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!

Long Flights to Cluster Fights: Meet the Asian Student Cluster Teams

November 22, 2017

Five teams from Asia traveled thousands of miles to compete at the SC17 Student Cluster Competition in Denver. Our cameras were there to meet ‘em, greet ‘em, and grill ‘em about their clusters and how they’re doi Read more…

By Dan Olds

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 question. The latest geo-region to throw its hat in the quantum co 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, workshop Read more…

By Andrew Jones

HPE Extreme Performance Solutions

HPE Wins “Best HPC Server” for the Apollo 6000 Gen10 System

Hewlett Packard Enterprise (HPE) was nominated for 14 HPCwire Readers’ and Editors’ Choice Awards—including “Best High Performance Computing (HPC) Server Product or Technology” and “Top Supercomputing Achievement.” The HPE Apollo 6000 Gen10 was named “Best HPC Server” of 2017. Read more…

Turnaround Complete, HPE’s Whitman Departs

November 22, 2017

Having turned around the aircraft carrier the Silicon Valley icon had become, Meg Whitman is leaving the helm of a restructured Hewlett Packard. Her successor, technologist Antonio Neri will now guide what Whitman assert Read more…

By George Leopold

Long Flights to Cluster Fights: Meet the Asian Student Cluster Teams

November 22, 2017

Five teams from Asia traveled thousands of miles to compete at the SC17 Student Cluster Competition in Denver. Our cameras were there to meet ‘em, greet ‘em Read more…

By Dan Olds

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 Read more…

By Andrew Jones

SC Bids Farewell to Denver, Heads to Dallas for 30th Anniversary

November 17, 2017

After a jam-packed four-day expo and intensive six-day technical program, SC17 has wrapped up another successful event that brought together nearly 13,000 visit Read more…

By Tiffany Trader

SC17 Keynote – HPC Powers SKA Efforts to Peer Deep into the Cosmos

November 17, 2017

This week’s SC17 keynote – Life, the Universe and Computing: The Story of the SKA Telescope – was a powerful pitch for the potential of Big Science projects that also showcased the foundational role of high performance computing in modern science. It was also visually stunning. Read more…

By John Russell

How Cities Use HPC at the Edge to Get Smarter

November 17, 2017

Cities are sensoring up, collecting vast troves of data that they’re running through predictive models and using the insights to solve problems that, in some Read more…

By Doug Black

Student Cluster LINPACK Record Shattered! More LINs Packed Than Ever before!

November 16, 2017

Nanyang Technological University, the pride of Singapore, utterly destroyed the Student Cluster Competition LINPACK record by posting a score of 51.77 TFlop/s a Read more…

By Dan Olds

Hyperion Market Update: ‘Decent’ Growth Led by HPE; AI Transparency a Risk Issue

November 15, 2017

The HPC market update from Hyperion Research (formerly IDC) at the annual SC conference is a business and social “must,” and this year’s presentation at S Read more…

By Doug Black

Nvidia Focuses Its Cloud Containers on HPC Applications

November 14, 2017

Having migrated its top-of-the-line datacenter GPU to the largest cloud vendors, Nvidia is touting its Volta architecture for a range of scientific computing ta Read more…

By George Leopold

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

NERSC Scales Scientific Deep Learning to 15 Petaflops

August 28, 2017

A collaborative effort between Intel, NERSC and Stanford has delivered the first 15-petaflops deep learning software running on HPC platforms and is, according Read more…

By Rob Farber

Oracle Layoffs Reportedly Hit SPARC and Solaris Hard

September 7, 2017

Oracle’s latest layoffs have many wondering if this is the end of the line for the SPARC processor and Solaris OS development. As reported by multiple sources Read more…

By John Russell

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

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 w 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

Amazon Debuts New AMD-based GPU Instances for Graphics Acceleration

September 12, 2017

Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The Read more…

By John Russell

Leading Solution Providers

SC17 Booth Video Tours

EU Funds 20 Million Euro ARM+FPGA Exascale Project

September 7, 2017

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development. Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work... Read more…

By Tiffany Trader

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

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

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

Intel Launches Software Tools to Ease FPGA Programming

September 5, 2017

Field Programmable Gate Arrays (FPGAs) have a reputation for being difficult to program, requiring expertise in specialty languages, like Verilog or VHDL. Easin Read more…

By Tiffany Trader

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

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

IBM Advances Web-based Quantum Programming

September 5, 2017

IBM Research is pairing its Jupyter-based Data Science Experience notebook environment with its cloud-based quantum computer, IBM Q, in hopes of encouraging a new class of entrepreneurial user to solve intractable problems that even exceed the capabilities of the best AI systems. Read more…

By Alex Woodie

Share This