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Clustering for Massive Parallelism


1 April 2014

Clustering for Massive Parallelism

A computer cluster is a collection of interconnected stand-alone computers which can work together collectively and cooperatively as a single integrated computing resource pool. Clustering explores massive parallelism at the job level and achieves high availability (HA) through stand-alone operations. The benefits of computer clusters and massively parallel processors (MPPs) include scalable performance, HA, fault tolerance, modular growth, and use of commodity components. These features can sustain the generation changes experienced in hardware, software, and network components. Cluster computing became popular in the mid-1990s as traditional mainframes and vector supercomputers were proven to be less cost-effective in many high-performance computing (HPC) applications.

Of the Top 500 supercomputers reported in 2010, 85 percent were computer clusters or MPPs built with homogeneous nodes. Computer clusters have laid the foundation for today’s supercomputers, computational grids, and Internet clouds built over data centers. We have come a long way toward becoming addicted to computers. According to a recent IDC prediction, the HPC market will increase from $8.5 billion in 2010 to $10.5 billion by 2013. A majority of the Top 500 supercomputers are used for HPC applications in science and engineering. Meanwhile, the use of high-throughput computing (HTC) clusters of servers is growing rapidly in business and web services applications.

Support for clustering of computers has moved from interconnecting high-end mainframe computers to building clusters with massive numbers of x86 engines. Computer clustering started with the linking of large mainframe computers such as the IBM Sysplex and the SGI Origin 3000. Originally, this was motivated by a demand for cooperative group computing and to provide higher availability in critical enterprise applications.
Subsequently, the clustering trend moved toward the networking of many “minicomputers, such as DEC’s VMS cluster, in which multiple VAXes were interconnected to share the same set of disk/tape controllers. Tandem’s Himalaya was designed as a business cluster for fault-tolerant online transaction processing (OLTP) applications.

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 of RISC or x86 PC engines. Clustered products now appear as integrated systems, software tools, availability infrastructure, and operating system extensions. This clustering trend matches the downsizing trend in the computer industry. Supporting clusters of smaller nodes will increase sales by allowing modular incremental growth in cluster configurations. From IBM, DEC, Sun, and SGI to Compaq and Dell, the computer industry has leveraged clustering of low-cost servers or x86 desktops for their cost-effectiveness, scalability, and HA features.

Milestone Cluster Systems

Clustering has been a hot research challenge in computer architecture. Fast communication, job scheduling, SSI, and HA are active areas in cluster research. Table 2.1 lists some milestone cluster research projects and commercial cluster products. Details of these old clusters “products. Details of these old clusters can be found in [14]. These milestone projects have pioneered clustering hardware and middleware development over the past two decades. Each cluster project listed has developed some unique features. Modern clusters are headed toward HPC clusters as studied in Section 2.5.

The NOW project addresses a whole spectrum of cluster computing issues, including architecture, software support for web servers, single system image, I/O and file system, efficient communication, and enhanced availability. The Rice University TreadMarks is a good example of software-implemented shared-memory cluster of workstations. The memory sharing is implemented with a user-space runtime library. This was a research cluster built over Sun Solaris workstations. Some cluster OS functions were developed, but were never marketed successfully.

A Unix cluster of SMP servers running VMS/OS with extensions, mainly used in high-availability applications. An AIX server cluster built with Power2 nodes and Omega network and supported by IBM Loadleveler and MPI extensions. A scalable and fault-tolerant cluster for OLTP and database processing built with non-stop operating system support. The Google search engine was built at Google using commodity components. MOSIX is a distributed operating systems for use in Linux clusters, multi-clusters, grids, and the clouds, originally developed by Hebrew University in 1999.


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