To Build or to Buy Time: That is the Question

By Nicole Hemsoth

August 11, 2010

Generally, when one thinks about the vast array of small to medium-sized businesses deploying a cloud to handle peak loads or even mission-critical operations, the idea that such a business might be designing the future of missile defense strategy isn’t the first thing that comes to mind. After all, SMB concerns have historically not had much in common with those of large-scale enterprise and HPC users. The cloud is creating a convergence of these spaces and smaller businesses that were once unable to gain a foothold in their market due to high infrastructure start-up costs are now a competitive force due to the availablity of shared or rented infrastructure and a virtualized environment. This convergence creates new possibilites but can complicate end user decision-making about ideal options for mission-critical workloads.

Analytical Services, Inc. (ASI), a U.S. Department of Defense Missile Defense Agency subcontractor recently used Sabalcore’s high performance computing (HPC) on-demand services to design aerospike nozzles for use in missile systems. These developments in aerospikes represent a significant improvement from a design perspective but required enormous compute power to bring them to market. Orlando, Florida-based Sabalcore, a relatively small company, was able to provide the Linux cluster required for the task while allowing ASI to eliminate the overhead of investing in their own hardware to meet the design challenges.

According to Joseph D. Sims, Technical Director of Engineering at ASI, “Computational fluid dynamics (CFD) is critical to our design efforts, which means we cannot complete that design without Sabalcore’s Linux cluster. We, like many small businesses, cannot afford the luxury of buying and maintaining our own.” Sims went on to note that as with other design projects requiring high levels of compute power, ASI’s goals meshed well with the Linux clusters on-demand because “we could not hope to support our design efforts with CFD running on a serial computer (e.g., a desktop or workstation).” ASI’s Technical Director stated that following comparisons of buying and maintaining a cluster versus buying the access to the Linux cluster, there was “a huge cost savings” that could be realized.

Dividing Line on Building Versus Buying Time?

Gauging from conversations with vendors and end users alike, it is this investment avoidance, coupled with the on-demand nature that makes HPC on-demand services like those offered by Sabalcore and a handful of others (Cycle, Penguin, rSystems, SGI, etc.) attractive. This, along with the fact that HPC on-demand providers tout their high level of personalized support makes this an attractive option—sometimes more attractive than a public cloud.

One has to wonder where the dividing line is for those making decisions about buying versus renting time via an on-demand service—all coupled with the added possibility of the cloud. For some it is about price, for others, it’s rooted in performance goals, for others security. There are no hard and fast rules of thumb for end users but it might seem more attractive to take someone else’s cluster for a guided spin versus tweak applications to suit a cloud that might not yet have proved itself as a viable option.

So where does the cloud fall short when it’s decision time for end users to make the crucial build or buy decision in a case like ASI’s? In an email interview, co-founder of Sabalcore, John Van Workum was asked if there was any tension or cause for competitive concern between HPC on demand services like his company’s and a service like the newly-announced Cluster Compute Instances from Amazon, which are aimed at the same market—those who require HPC-like capacity to run complex or particularly resource-hungry applications. Van Workum stated:

Providers like Amazon have the advantage when it comes to sheer size. They have vast web, storage, and compute resources that a user can tap into. But, HPC boils down to performance. How fast will my application run and how much will it cost are the two biggest questions. It will be interesting to see if Amazon’s new HPC instances will be popular with the HPC user base community.

Because of Amazon’s virtualization layers, the end user is not getting near 100% of the bare-metal performance from a server. Their upgraded 10GigE network for the  HPC instances is an improvement over previous offerings, but DDR and QDR InfiniBand are proven faster. Also, I believe Amazon has restrictions in place when it comes to the number of cores an HPC instance can have at any given time.  Sabalcore, on the other-hand, has a purpose built HPC systems with very few restrictions. Of course, customer service and technical support sets us apart from large HPC cloud providers.

HPC On-Demand Versus an HPC Cloud

ASI like many other small to mid-sized enterprises who have occasional spikes in need for HPC resources are faced with the decision between building or buying time. Performing a careful cost analysis of such a decision is difficult and fraught with uncertainty for new users when there is a cloud option available to contend with as well. However, the problem is that many HPC on-demand companies like Sabalcore are taking the cloud approach with their marketing message and might be adding to confusion by muddling the concept of what a cloud is—and is not.

In fact, the very term “cloud” is problematic for a company like Sabalcore since what they’re providing is not really a cloud at all. While they certainly recognize this, companies with essentially the same offerings are putting the word “cloud” on HPC on-demand services, which adds to confusion, especially for new users who are far more concerned with keeping with their research and time-to-market goals than arguing over complex, hotly-debated definitions. In Van Workum’s view;

Cloud is such a broad term and it’s definition has been discussed in detail and I don’t believe it has one, all encompassing, definition.

One could consider us cloud simply because we host services on the internet. But it pretty much ends there. HPC has very little to do with web-based desktop tools, virtual storage, virtual servers, cloud files, and nebulous virtual  environments which are synonymous with “cloud” these days. We are none of those things either. So therefore we avoid using the term “cloud” when describing Sabalcore.

With this in mind, Workum also provided some commentary on those who are offering the same HPC on-demand service and how a company can differentiate itself in the face of new cloud offerings and competitors. While his detailed response is below, it should be noted that he hits on exactly the same core themes that have emerged in recent conversations with companies like Penguin about its P.O.D service, rSystems, and a host of others. On Sabalcore and the landscape for HPC on-demand companies Workum noted:

HPC users that are familiar with traditional Linux cluster environments will find our environment very similar. We have a very low learning curve. The end user is not hassled by managing instances, insufficient web interfaces, or third party products. Often, a customer is running their job in a matter of hours after logging in for the first time.

Not every application fits nicely into an HPC environment. We provide each new customer with adequate evaluation time and hand holding assistance should they require it.

Our engineers have experience working with hundreds of different applications and can usually make the required modifications in a matter of hours. It is important to note that we almost always adjust the customer’s computing environment in such a way that the changes are as transparent as possible to the customer. It is very uncommon for us to require that the customer make more than superficial changes to their applications or data. But when that does occur, we have the experience to either do it for them or to guide them with the modifications.

Experience and exceptional technical and customer support define us. Sabalcore is a 100% HPC as a service provider and has been since its inception in 2000. We focus solely on our service rather than also selling hardware unlike some recent HPC cloud participants.

In his line of thinking, the cloud is hindered by its lack of support, which is part of the reason why some companies opt for HPC on-demand services versus a public cloud like Amazon’s EC2—even with its new HPC-geared instance type.

Sabalcore has experienced solid growth in the last four years, in part because it has been able to appeal to those who rejected the cloud as an option and who have certainly rejected the option of investing in their own clusters for more obvious reasons. As the cloud, especially public cloud offerings, are developed to be more in tune with the needs of companies like ASI, however, the cloud might push HPC on-demand providers to emphasize even more fervently the support and personalization aspects that go hand-in-hand with their alternative.

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!

Geospatial Data Research Leverages GPUs

August 17, 2017

MapD Technologies, the GPU-accelerated database specialist, said it is working with university researchers on leveraging graphics processors to advance geospatial analytics. The San Francisco-based company is collabor Read more…

By George Leopold

Intel, NERSC and University Partners Launch New Big Data Center

August 17, 2017

A collaboration between the Department of Energy’s National Energy Research Scientific Computing Center (NERSC), Intel and five Intel Parallel Computing Centers (IPCCs) has resulted in a new Big Data Center (BDC) that Read more…

By Linda Barney

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 week the cloud giant released deeplearn.js as part of that in Read more…

By John Russell

HPE Extreme Performance Solutions

Leveraging Deep Learning for Fraud Detection

Advancements in computing technologies and the expanding use of e-commerce platforms have dramatically increased the risk of fraud for financial services companies and their customers. Read more…

Spoiler Alert: Glimpse Next Week’s Solar Eclipse Via Simulation from TACC, SDSC, and NASA

August 17, 2017

Can’t wait to see next week’s solar eclipse? You can at least catch glimpses of what scientists expect it will look like. A team from Predictive Science Inc. (PSI), based in San Diego, working with Stampede2 at the Read more…

By John Russell

Microsoft Bolsters Azure With Cloud HPC Deal

August 15, 2017

Microsoft has acquired cloud computing software vendor Cycle Computing in a move designed to bring orchestration tools along with high-end computing access capabilities to the cloud. Terms of the acquisition were not disclosed. Read more…

By George Leopold

HPE Ships Supercomputer to Space Station, Final Destination Mars

August 14, 2017

With a manned mission to Mars on the horizon, the demand for space-based supercomputing is at hand. Today HPE and NASA sent the first off-the-shelf HPC system i Read more…

By Tiffany Trader

AMD EPYC Video Takes Aim at Intel’s Broadwell

August 14, 2017

Let the benchmarking begin. Last week, AMD posted a YouTube video in which one of its EPYC-based systems outperformed a ‘comparable’ Intel Broadwell-based s Read more…

By John Russell

Deep Learning Thrives in Cancer Moonshot

August 8, 2017

The U.S. War on Cancer, certainly a worthy cause, is a collection of programs stretching back more than 40 years and abiding under many banners. The latest is t Read more…

By John Russell

IBM Raises the Bar for Distributed Deep Learning

August 8, 2017

IBM is announcing today an enhancement to its PowerAI software platform aimed at facilitating the practical scaling of AI models on today’s fastest GPUs. Scal Read more…

By Tiffany Trader

IBM Storage Breakthrough Paves Way for 330TB Tape Cartridges

August 3, 2017

IBM announced yesterday a new record for magnetic tape storage that it says will keep tape storage density on a Moore's law-like path far into the next decade. Read more…

By Tiffany Trader

AMD Stuffs a Petaflops of Machine Intelligence into 20-Node Rack

August 1, 2017

With its Radeon “Vega” Instinct datacenter GPUs and EPYC “Naples” server chips entering the market this summer, AMD has positioned itself for a two-head Read more…

By Tiffany Trader

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

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a 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

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. Just how close real-wo 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

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

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 a Read more…

By Tiffany Trader

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 cam Read more…

By John Russell

Leading Solution Providers

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of Read more…

By Alex Woodie

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

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

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Engine (GCE) job. Sutherland ran the massive mathematics workload on 220,000 GCE cores using preemptible virtual machine instances. Read more…

By Tiffany Trader

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

Messina Update: The US Path to Exascale in 16 Slides

April 26, 2017

Paul Messina, director of the U.S. Exascale Computing Project, provided a wide-ranging review of ECP’s evolving plans last week at the HPC User Forum. Read more…

By John Russell

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