APPLICATIONS ON HIGH PERFORMANCE CLUSTER COMPUTERS (original) (raw)
High Performance Computing Clusters
International Journal of Computer Applications, 2014
A computer cluster is a group of internconnected computers which are connected to form a single computer. Interconnections between computers in a cluster are made through local area networks. Problems regarding computing are solved by using high performance computing(HPC) which is an amalgamation between super computers and computing clusters.HPC combines of systems administration and parallel programming into a combination of computer architecture, system software, programming languages, algorithms and computational techniques. This paper consist of mechanism required for the creation of a 96 node single cluster.
Handbook of Nature-Inspired and Innovative Computing, 2006
The emergence of cluster platforms was driven by a number of academic projects, such as Beowulf [2], Berkeley NOW [3], and HPVM [4] that prove the advantage of clusters over other traditional platforms. These advantages include low-entry costs to access supercomputing-level performance, the ability to track technologies, incrementally upgradeable system, open source development platforms, and vendor independence. Today, clusters are widely used for research and development of science, engineering, commerce and industry applications that demand high performance computations. In addition, clusters encompass strengths such as high availability and scalability that motivate wide usage in nonsupercomputing applications as well, such as clusters working as web and database servers.
PC cluster as a platform for parallel applications
The complexity and size of the current generation of supercomputers leads to the emergence of cluster computing which is characterized by its scalability, flexibility of configuration and upgrade, high availability and improvement of cost and time. This paper, explains the importance of cluster computing and its advantages and disadvantages. Also, it presents the types of schedulers and the steps of building the cluster. The work herein also evaluates this cluster by two case studies: matrix multiplication as a simple case study and sobel edge detection as a heavy computation one.
Low cost cluster architectures for parallel and distributed processing
2000
Cluster based architectures are standing out in the last years as an alternative for the construction of versatile, low cost parallel machines. This versatility permits their use as much as a teaching tool or as a research environment in the field of parallel and distributed processing. This paper describes some of the possibilities found today on the market for the construction of cluster based parallel machines and proposes different configurations based on cost and application areas.
Scalable Cluster Technologies for Mission-Critical Enterprise Computing
2003
Enterprise computing has changed significantly in the past decade. In the past, the workloads at corporate datacenters were dominated by centralized processing using a limited number of big database servers, mainly handling online transaction processing (OLTP) and batch processing tasks in support of the back-office process. The organization of these datacenters has evolved from mainframe-oriented into a large collection of flexible application servers providing a very diverse set of services. These services still include the traditional order processing and inventory control, but now also provide internal and external information portals, continuous data-mining operations, pervasive integration of customer relationship management information, email and other collaboration services, and a variety of computational services such as financial forecasting. An important observation is that these services have become essential to the successful operation of the enterprise, and that any service interruption, either through failure or through performance degradation, could bring the activities of the enterprise to a halt. The mission-critical nature of these services requires them to be scalable, highly-available, and with robust performance guarantees. Organizing these services into compute clusters appeared a logical step as cluster technology held the promise of cost-effective scalability and was considered to be a good basis for implementing a highly-available service organization. In the early 1990's the technologies provided by traditional cluster computing, being either OLTP or parallel computing oriented, were insufficient for developing the scalable, robust services the new information-centered enterprise required. The problems that faced enterprise cluster computing are best described by Greg Pfister industry standards such as the Virtual Interface Architecture, into commercial available clustered application-servers, and into the design of a new commercial highly-scalable cluster management system that supports enterprise-wide, geographically distributed, management of cluster services. This thesis presents several of the more important results, but the research has lead to many more results, also outside of the four main areas, and these results are referenced in Appendix A. Each of the four main research areas is described in more detail in the following sections. Although significant progress had been made in the early 1990's in developing highperformance cluster interconnects, this technology was not yet suitable for integration into off-the-shelf enterprise cluster systems. The communication technology was targeted towards high-performance parallel computing where the operating systems used styles of application structuring that made it difficult to transfer the technology to standard workstations. For example the IBM SP2 used techniques that allowed only one application access to the interconnect, as the operating system provided no protection on the network. The arrival of standard high-performance network technology brought the promise that regular workstations and servers could use high-performance communication in a manner similar to parallel computing systems, but in a much more cost-effective way. Unfortunately the standard operating systems were not structured to support high-performance and the overhead on network processing was so high that most of the benefits of the new networks could not be made available. In 1994 I started research, in collaboration with Thorsten von Eicken, to break through this barrier. The resulting architecture, U-Net, presented a new abstraction that combined the power of direct user-level network access with the full protection of standard operating systems. In U-Net the network adapter was virtualized into the application's address space, enabling end-to-end network performance close to the bare-wire maximum. The complete separation of data and control for network processing enabled the construction of very high performance cluster applications. An industry consortium lead by Intel, Microsoft and Compaq standardized the U-Net architecture into the Virtual Interface Architecture, which became the de-facto standard for enterprise cluster interconnections. The U-Net architecture, its transition into VIA, and experiences with large production clusters based on VIA can be found in Part I of this thesis. Advances in the scalability of cluster hardware and cluster management systems enabled a large set of applications to benefit from improved performance and 1.3 Structuring the management of large-scale enterprise computing systems 5 1.3 Structuring the management of large-scale enterprise computing systems 5 Part I An Architecture for Protected User-Level Communication An Architecture for Protected User-Level Communication 10 An Architecture for Protected User-Level Communication results in communication patterns that are very hard to predict, which puts a heavy burden on the interconnects to manage the load in the network fairly. The separation of data and control in the VIA interface removed the ability of the communication architecture to provide end-to-end back-pressure to manage competing data streams. In chapter 4 detailed experiments are described which I performed to investigate how effective the use of flow-control feedback to network adapters is, when one cannot control the processes generating and receiving the data streams. The experiments were performed at one of the first large production VIA installations, a 256 processor cluster using a multi-stage Giganet interconnect, consisting of 40 switches organized in a fat tree. The results of the experiments were presented at the 2000 IEEE Hot Interconnects conference. COM local Distributed COM with VIA VIA with Raw Messages
High performance computing at Intel: the OSCAR software solution stack for cluster computing
2001
This is an exciiing time in high perjormance compuiing (HPC). Radical change has become ihe norm as clirsters of commerciul o f the sheu (COTS) cotnpirters have come to domitiaie HPC. The hatdware trends are clear. Microprocessor technology has coniinired to ,follow Moore 's law. These high performance processors on iwo io four processor SMP boards mcike ideal nodes for building sirpercompiiier-class c1tister.s. On the neiworking front. cotnmerciallv available networks nre delivering impressive performance niimbers. With In/inibanrl prodircis expected in ihe next year or iwo, we'll have U quuntiitn leap in rietvvork performance with a significant drop in price. I n short. ihe hardware for HPC is in good shape and iis steadilv getting better. What about the sojtware'
Four Decades of Cluster Computing
Parallel Computing: Technology Trends
During the latter half of the 1970s high performance computers (HPC) were constructed using specially designed and manufactured hardware. The preferred architectures were vector or array processors, as these allowed for high speed processing of a large class of scientific/engineering applications. Due to the high cost of the development and construction of such HPC systems, the number of available installations was limited. Researchers often had to apply for compute time on such systems and wait for weeks before being allowed access. Cheaper and more accessible HPC systems were thus in great need. The concept to construct high performance parallel computers with distributed Multiple Instruction Multiple Data (MIMD) architectures using standard off-the-shelf hardware promised the construction of affordable supercomputers. Considerable scepticism existed at the time about the feasibility that MIMD systems could offer significant increases in processing speeds. The reasons for this wer...
The acceptance of parallel computing in workstation clusters has increased in the past years. One important reason for this is the cost-efficiency of workstation clusters as an alternative to specialized distributed-memory parallel computer systems. A potential bottleneck for distributedmemory architectures is the interconnection network between the processing elements. This is the main disadvantage of clusters which arises due to the local area network (LAN) connecting the workstations. A LAN does not reach the low latency, high bandwidth and capacity of a specialized interconnection network used in distributed-memory parallel computer architectures.
Performance Evaluation of Cluster Computing.
International Journal of Engineering Sciences & Research Technology, 2013
Cluster Computing addresses the latest results in these fields that support High Performance Distributed Computing (HPDC). In HPDC environments, parallel and/or distributed computing techniques are applied to the solution of computationally intensive applications across networks of computers. A cluster computing is a type of parallel or distributed computer system, which consists of a collection of interconnected stand-alone computers working together as a single integrated computing resource. The key components of a cluster include multiple standalone computers (PCs, Workstations, or SMPs), operating systems, high-performance interconnects, middleware, parallel programming environments, and applications. It assumes that the reader is familiar with the standard commodity hardware and software components such as stand-alone computers, operating systems such as Linux and Windows, and standard communication software such as TCP/IP. There are many applications which can benefit from parallelisation. Employing clusters of computers provides a method to utilise commodity components, minimising cost and and maximising longevity of the individual parts.