CLUSTER COMPUTING

Parallel computing has seen many changes since the days of the highly expensive and proprietary supercomputers. Changes and improvements in performance have also been seen in the area of mainframe computing for many environments. But these compute environments may not be the most cost effective and flexible solution for a problem.

Over the past decade, cluster technologies have been developed that allow multiple low cost computers to work in a coordinated fashion to process applications. The economics, performance and flexibility of compute clusters makes cluster computing an attractive alternative to centralized computing models and the attendant to cost, inflexibility, and scalability issues inherent to these models.

Many enterprises are now looking at clusters of high-performance, low cost computers to provide increased application performance, high availability, and ease of scaling within the data center. Interest in and deployment of computer clusters has largely been driven by the increase in the performance of off-the-shelf commodity computers, high-speed, low-latency network switches and the maturity of the software components.

Application performance continues to be of significant concern for various entities including governments, military, education, scientific and now enterprise organizations. This document provides a review of cluster computing, the various types of clusters and their associated applications. This document is a high-level informational document; it does not provide details about various cluster implementations and applications.

CLUSTER COMPUTING

Cluster computing is best characterized as the integration of a number of off-the-shelf commodity computers and resources integrated through hardware, networks, and software to behave as a single computer. Initially, the terms cluster computing and high performance computing were viewed as one and the same. However, the technologies available today have redefined the term cluster computing to extend beyond parallel computing to incorporate load-balancing clusters (for example, web clusters) and high availability clusters. Clusters may also be deployed to address load balancing, parallel processing, systems management, and scalability.

Today, clusters are made up of commodity computers usually restricted to a single switch or group of interconnected switches operating at Layer 2 and within a single virtual local-area network (VLAN).Each compute node (computer) may have different characteristics such as single processor or symmetric multiprocessor design, and access to various types of storage devices. The underlying network is a dedicated network made up of high-speed, low-latency switches that may be of a single switch or a hierarchy of multiple switches. A growing range of possibilities exists for a cluster interconnection technology. Different variables will determine the network hardware for the cluster. Price-per-port, bandwidth, latency, and throughput are key variables. The choice of network technology depends on a number of factors, including price, performance, and compatibility with other cluster hardware and system software as well as communication characteristics of the applications that will use the cluster.

Clusters are not commodities in themselves, although they may be based on commodity hardware. A number of decisions need to be made (for example, what type of hardware the nodes run on, which interconnect to use, and which type of switching architecture to build on) before assembling a cluster range. Each decision will affect the others, and some will probably be dictated by the intended use of the cluster. Selecting the right cluster elements involves an understanding of the application and the necessary resources that include, but are not limited to, storage, throughput, latency, and number of nodes.

When considering a cluster implementation, there are some basic questions that can help determine the cluster attributes such that technology options can be evaluated:

Will the application be primarily processing a single dataset?

Will the application be passing data around or will it generate real-time information?

Is the application 32- or 64-bit?

The answers to these questions will influence the type of CPU, memory architecture, storage, cluster interconnect, and cluster network design. Cluster applications are often CPU-bound so that interconnect and storage bandwidth are not limiting factors, although this is not always the case.

CONCLUSION

High-performance cluster computing is enabling a new class of computationally intensive applications that are solving problems that were previously cost prohibitive for many enterprises. The use of commodity computers collaborating to resolve highly complex, computationally intensive tasks has broad application across several industry verticals such as chemistry or biology, quantum physics, petroleum exploration, crash test simulation, CG rendering, and financial risk analysis. However, cluster computing pushes the limits of server architectures, computing, and network performance.

Due to the economics of cluster computing and the flexibility and high performance offered, cluster computing has made its way into the mainstream enterprise data centers using clusters of various sizes.

As clusters become more popular and more pervasive, careful consideration of the application requirements and what that translates to in terms of network characteristics becomes critical to the design and delivery of an optimal and reliable performing solution.

Knowledge of how the application uses the cluster nodes and how the characteristics of the application impact and are impacted by the underlying network is critically important. As critical as the selection of the cluster nodes and operating system, so too are the selection of the node interconnects and underlying cluster network switching technologies.

A scalable and modular networking solution is critical, not only to provide incremental connectivity but also to provide incremental bandwidth options as the cluster grows. The ability to use advanced technologies within the same networking platform, such as 10 Gigabit Ethernet, provides new connectivity options, increases bandwidth, whilst providing investment protection.

The technologies associated with cluster computing, including host protocol stack-processing and interconnect technologies, are rapidly evolving to meet the demands of current, new, and emerging applications. Much progress has been made in the development of low-latency switches, protocols, and standards that efficiently and effectively use network hardware components.