011

Next generation DNA sequencing has brought a wealth of opportunities in research, pharmaceutical and clinical contexts, but for those who are in the high performance computing space, this particular market is bursting with a different array of opportunities. From specialty clusters dedicated exclusively to crunching the overwhelming amounts of data coming of sequencers (not to mention the storage might to keep it all in check) the biosciences industry is a prime target for vendors of all stripes.

Interestingly, with the rise of cloud computing and on-demand resources, investment in hardware for many companies isn’t always the first option. According to Tom Coull, Senior Vice President at Penguin Computing, a large number of DNA-driven companies are finding on-demand HPC a perfect fit, especially since their demands for high throughput computing are large but generally sporadic.

Providers of on-demand high performance computing that have an eye on this particular industry (Penguin Computing, Cycle Computing, and SGI in particular) have little elbow room in this tight market to garner valuable life sciences business. In addition to competing with public cloud resources like Amazon EC2, not to mention competition from traditional modes of computing (buying your own cluster) such services have to run a tight ship to keep their own hardware investments churning at peak capacity.

This issue of peak capacity is critical for both users of on-demand HPC and for the providers themselves. Naturally a provider like Penguin wants to make sure their investment is being fully utilized and they’re retuning a profit on the core hours spent. On the flip side, however, life sciences companies want to make sure that they’re balancing time-to-market concerns with core competency arguments.

To be more specific about this balance of issues, we spoke to Abe Lietz who heads IT for a major life sciences firm, Life Technologies. This global company provides a range of solutions for customers in the industry, from biological products for research to the instrumentation to back next-generation DNA sequencing efforts. In short, as Abe told us, “our core competency is about keeping pace with a rapidly changing industry; things change quickly and it’s not part of our goal to put the extreme time and resources into running our own IT the right way.”

Life Technologies is using Penguin Computing’s HPC on-demand (POD) offering to back a web interface into one of its most popular software packages for gene sequence analysis, Bioscope. While on the surface this might sound like a simple enough offering, the complexity of Bioscope and the fact that it is residing on collocated servers in Salt Lake City goes deeper than one might imagine.

Users log in through solidbioscope.com and are able to use the pay as you go model to analyze genomic data, using Penguin’s storage and resources exclusively. Penguin’s Coull noted that the pricing is roughly equivalent to what you might get with a similar cloud provider but unlike with a public cloud, users are able to know exactly where their data is at any given moment—an important issue for the HIPPA compliance-aware.

Coull also noted that for genomics researchers considering this from a purely cost-driven basis, if you’ve built and maintained a cluster based on peak requirements and you’re not using it at 35 percent on a full-time basis, you’re better off using an on-demand resource provider.  During our phone interview he was watching POD activity from his screen and noted that of the applications that were running at any given moment, a good estimation is that 50% of users have replaced their in-house systems electing to use POD exclusively while the other half were the sporadic users who make up a nice portion of the life sciences on-demand market due to the spotty need for big computation.

On a side note, Coull says that Penguin expects 4-fold growth over the next year for their POD service with the build-out of two AMD and Intel partnerships for new POD centers. Although he didn’t comment what percent of the business was life sciences driven, he noted this market was “significant” and that they’d seen a surprising uptick from academic institutions that needed extra resources.

Coull noted as well that their software stack has been tweaked by users to be able to bridge over to other cloud computing options, including Amazon’s S3, due to the fact that it seems to be one of the most popular storage options for this type of user.

It’s worth noting, by the way, that this was not Life Technology’s first interaction with Penguin Computing. The company had been providing hardware services to support Life Technologies’ proprietary software since 2007.

According to Penguin, this is a side effect of having a solid reputation with customers who are software-driven—if their in-house systems perform well and they like the service and support, it’s a natural fit for users to consider using their remote resources if they fit the bill.

Coull noted that some users are getting creative about using the POD service. For instance, during his occasional glances at the real-time reports from the POD interface, there were Life Technologies training sessions going on in real time, which gave users the chance to work in a hands-on fashion with the software.

VP of Life Technologies, Jeff Cafferty also weighed on this, noting that beyond sheer training, potential customers interested in evaluating analytics options (since there are many—and many are non-proprietary) could hop on the POD-driven solidbioscope.com resource and compare results, including mappability and other specific factors.

In addition to extolling the benefits of the cloud beyond just analytics, Cafferty told us, “We are in the post-human genome sequencing project phase of life sciences” what’s happened in this last decade is that companies like ours have been developing evermore high throughput technologies for sequencing DNA and furthermore the cost of sequencing has gone down tremendously. What this means is that there’s been a huge explosion in the amount of sequence information available for life sciences researchers.

This is a fact that is driving the next big buzzphrase after cloud computing—“big data”—into every marketing message, particularly on the storage end, for obvious reasons. While the massive data end of the equation is a major factor that is causing genomics researchers to consider looking beyond physical hardware, the computational requirements are nothing to sneeze at either.

Caffrey put this in context, noting that to sequence a human genome researchers are dealing with something that is 3 billion base pairs long. Their instrumentation for next generation sequencing creates what are called “short reads” of DNA and in one genome, this creates billions such reads that then need to be mapped back to a reference genome.

He also elaborated on a topic that is growing nearer and dearer to storage, compute, software and cloud vendors alike: “Life sciences researchers have traditionally functioned on an experimental model that involved a great deal of time generating data (biological samples can be rare or hard to extra information from) and relatively small amounts of time analyzing it, in part because there just wasn’t very much of it. In sequencing in particular this paradigm has been flipped—we’re now generating a tremendous amount of data in a very short period of time and thus the length now is because of the mining, management, comparing and analysis of all that data.”

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