Grid computing is an emerging computing model that distributes processing across a parallel infrastructure. Throughput is increased by networking many heterogeneous resources across administrative boundaries to model a virtual computer architecture. For a computing problem to benefit from a grid, it must require either large amounts of computation time or large amounts of data, and it must be reducible to parallel processes that do not require intensive inter-communication. Distributed Potential provides remote on-demand computational capacity.

 

The Distributed Potential platform is data-driven, which means that no human interaction is needed to provision a new account to the platform.

Distributed Potential "virtualizes" the resources beyond the limits of one physical server. Distributed Potential's grid computing system offers a model for solving massive computational problems by making effective use of resources (CPU cycles and/or disk storage) of a large numbers of virtual servers.

A Grid environment is created to address resource needs. The use of that resource(s) (eg. CPU cycles, disk storage, data, software programs, peripherals) is usually characterized by its availability outside of the context of the local administrative domain. This 'external provisioning' approach entails creating a new administrative domain referred to as a Virtual Organization (VO) with a distinct and separate set of administrative policies (home administration policies plus external resource administrative policies equals the VO (aka your Grid) administrative policies). The context for a Grid 'job execution' is distinguished by the requirements created when operating outside of the home administrative context. Grid technology (aka. middleware) is employed to facilitate formalizing and complying with the Grid context associated with your application execution.

Customer account changes (to add new resources or change settings) are propagated immediately to every server in the cluster. This is different from typical shared hosting architectures that usually require changes to a configuration file that becomes live after the server is rebooted during off hours, or are pushed on a cyclic basis every few hours.

Technical Benefits

• Instant Provisioning
  Distributed Potential  enables you to increase or decrease capacity within minutes, not hours or days. You can commission one, hundreds or even thousands of server instances simultaneously. Of course, because this is all controlled with web service APIs, your application can automatically scale itself up and down depending on its needs.
  
  
• Completely Controlled
  You have complete control of your instances. You have root access to each one, and you can interact with them as you would any machine. Each instance predictably provides the equivalent of a system with a 1.7Ghz Xeon CPU, 1.75GB of RAM, 160GB of local disk, and 250Mb/s of network bandwidth.
  
  
• Reliable
  Distributed Potential offers a highly reliable environment where replacement instances can be rapidly and reliably commissioned.
  
  
• Secure
  Distributed Potential provides web service interfaces to control network security. You define groups of instances and their desired accessibility.