HPCwire: Cluster Adoption Phases

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March 17, 2006

Cluster Adoption Phases

by Rick Friedman

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If you're reading this article, the idea that cluster adoption is increasing will be of no surprise to you. The idea of linking low cost, commodity computers together, Rick Friedman, Director of Marketing, Scali Inc. and leveraging a low cost operating system, has been around for a number of years now. The ability to cost-effectively leverage high performance computing changes the way people do their jobs and changes the way leaders plan their projects. The use of these types of systems has grown from small projects inside of labs, universities, and basements into full-fledged validated enterprise tools. Scali, a company making cluster management and MPI library software tools, has been involved in Linux-based cluster computing since 1997. Over the past nine years, we've noticed a pattern in how clusters are brought into organizations, particularly commercial organizations, and how their usage and impact changes over time. This article will discuss those various phases and how laying the proper groundwork can significantly increase the likelihood of success when transitioning to the next phase.

One of the interesting aspects of seeing how cluster adoption has spread, particularly within a single organization over time, is how many users claim that if they knew then what they know now, they would have done things differently. In general, many users comment that they tend to focus very heavily on the processor count and performance aspects of their initial systems, but very quickly found that things like management, expansion, networks, operating systems, and applications ended up being the key elements that affected actual user success.

As clusters become more mainstream, we see that the challenges of deploying, managing and maintaining these environments have become increasingly complex and require comprehensive tools, such as Scali Manage, to provide assistance in making these clusters as efficient as possible.

Phase One: Project/Evaluation

Typically, we see that most commercial organizations bring their initial clusters in as single purpose clusters. These clusters are usually focused on specific tasks or specific projects. They consist of homogenous hardware and operating environments that are not expected to change much from initial specifications.

These clusters are often brought into the organization by the project teams themselves and are not directly tied to the general IT environment. This implies that the support and ongoing maintenance is also a responsibility of the project team, with all the benefits and risks that control offers them. They are typically deployed to provide performance and capabilities to teams that have specific project goals that need to be met. They usually have a single or limited number of applications and a limited user base. The primary criteria of success for these types of clusters are that they get up and running quickly, providing benefits to the project completion.

From a management perspective, these users need solutions that can deploy their clusters quickly, leveraging best practices to ensure success. From an ongoing perspective, these environments need an easy-to-use solution for keeping their systems running and for handling any updates to the application environment, while providing basic feedback on the efficiency and effectiveness of the cluster.

Phase Two: Distribution

Once projects experience some success with clusters, that success breeds additional interest in the use of the cluster -- and of clusters in general -- by other projects within the organization.

At this point, the initial cluster environment starts to grow in all dimensions from its original design and purpose. As this occurs, the number of nodes increases, the mix of hardware changes from a purely homogenous to a heterogeneous environment, the number of applications increases and the number of users expands.

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