Chapter 2 Computer Clusters Lecture 2.1 Overview

Outline Cluster definition and significance Cluster development trend Cluster family classification Analysis of the Top 500 Supercomputers

Definition and Significance Definition – A Collection of interconnected stand-alone computer which can work together collectively and cooperatively as a single integrated computer resource pool – Clustering explores massive parallelism at the job level and achieves high availability though stand- alone operations

Significance – Of the top 500 supercomputers reported in 2010, 85% were computer clusters or MPPs built with homogeneous nodes. – Computer clusters have laid the foundation for today’s supercomputers, computational grids and Internet clouds build over data centers

Cluster Development Trends Computer clustering started with the linking of large mainframe computers such as the IBM Sysplex and the SCI Origin Subsequently, the clustering trend moved toward the networking of many minicomputers, such as Dec’s VMS cluster. In the early 1990s, the next move was to build UNIX- based workstation clusters represented by the Berkeley NOW (network of workstations) and IBM SP2 AIX- based server cluster Beyond 2000, we see the trend moving to the clustering x86 PC engines.

Milestone Cluster Systems – Clustering has been a hot research challenge in computer architecture. Fast communication, job scheduling, SSI HA – The following tables lists some milestone cluster research projects and commercial cluster products, each of which has contributed some unique features.

Cluster Family Classification Based on application demand, computer clusters are divided into three classes: – Computer Clusters – High-Availability Clusters – Load-balancing Clusters

– Compute Clusters These are clusters designed mainly for collective computation over a single large job, such as large scale simulation and modeling. The cluster typically shares a dedicated network, and the nodes are mostly homogeneous and tightly coupled. This type of clusters is also known as a Beowulf cluster. Beowulf cluster typically runs Linux, or other Unix-like operating systems such as BSD, and contain shared libraries. Such as Message-Passing Interface (MPI), the Beowulf cluster behaves more like a single (super)computer.

– High-Availability clusters HA (high-availability) clusters are designed to be fault- tolerant and achieve HA of services. HA clusters operate with many redundant nodes to sustain faults or failures. They are designed to avoid all single points of failure. Many commercial HA clusters are available for various operating systems.

– Load-balancing clusters For this type of clusters, requests initiated from the user are distributed to all node computers, which results in a balanced workload among different machines. Middleware is needed to achieve dynamic load balancing by job or process migration among all the cluster nodes.

Analysis of the Top 500 Supercomputers Every six months, the world’s Top 500 supercomputers are evaluated by running the Linpack Benchmark program over very large data sets. The ranking varies from year to year, similar to a competition. We will analyze the trend of top 500 supercomputers over time from the following perspectives: – Architectural Evolution – Speed Improvement over time – Operating System Trends

Architectural Evolution

Speed Improvement Over Time

Operating System Trends in the Top 500 – The five most popular operating systems have more than a 10 percent share among the Top 500 Computers in November – 410 supercomputers are using Linux with a total processor count exceeding 4.5 million. This constitutes 82 percent of the systems adopting Linux. – The IBM AIX/OS is in second place with 17 systems (a 3.4 percent share) and more than 94,288 processors. – Third place is represented by the combined use of the SLES10 with the SGI ProPack5, with 15 systems (3 percent) over 135,200 processors. – Fourth place goes to the CNK/SLES9 used by 14 systems (2.8 percent) over 1.13 million processors. – Finally, the CNL/OS was used in 10 systems (2 percent) over 178,577 processors. – The remaining 34 systems applied 13 other operating systems with a total share of only 6.8 percent.

The Top Five Systems in 2010

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