GIS Applications Take to the Clouds

By Nicole Hemsoth

July 20, 2010

Geographic Information Systems (GIS) applications have been moving into the cloud with increased momentum but like other fields where software drives the business model, the move from complex software to the software as a service cloud model was slow to catch on due to the business of delivering software—not the technological constraints of doing so. This presents a new market for those previously locked out of GIS due to high startup costs and a potential paradigm shift for how this niche segment of the software industry does business from now on. The GIS example is representative not only of how large-scale application areas are tentatively approaching the cloud from a technological and business model standpoint, but how such shifts can begin to have an instant impact on the new user groups enabled by the delivery model.

The diverse field of Geographic Information Systems (GIS) has seen greater demand for its wide array of geospatial technologies, not only because the mainstream internet has allowed for a much richer, more inclusive way to map just about anything that is a noun via a sort of unconscious crowd-sourcing of metadata and geotagging, but because the applications for such data are growing. GIS technologies have traditionally been used in predictable ways in the forestry, civil engineering and development areas, as well as in natural resource exploration and the culling of general population data for use by agencies and organizations of all sizes and purposes. As mapping has become more detailed and the underlying technology behind it more powerful, GIS has been increasingly used in marketing and consumer trend identification—and you can let your imagination take you from there.

Technologically speaking, GIS is continually evolving at the same rapid pace that the internet and satellite imaging technologies are, although the business model for GIS has, until very recently, remained the same. Over the last few months there has been an increasing amount of news from the GIS community as it begins to adapt to the arrival of software as a service (SaaS) model. Major players in the industry like Esri are taking a proactive approach by making highly publicized partnerships with cloud vendors and cloud-enabled supercomputing sites like Rocky Mountain Supercomputing Centers.

Unlike some other areas, GIS has not taken off to the clouds until recently because of what appears to be business concerns versus those revolving around application functionality. Many common GIS applications will function in public cloud environments like EC2 and Microsoft Azure but there were a relatively small handful of GIS software companies, all of whom had been carrying along just fine on their traditional mode of software delivery. It was not until Esri, who just happens to be one of the biggest players in the GIS software industry, took the first highly publicized step to the cloud to make their technology available via an SaaS model.  While this is not to say that some of the large-scale GIS applications won’t experience the typical performance hitch so common for other HPC-type applications in a cloud like EC2 or Azure, this is a tight software industry that has hitherto been resistant to change—and who can blame them, at least from a business standpoint?

As one might imagine, this has traditional GIS software companies up in arms—the model of GIS software delivery is changing and it is becoming clear to many that they either need to catch up with the times and make bold moves like Esri did (they are the big newsmakers on the GIS front in terms of shifting to the SaaS model)

On the user side, however, the move for GIS applications in the cloud and delivered via an SaaS model holds great potential, especially for those who found the barriers for entry to GIS too high in terms of costs to license and then to actually have the compute thrust to run such applications.

But, when it comes to the traditional delivery model of GIS software, the times they are a’ changin’…

GIS on Microsoft’s Azure Cloud

Microsoft Azure seems to be among the favored platforms when it comes to GIS applications in the cloud, particularly for applications with less hefty requirements than what is being crunched at Rocky Mountain Supercomputing Centers in the course of their partnership with GIS software maker Esri. Take for example Microsoft’s case study of GIS software company Esri and its MapIt software that they thought might best empower users if delivered as a service.

Esri has been providing software for GIS since 1969 and is among the leaders in the space, providing its handiwork for government, industry and academia across roughly 300,000 organizations. It recently partnered with Microsoft to expand “the reach of its GIS technology by offering a lightweight solution called MapIt that combines the software plus services to provide spatial analysis and visualization tools to users unfamiliar with GIS. Esri began offering MapIt as a cloud service with the Windows Azure platform” and customers are now able to deploy the software on Azure to store their information in the Microsoft SQL database. As Microsoft reports in its detailed case study of taking GIS to the cloud on Azure, “By lowering the cost and complexity of deploying GIS, Esri is reaching new markets and providing new and enhanced services to its existing customers.”

Microsoft’s push for Azure in the GIS space has been centered on the fact that they are making once complex, specialized software usable by only trained few open to a far wider base. This in part, of course, due to the professed ease of use over the traditional GIS setup. In other words, their point is that by using Azure for a GIS application, one doesn’t necessarily require ArcGIS Server and a throng of system goons to attend to it–a major cost savings and decreased time to get started (sorry system goons).

As Arthur Haddad, Development Lead and Architect at Esri noted of the Azure involvement, “By freeing customers from having to make large hardware, software and staffing investments up front, we’re helping to lower the cost of GIS entry and increase the return on investment.”

GIS Supercomputing in the RMSC Cloud

According to Earl Dodd, Executive Director of Rocky Mountain Supercomputing Centers, “the cloud computing paradigm is the future of GIS…HPC cloud technology has the potential to scale up GIS software and boost its volumetrics to solve geospatial data processing challenges must faster than previously possible.” In line with the goals of RMSC as well, as Dodd detailed at length here, this is also allowing companies in Montana (where the center is based) to take advantage of GIS applications powered by the massive compute crunch factor they can provide.

RMSC recently announced an agreement with Esri to run their ArcGIS 10 software in an HPC cloud environment to “examine the processing capacity of existing models and expand ArcGIS throughput and performance capabilities for advanced geospatial projects.” Many of the simulation and modeling GIS applications require crunch terabytes in real time, a task that RMSC hopes to refine and study via a host of different configurations that can make it possible for ArcGIS 10 to perform most efficiently and with peak performance. This will also make it easier for a company like Esri to determine what their customers are likely to encounter with their applications, thus better preparing to address concerns before they arise.

Dodd also noted that while there are several public cloud alternatives available, most notably Amazon’s EC2 (since there were no Cluster Compute Instances just over a week ago when the story broke) the HPC cloud at RMSC is better tailored to the needs of GIS applications. Dodd noted that RMSC’s cloud “can significantly reduce processing time with expanded model sizes, especially in critical geospatial applications such as 3D modeling, visualization and simulation [that is already] supporting national security, emergency management and policy decision support.” 

The Democratization of GIS

One can easily advocate, as RMSC’s Earl Dodd does at length, that the cloud can enable access to supercomputing might for those who need it most—that is, those who can least afford it. To take that point one step further, what seems most appealing about GIS in the cloud—at least from a bystander perspective—is that the tools for incredibly powerful GIS-based research and development are now going to be more widely available than ever to an increasing number of people. As Microsoft Azure claimed during its case study with Esri’s GIS in the cloud, it removes the complexity and makes the software available as a true service—open and free from the requirement that one be an expert in GIS on the compute side.

Esri’s shedding of the traditional delivery of it’s GIS applications should make quite a point to other leaders in the GIS software industry. However, for the full democratization of the powerful resource opened by larger users of GIS software to take hold, the industry as a whole requires a similar act of reshaping old models of thinking about providing software.

The democratization of GIS is going to require a philosophical shift for GIS software companies—an industry that is dominated by a few very large firms without much room for the smaller guys. This, according to CEO of of GIS firm eSpatial Philip O’Doherty, who recently wrote “How Will GIS Companies Weather the Cloud Computing Storm” in which he asks how companies reliant on the traditional software model are going to adapt to the paradigm shift brought by the SaaS model. He asks, “what does this mean in the world of Geographic Information Systems where change and technical advances have tended to be a bit slower than in many other business software categories” and goes on to note, “we know the potential that GIS and online mapping and analysis can offer to solve complex business problems, but can GIS software and the use of spatial data evolve to meet the needs of a world that consumes its software as a service in the cloud or do we need to rip it all up and start again?” While these are questions that have been asked in many software arenas as the SaaS model was address as an alternative, threat, or combination thereof, but in this case the “rip it all up and start again” model isn’t really an option—and it’s not clear how that could be done to begin with.

eSpatial’s CEO does go on to answer his initial question, saying that “for existing GIS software vendors to successfully provide GIS as a service, they first need to make the obvious significant philosophical leap. They need to stop thinking like software companies and start thinking and acting like service providers.” He is making an argument that for the first time in history, it will be possible for smaller software providers using the SaaS model to break into a once-locked industry and deliver to a new market of GIS consumers in an on-demand fashion without up-front costs. He sees this as being a sign of a revolution larger than the client-server one that took place in the past—and if he’s right, it could mean a whole new world for GIS users and startups.

The same questions that are being posed in the GIS software industry about moving from traditional software delivery models to SaaS are being asked elsewhere. At this point, however, it seems clear that those with software that is being provided in industries that have been around for a long time and that are dominated by a few key software players have to dare each other to “go first” into the cloud. Because once one starts with some success, the entry of the rest of the space into the cloud won’t be far off.

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!

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 2017 with scale-up production for enterprise datacenters and Read more…

By Tiffany Trader

Fine-Tuning Severe Hail Forecasting with Machine Learning

July 20, 2017

Depending on whether you’ve been caught outside during a severe hail storm, the sight of greenish tinted clouds on the horizon may cause serious knots in the pit of your stomach, or at least give you pause. There’s g Read more…

By Sean Thielen

Trinity Supercomputer’s Haswell and KNL Partitions Are Merged

July 19, 2017

Trinity supercomputer’s two partitions – one based on Intel Xeon Haswell processors and the other on Xeon Phi Knights Landing – have been fully integrated are now available for use on classified work in the Nationa Read more…

By HPCwire Staff

Fujitsu Continues HPC, AI Push

July 19, 2017

Summer is well under way, but the so-called summertime slowdown, linked with hot temperatures and longer vacations, does not seem to have impacted Fujitsu's output. The Japanese multinational has made a raft of HPC and A Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

HPE Servers Deliver High Performance Remote Visualization

Whether generating seismic simulations, locating new productive oil reservoirs, or constructing complex models of the earth’s subsurface, energy, oil, and gas (EO&G) is a highly data-driven industry. Read more…

Researchers Use DNA to Store and Retrieve Digital Movie

July 18, 2017

From abacus to pencil and paper to semiconductor chips, the technology of computing has always been an ever-changing target. The human brain is probably the computer we use most (hopefully) and understand least. This mon Read more…

By John Russell

The Exascale FY18 Budget – The Next Step

July 17, 2017

On July 12, 2017, the U.S. federal budget for its Exascale Computing Initiative (ECI) took its next step forward. On that day, the full Appropriations Committee of the House of Representatives voted to accept the recomme Read more…

By Alex R. Larzelere

Summer Reading: IEEE Spectrum’s Chip Hall of Fame

July 17, 2017

Take a trip down memory lane – the Mostek MK4096 4-kilobit DRAM, for instance. Perhaps processors are more to your liking. Remember the Sh-Boom processor (1988), created by Russell Fish and Chuck Moore, and named after Read more…

By John Russell

Women in HPC Luncheon Shines Light on Female-Friendly Hiring Practices

July 13, 2017

The second annual Women in HPC luncheon was held on June 20, 2017, during the International Supercomputing Conference in Frankfurt, Germany. The luncheon provides participants the opportunity to network with industry lea Read more…

By Tiffany Trader

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

Fine-Tuning Severe Hail Forecasting with Machine Learning

July 20, 2017

Depending on whether you’ve been caught outside during a severe hail storm, the sight of greenish tinted clouds on the horizon may cause serious knots in the Read more…

By Sean Thielen

Fujitsu Continues HPC, AI Push

July 19, 2017

Summer is well under way, but the so-called summertime slowdown, linked with hot temperatures and longer vacations, does not seem to have impacted Fujitsu's out Read more…

By Tiffany Trader

Researchers Use DNA to Store and Retrieve Digital Movie

July 18, 2017

From abacus to pencil and paper to semiconductor chips, the technology of computing has always been an ever-changing target. The human brain is probably the com Read more…

By John Russell

The Exascale FY18 Budget – The Next Step

July 17, 2017

On July 12, 2017, the U.S. federal budget for its Exascale Computing Initiative (ECI) took its next step forward. On that day, the full Appropriations Committee Read more…

By Alex R. Larzelere

Women in HPC Luncheon Shines Light on Female-Friendly Hiring Practices

July 13, 2017

The second annual Women in HPC luncheon was held on June 20, 2017, during the International Supercomputing Conference in Frankfurt, Germany. The luncheon provid Read more…

By Tiffany Trader

Satellite Advances, NSF Computation Power Rapid Mapping of Earth’s Surface

July 13, 2017

New satellite technologies have completely changed the game in mapping and geographical data gathering, reducing costs and placing a new emphasis on time series Read more…

By Ken Chiacchia and Tiffany Jolley

Intel Skylake: Xeon Goes from Chip to Platform

July 13, 2017

With yesterday’s New York unveiling of the new “Skylake” Xeon Scalable processors, Intel made multiple runs at multiple competitive threats and strategic Read more…

By Doug Black

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference 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. Just how close real-wo 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 a 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

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

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

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

Facebook Open Sources Caffe2; Nvidia, Intel Rush to Optimize

April 18, 2017

From its F8 developer conference in San Jose, Calif., today, Facebook announced Caffe2, a new open-source, cross-platform framework for deep learning. Caffe2 is the successor to Caffe, the deep learning framework developed by Berkeley AI Research and community contributors. Read more…

By Tiffany Trader

Leading Solution Providers

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

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

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

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

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

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

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