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 industry updates delivered to you every week!

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that have occurred about once a decade. With this in mind, the ISC Read more…

2024 Winter Classic: Texas Two Step

April 18, 2024

Texas Tech University. Their middle name is ‘tech’, so it’s no surprise that they’ve been fielding not one, but two teams in the last three Winter Classic cluster competitions. Their teams, dubbed Matador and Red Read more…

2024 Winter Classic: The Return of Team Fayetteville

April 18, 2024

Hailing from Fayetteville, NC, Fayetteville State University stayed under the radar in their first Winter Classic competition in 2022. Solid students for sure, but not a lot of HPC experience. All good. They didn’t Read more…

Software Specialist Horizon Quantum to Build First-of-a-Kind Hardware Testbed

April 18, 2024

Horizon Quantum Computing, a Singapore-based quantum software start-up, announced today it would build its own testbed of quantum computers, starting with use of Rigetti’s Novera 9-qubit QPU. The approach by a quantum Read more…

2024 Winter Classic: Meet Team Morehouse

April 17, 2024

Morehouse College? The university is well-known for their long list of illustrious graduates, the rigor of their academics, and the quality of the instruction. They were one of the first schools to sign up for the Winter Read more…

MLCommons Launches New AI Safety Benchmark Initiative

April 16, 2024

MLCommons, organizer of the popular MLPerf benchmarking exercises (training and inference), is starting a new effort to benchmark AI Safety, one of the most pressing needs and hurdles to widespread AI adoption. The sudde Read more…

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that ha Read more…

Software Specialist Horizon Quantum to Build First-of-a-Kind Hardware Testbed

April 18, 2024

Horizon Quantum Computing, a Singapore-based quantum software start-up, announced today it would build its own testbed of quantum computers, starting with use o Read more…

MLCommons Launches New AI Safety Benchmark Initiative

April 16, 2024

MLCommons, organizer of the popular MLPerf benchmarking exercises (training and inference), is starting a new effort to benchmark AI Safety, one of the most pre Read more…

Exciting Updates From Stanford HAI’s Seventh Annual AI Index Report

April 15, 2024

As the AI revolution marches on, it is vital to continually reassess how this technology is reshaping our world. To that end, researchers at Stanford’s Instit Read more…

Intel’s Vision Advantage: Chips Are Available Off-the-Shelf

April 11, 2024

The chip market is facing a crisis: chip development is now concentrated in the hands of the few. A confluence of events this week reminded us how few chips Read more…

The VC View: Quantonation’s Deep Dive into Funding Quantum Start-ups

April 11, 2024

Yesterday Quantonation — which promotes itself as a one-of-a-kind venture capital (VC) company specializing in quantum science and deep physics  — announce Read more…

Nvidia’s GTC Is the New Intel IDF

April 9, 2024

After many years, Nvidia's GPU Technology Conference (GTC) was back in person and has become the conference for those who care about semiconductors and AI. I Read more…

Google Announces Homegrown ARM-based CPUs 

April 9, 2024

Google sprang a surprise at the ongoing Google Next Cloud conference by introducing its own ARM-based CPU called Axion, which will be offered to customers in it Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Leading Solution Providers

Contributors

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Eyes on the Quantum Prize – D-Wave Says its Time is Now

January 30, 2024

Early quantum computing pioneer D-Wave again asserted – that at least for D-Wave – the commercial quantum era has begun. Speaking at its first in-person Ana Read more…

GenAI Having Major Impact on Data Culture, Survey Says

February 21, 2024

While 2023 was the year of GenAI, the adoption rates for GenAI did not match expectations. Most organizations are continuing to invest in GenAI but are yet to Read more…

The GenAI Datacenter Squeeze Is Here

February 1, 2024

The immediate effect of the GenAI GPU Squeeze was to reduce availability, either direct purchase or cloud access, increase cost, and push demand through the roof. A secondary issue has been developing over the last several years. Even though your organization secured several racks... Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire