Hardware Systems: Processor and Board Alternatives Afshin Attarzadeh INFOTECH, Universität Stuttgart,
[email protected] Abstract: Nowadays parallel computing has a great influence in our daily life. Weather forecast, air control, modeling nuclear experiments instead of actually performing it and lots of other issues are directly related to parallel computing concept. Clusters in the issue of parallelism, are more commonly used today. The issue of clusters, like other concepts in parallelism, is a system issue which involves with software and hardware and their relation to each other. In this paper the hardware part is considered mostly. Introduction – What is cluster computing? As Pfister mentions in his book [1], there are three ways to improve performance: − Work harder − Work smarter − Get help To work harder is just like using faster hardware. This means using faster processors, faster and higher capacity of memory storage and peripheral devices with higher capabilities. Working smarter is when things are done more efficiently and this is due to use of efficient and faster algorithms and techniques. The last aspect deals with parallel processing. Clusters could be a good solution in utilizing all those three aspects of performance improvement with a reasonable expense! Clusters are so flexible that commodity components could be used in their hardware structure. Their flexibility allows designers in developing high performance parallel algorithms. Clusters could be easily configured and more over they are scalable. This means they can easily follow the technology advances in both hardware and software aspects. According to Buyya[2] the most common scalable parallel computer architectures could be classified as follows: • Massively Parallel Processors (MPP) • Symmetric Multiprocessors (SMP) • Cache-Coherent Nonuniform Memory Access (CC-NUMA) • Distributed Systems • Clusters 2 Afshin Attarzadeh Clusters – Definition and Architecture There are many different definitions on clusters.