Will Public Clouds Ever Be Suitable for HPC?

By Nicole Hemsoth

June 27, 2010

For those who believe HPC is on the cusp of a revolution in terms of access and usability — especially for non-technical researchers — there are big, ever-lingering questions about how to make a general purpose cloud fit for HPC workloads. The end of most of these discussions comes when the topic of performance emerges because, let’s face it, there are not many appealing features to a large public cloud like Amazon for researchers with very specific compute demands. Having the power on demand is nice, but if the performance is the price to pay then it renders the idea useless.

If it’s a large public cloud we’re talking about — one that is most often used for scientific and large-scale enterprise computing — chances are it’s Amazon’s EC2. There are other public cloud providers, of course, but for the sake of argument, Amazon’s Elastic Compute offering is the poster child for cloud computing and often the first choice — if only because it has been around the longest. From startup cloud providers to big players, Amazon symbolizes the possibilities of cloud for everyone while it epitomizes the problems inherent to the cloud concept as it pertains to HPC.

Not to pick on EC2 here since there are several other public cloud providers to choose from, but it seems that most of the researchers who have made broader use of the public cloud, from large institutions down to individuals working on complex problems, have made this their premium choice. Will it stay this way forever? Probably not, especially since Microsoft and others are chomping at the bit for their share of the cloud movement with a direct focus on the HPC market. In fact, as it becomes clear that there might be benefits for scientific computing in the cloud at the same time that it is becoming glaringly obvious that the cloud-for-everyone will not apply for this specialized subset of users.

The Stagnant Public Cloud

It’s difficult to foster hope for greater use of the public cloud when it is not modified to any significant degree since its standard resources are providing enough to keep this end of the Amazon empire running.

Dr. Dieter Kranzlmuller in the German magazine Computer Woche suggested there are only very limited uses for the public cloud in HPC. “The effective use of a cloud is dependent on the applications. The cloud can be used appropriately when dealing with linear processes and independent, relatively small data volumes. For applications with larger storage requirements or closely coupled parallel processes with high I/O requirements, clouds are often useless.”

Way back in 2008, Edward Walker published a study entitled, “Benchmarking Amazon’s EC2 for High-Performance Scientific Computing” that provided results based on macro and micro comparison points to form a solid theory about the performance gap in the public cloud, even with equivalent processing power. This of course boils down to the MPI and interconnects issue — just as it still does today. The mere act of virtualization renders the cloud almost useless to many scientific HPC clusters, in other words.

According to Walker in his older yet still just-as-relevant report based on the benchmarking study, “the delivery of HPC performance with commercial cloud computing services such as Amazon EC2 is not yet mature…a performance gap exists between performing HPC computations on a traditional scientific cluster and on an EC2 provisioned scientific cluster. This performance gap is seen not only in the MPI performance of distributed-memory parallel programs but also in the single compute node OpenMP performance for shared-memory parallel programs. For cloud computing to be a viable alternative for the computational science community, vendors will need to upgrade their service offerings, especially in the area of high-performance network provisioning to cater to this unique class of users.”

Since the vendor in question here — Amazon — has not upgraded its service offerings, the time has come for others to pick up the slack and create specialized cloud environments that are in tune with the performance demands of HPC users if the cloud vision is to be realized for its cost benefits.

None of this portends well for strict HPC applications in a large public cloud offering like Amazon’s. EC2 and other public clouds designed to run everything from big commercial websites to outsourced large batch jobs might seem appealing on a cursory glance to many, but as William Fellows, analyst at the 451 Group, stated, “The main problem with running HPC tasks on conventional clouds is that conventional clouds are geared toward supporting general-purposes applications and services — short transactional workloads such as web applications and database tasks…theses are heavily dependent on the need to be processed serially and within an infrastructure geared toward supporting inter-process communication.”

In other words, the public cloud is designed for an admirably long list of workloads but HPC in general — not so much. But really, when you get right down to it, why should EC2 change its style to fit the needs of scientific users in the first place when it is doing just fine serving the needs of mainstream users? After all, other companies who already have some degree of HPC supremacy are making headway as they are better positioned to tailor their approach to coaxing researchers on to their clouds — in whatever form they’ve devised.

Bridges Across the Performance Chasm

When so many think about the cloud in general, the first thought is about large-scale cloud providers like Amazon, but the fact is, there are an increasing number of choices that remove the performance gap caused by virtualization or that have clouds that are tailored to the performance-driven needs of HPC users.

IBM, Microsoft, SGI, Penguin, Cycle and a handful of others that do not work directly to manage their clients’ push to the public cloud via a layer of cloud management software are doing so in part because they’ve realized that there is no broad appeal for true, traditional HPC users to move to EC2. They realize that the environment needs to be customized, that the performance is the most critical factor in gaining converts — and most importantly, that there is no public cloud that can beat the power of a cluster. So in a manner that screams “grid” they are renting specialized clusters that are specifically designed for HPC users.

In an effort to overcome the performance gap yet still provide users with the freedom of owning and managing their own clusters, Penguin On-Demand (POD) and others, including Cycle Computing, are taking the concept of the cloud for HPC and making it more attractive to HPC users by eliminating the virtualization and providing customized servers. This missing layer of virtualization adds some complication to the term “cloud” but it is a logical step for researchers who are attracted to the cost benefits of avoiding the expense of a cluster investment. Since many HPC users have found that large public clouds, most notably Amazon’s EC2, do not offer the service levels they depend on, it is reasonable to predict that there will be a host of new upstarts that seek to bring dedicated servers to researchers in an on-demand fashion versus creating a complex management layer that is tied to the public cloud.

This is not to say that EC2 is not being used with some success, but most often these are jobs are that are not necessarily HPC-like. As Kathy Yelick, director of NERSC, noted in a recent interview about current developments in the Magellan cloud, “there’s a part of the workload in scientific computing that’s well-suited to the cloud, but it’s not the HPC end, it’s really the bulk aggregate serial workload that often comes up in scientific computing, but that is not really the traditional arena of high-performance computing.”

If existing cloud providers with their eyes on the HPC market can better tailor their solutions to meet the broader range of HPC application needs with a distinct focus on performance, it stands to reason that the world of the public cloud will be out of reach to Amazon and other general purpose cloud providers.

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!

Ohio Supercomputing Center Dedicates ‘Owens’ Cluster

March 29, 2017

In a dedication ceremony held earlier today (March 29), officials from Ohio Supercomputing Center (OSC) along with state representatives gathered to celebrate the launch of OSC’s newest cluster: Read more…

By Tiffany Trader

EU Ratchets up the Race to Exascale Computing

March 29, 2017

The race to expand HPC infrastructure, including exascale machines, to advance national and regional interests ratcheted up a notch yesterday with announcement that seven European countries – Read more…

By John Russell

Data-Hungry Algorithms and the Thirst for AI

March 29, 2017

At Tabor Communications’ Leverage Big Data + EnterpriseHPC Summit in Florida last week, esteemed HPC professional Jay Boisseau, chief HPC technology strategist at Dell EMC, engaged the audience with his presentation, “Big Computing, Big Data, Big Trends, Big Results.” Read more…

By Tiffany Trader

Bill Gropp – Pursuing the Next Big Thing at NCSA

March 28, 2017

About eight months ago Bill Gropp was elevated to acting director of the National Center for Supercomputing Applications (NCSA). Read more…

By John Russell

HPE Extreme Performance Solutions

Leveraging the Power of Big Data to Improve Customer Satisfaction & Brand Loyalty

In the dynamic world of retail, retailers must find ways to recognize and effectively respond to shopping behaviors, patterns, and trends in order to succeed. Read more…

UK to Launch Six Major HPC Centers

March 27, 2017

Six high performance computing centers will be formally launched in the U.K. later this week intended to provide wider access to HPC resources to U.K. Read more…

By John Russell

AI in the News: Rao in at Intel, Ng out at Baidu, Nvidia on at Tencent Cloud

March 26, 2017

Just as AI has become the leitmotif of the advanced scale computing market, infusing much of the conversation about HPC in commercial and industrial spheres, it also is impacting high-level management changes in the industry. Read more…

By Doug Black

Scalable Informatics Ceases Operations

March 23, 2017

On the same day we reported on the uncertain future for HPC compiler company PathScale, we are sad to learn that another HPC vendor, Scalable Informatics, is closing its doors. Read more…

By Tiffany Trader

‘Strategies in Biomedical Data Science’ Advances IT-Research Synergies

March 23, 2017

“Strategies in Biomedical Data Science: Driving Force for Innovation” by Jay A. Etchings is both an introductory text and a field guide for anyone working with biomedical data. Read more…

By Tiffany Trader

Data-Hungry Algorithms and the Thirst for AI

March 29, 2017

At Tabor Communications’ Leverage Big Data + EnterpriseHPC Summit in Florida last week, esteemed HPC professional Jay Boisseau, chief HPC technology strategist at Dell EMC, engaged the audience with his presentation, “Big Computing, Big Data, Big Trends, Big Results.” Read more…

By Tiffany Trader

Bill Gropp – Pursuing the Next Big Thing at NCSA

March 28, 2017

About eight months ago Bill Gropp was elevated to acting director of the National Center for Supercomputing Applications (NCSA). Read more…

By John Russell

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

New Japanese Supercomputing Project Targets Exascale

March 14, 2017

Another Japanese supercomputing project was revealed this week, this one from emerging supercomputer maker, ExaScaler Inc., and Keio University. The partners are working on an original supercomputer design with exascale aspirations. Read more…

By Tiffany Trader

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

Leading Solution Providers

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

Enlisting Deep Learning in the War on Cancer

December 7, 2016

Sometime in Q2 2017 the first ‘results’ of the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) will become publicly available according to Rick Stevens. He leads one of three JDACS4C pilot projects pressing deep learning (DL) into service in the War on Cancer. Read more…

By John Russell

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

CPU Benchmarking: Haswell Versus POWER8

June 2, 2015

With OpenPOWER activity ramping up and IBM’s prominent role in the upcoming DOE machines Summit and Sierra, it’s a good time to look at how the IBM POWER CPU stacks up against the x86 Xeon Haswell CPU from Intel. Read more…

By Tiffany Trader

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

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