Cloud Computing Opportunities in HPC
This article is excerpted from “Cloud Opportunities in HPC: Market Taxonomy,” published by InterSect360 Research. The full article was distributed to subscribers of the InterSect360 market advisory service and can also be obtained by contacting email@example.com.
In Life, the Universe, and Everything, the third book of Douglas Adams’ whimsical Hitchhiker fantasy trilogy, cosmic wayfarer Ford Prefect describes how an object, even a large object, could effectively be rendered invisible to the general populace by surrounding it with an “SEP field” that causes would-be observers to avoid recognizing Somebody Else’s Problem. “An SEP,” Ford helpfully explains, “is something we can’t see, or don’t see, or our brain doesn’t let us see, because we think that it’s somebody else’s problem.”
If we were to reinterpret SEP to stand for “Somebody Else’s Processing,” we would be well on the way to a definition of cloud computing.
The term “cloud” comes from the engineering practice of drawing a cloud in a schematic to represent an external resource that the engineer’s design will interact with — a part of the workflow that he or she will assume is working but that is not part of that specific design. For example, a processor designer might draw a cloud to represent a memory system, with arrows indicating the flow of data in and out of the memory cloud. Cloud computing takes this concept to an organizational level; entire sections of IT workflows can now be virtualized into resources that are someone else’s concern.
Cloud computing is therefore a new instantiation of distributed computing. It is built on grid computing concepts and technology and further enabled by Internet technologies for access. Cloud computing is the delivery of some part of an IT workflow — such as computational cycles, data storage, or application hosting — using an Internet-style interface. This definition includes Web-immersed intranets as conduits for accessing private clouds.
Cloud computing is currently driven by business models that attempt to utilize or monetize unused resources. Grid, virtualization, and now cloud technologies have attempted to find and tap idle resources, thus reducing costs or generating revenue. The most interesting difference between cloud computing and earlier forms of distributed computing is that in developing ultra-scale computing centers, organizations such as Google and Amazon incidentally built out significant caches of occasionally idle computing resources that could be made generally available through the Internet. Furthermore these organizations found that they had developed significant skills in constructing and managing these resources, and economies of scale allowed them to purchase incremental equipment at relatively lower prices. The cloud was born as an effort to monetize those skills, economic advantages, and excess capacity.
This is important because from a business model point of view the cloud resources came into existence at no cost, with minimal incremental support requirements. The majority of the costs are born by the core businesses, and therefore, at least initially, customers of the excess capacity do not need to foot the bill for capital expenditures. Costs associated with staff training, facilities, and development are similarly already fully amortized and absorbed by the parent businesses. There is little more appealing than being able to sell something that you get for free.
With such an appealing proposition in play, many other organizations are scrambling to see whether they have an infrastructure — public or private — that can be exploited for gain through cloud computing. However, when significant excess capacity does not exist, or if it cannot be leveraged in a timely or reliable fashion, it is not clear what sustainable business models exist for cloud computing.
High-end, public cloud computing offerings represent a convergence of grid and Internet technologies, potentially enabling workable new business models. Smaller, private clouds are a technical evolution that expands the ease of use and deployment of grids in more organizations.
As cloud computing technologies mature, InterSect360 Research sees several possible business models that could evolve. Although we emphasize High Performance Computing in our analysis, cloud computing transcends HPC, and similar models will exist in non-HPC markets.
Utility Computing Models
Cloud computing provides a methodology for extending utility computing access models. Utility computing is not new; it has been touted for several years as a way for users to manage peaks in demand, extend capabilities, or reduce costs. Traditionally, limitations in network bandwidth, security issues, software licensing models, and repeatability of results have acted as barriers to adoption, and all of these still need to be addressed with cloud.
There are four major variations on the potential utility computing models with cloud:
Cycles On Demand
The cycles-on-demand model is the most basic approach to cloud computing. The cloud supplier provides hardware and basic software environments, and the user provides application software, application data, and any additional middleware required. In this case users are simply buying access to computer processors, which they provision and manage as needed in order to run their applications, after which the resources are “returned” to the cloud provider. Users are charged for the time the resources are in use, plus possibly some overhead costs. The demands are relatively low on the cloud provider, and relatively high on the user in terms of making sure there is effective utility generated by the rented resources.
The storage cloud model complements the cycles-on-demand model both in terms of operational approach — users buy disk space at a cloud providers facility — and in terms of providing a more complete solution for cycles users — a place to put programs and data between job runs. In the storage-on-demand approach the cloud is used:
- As the final (archival) stage in hierarchical storage management schemes (even if it is a two-level hierarchy: local disk and cloud). On the consumer side this is essentially the concept used for PC backup services.
- A file-sharing buffer where users can place data that can be accessed at a later time by other users. This approach is at the heart of photo sharing sites, and arguably with social sites such as Facebook and LinkedIn. This same concept is also used for shared science databases in areas such as genomics and chemistry.
Software as a Service
Software as a service (SaaS) extends the basic cycles-on-demand model by providing application software within the cloud. This model addresses software licensing issues by bundling the software costs within the cloud processing costs. It also addresses software certification and results repeatability issues because the cloud provider controls both the hardware and software environment and can provide specific system images to users.
SaaS also has the advantages for providers of allowing them to sell services along with the software, and to use the cloud as demonstration platform for direct sales of software products. In addition, the user is able to turn much of the system administration task over to the provider. The major drawback to this strategy is that users generally run of a series of software packages as part of their overall R&D workflow, in such case data would need to be moved into and out of the cloud for specific stages of the workflow, or the cloud provider must support an end-to-end process.
Environmental hosting is the use of a service to support virtually all computational tasks, with servers, storage, and software all being maintained by a third party. This concept can include constructs such as platform as a service (PaaS) and infrastructure as a service (IaaS). Arguably environmental hosting in the cloud is an oxymoron, however, it represents the upper end of the utility computing spectrum and a logical destination of cloud strategies. This approach addresses software, result repeatability, and most networking issues by simply providing dedicated resources all in one (logical) place. It addresses many of the technical security issues, but not a consumer organization’s security problem of inserting a third party into the workflow process.
In addition to the models for those who would consume resources through the cloud, there are applications that are made possible by the combination of Internet communications and large computing resources. This is inclusive of the opportunities for organizations to become cloud computing service providers, either externally or internally. In addition, there is the potential for some secondary markets to be enabled by the adoption of cloud technologies.
Restructuring of Internet-Based Service Infrastructures
One of the most interesting aspects of cloud computing is that Internet companies with value-add and expertise in intellectual property or content (as opposed to purchasing, managing, and running computer hardware systems) could move their internal computing architecture to the cloud, while maintaining system management and operating control in-house. With this strategy an organization would move the bulk of its computing to the cloud keeping only what is necessary for communications and cloud management, in doing so they convert internal costs for systems, software, staff, space and power into usage fees in the cloud. Cloud technology and service providers facilitate and accelerate the industry’s evolution towards a network of interrelated specialty companies, as opposed to groups of organizations each performing the same set of infrastructure functions in house. The major issue potentially holding this model back would be cost; i.e., the level of premium users would be willing to pay for a service versus a do-it-yourself solution.
This strategy would replace personal computers with an advanced terminal that connected to a cloud utility that holds all of the user’s data and software. The advantage for users is that they would be relieved of the burden of purchasing, maintaining, and upgrading their personal systems. They would also have professional support for such task as system back-up and system security and would also be able to access their computing environment form any Web-connected device.
This strategy may represent the evolutionary future of the Internet, particularly as more devices become Web-enabled and the relationship between the Web and the personal computer is weakened by competing devices, such as smart phones. The main challenge to this model is overall bandwidth on the Internet. Side effects to such an evolution would replace the role of the operating system with a Web browser and whatever backend environment the cloud supplier chose to provide, also creating a new product class for Web terminals.
InterSect360 Research Analysis
We see cloud computing as part of the logical progression in distributed computing. It is not completely revolutionary, nor is it a panacea that will provide any service that can be imagined. The business models must be considered in terms of cost and control, barriers and benefits.
Of all the cloud business models, InterSect360 Research believes that SaaS has the highest potential for success within HPC. It addresses several of the major dampening factors associated with cloud and provides additional revenue opportunities in the services arena. It also targets industrial users, who would be the most likely to pay a premium for the product, without attempting to develop competing solutions. Furthermore companies can adopting SaaS models in cloud in a phased or tiered way, first proving the concept private clouds before giving themselves over to public or hybrid models. (This same phenomenon persists with private and public grids today.)
Organizations that have experience with the software and in house operations may look to SaaS options for peak load management and capacity extension. However, we believe the greater opportunity is for selling packaged cloud computing, software, and start-up services to companies testing HPC solutions. Our research indicates that there are major start-up barriers to using HPC solutions among small and medium companies. These barriers include finding the expertise for the creation of the organization’s first scalable digital models.
The major barrier for SaaS adoption in HPC is the fragmentation of the applications software sector of the industry. The boutique nature of the opportunity may indicate there is not sufficient volume to merit the ISV’s investment to create and market cloud-enable versions of their applications. Interestingly, in a recursive manner, small SaaS providers could theoretically tap into larger cycles-on-demand cloud providers to supply the computing resources.
Similarly, implementation of environment hosting within current cloud environments for HPC organizations would currently entail significant amounts of effort by the user organization to set up and manage storage and software environments. It would also be limited by software licensing issues for industrial users in particular. Thus market opportunities for this option are very limited at this time. That said, a small organization could conceivably do all its computing in the cloud, keeping all its data on cloud storage system, using only internally developed, open-source, or SaaS software, and trusting in small size as part of a herd to provide security.
Finally, we note that Web-based software services are not new to the market; they currently range from income tax preparation services to on-line gaming companies. SaaS fits into cloud markets based on the concept of work being sent to outside party and results returned, without the sender having knowledge of exactly how those results are generated. For some users, SaaS may inherently make sense. Ultimately the best way to help users adopt HPC applications may be to make them Somebody Else’s Problem.