Clustered file systemA clustered file system is a which is shared by being simultaneously mounted on multiple servers. There are several approaches to clustering, most of which do not employ a clustered file system (only direct attached storage for each node). Clustered file systems can provide features like location-independent addressing and redundancy which improve reliability or reduce the complexity of the other parts of the cluster. Parallel file systems are a type of clustered file system that spread data across multiple storage nodes, usually for redundancy or performance.
ScalabilityScalability is the property of a system to handle a growing amount of work. One definition for software systems specifies that this may be done by adding resources to the system. In an economic context, a scalable business model implies that a company can increase sales given increased resources. For example, a package delivery system is scalable because more packages can be delivered by adding more delivery vehicles.
Cloud computingCloud computing is the on-demand availability of computer system resources, especially data storage (cloud storage) and computing power, without direct active management by the user. Large clouds often have functions distributed over multiple locations, each of which is a data center. Cloud computing relies on sharing of resources to achieve coherence and typically uses a pay-as-you-go model, which can help in reducing capital expenses but may also lead to unexpected operating expenses for users.
Distributed memoryIn computer science, distributed memory refers to a multiprocessor computer system in which each processor has its own private memory. Computational tasks can only operate on local data, and if remote data are required, the computational task must communicate with one or more remote processors. In contrast, a shared memory multiprocessor offers a single memory space used by all processors. Processors do not have to be aware where data resides, except that there may be performance penalties, and that race conditions are to be avoided.
High-availability clusterHigh-availability clusters (also known as HA clusters, fail-over clusters) are groups of computers that support server applications that can be reliably utilized with a minimum amount of down-time. They operate by using high availability software to harness redundant computers in groups or clusters that provide continued service when system components fail. Without clustering, if a server running a particular application crashes, the application will be unavailable until the crashed server is fixed.
Server farmA server farm or server cluster is a collection of computer servers, usually maintained by an organization to supply server functionality far beyond the capability of a single machine. They often consist of thousands of computers which require a large amount of power to run and to keep cool. At the optimum performance level, a server farm has enormous financial and environmental costs. They often include backup servers that can take over the functions of primary servers that may fail.
MOSIXMOSIX is a proprietary distributed operating system. Although early versions were based on older UNIX systems, since 1999 it focuses on Linux clusters and grids. In a MOSIX cluster/grid there is no need to modify or to link applications with any library, to copy files or login to remote nodes, or even to assign processes to different nodes – it is all done automatically, like in an SMP. MOSIX has been researched and developed since 1977 at The Hebrew University of Jerusalem by the research team of Prof.
Load balancing (computing)In computing, load balancing is the process of distributing a set of tasks over a set of resources (computing units), with the aim of making their overall processing more efficient. Load balancing can optimize the response time and avoid unevenly overloading some compute nodes while other compute nodes are left idle. Load balancing is the subject of research in the field of parallel computers.
Single system imageIn distributed computing, a single system image (SSI) cluster is a cluster of machines that appears to be one single system. The concept is often considered synonymous with that of a distributed operating system, but a single image may be presented for more limited purposes, just job scheduling for instance, which may be achieved by means of an additional layer of software over conventional operating system images running on each node. The interest in SSI clusters is based on the perception that they may be simpler to use and administer than more specialized clusters.
FailoverFailover is switching to a redundant or standby computer server, system, hardware component or network upon the failure or abnormal termination of the previously active application, server, system, hardware component, or network in a computer network. Failover and switchover are essentially the same operation, except that failover is automatic and usually operates without warning, while switchover requires human intervention. Systems designers usually provide failover capability in servers, systems or networks requiring near-continuous availability and a high degree of reliability.
High-performance computingHigh-performance computing (HPC) uses supercomputers and computer clusters to solve advanced computation problems. HPC integrates systems administration (including network and security knowledge) and parallel programming into a multidisciplinary field that combines digital electronics, computer architecture, system software, programming languages, algorithms and computational techniques. HPC technologies are the tools and systems used to implement and create high performance computing systems.
Blade serverA blade server is a stripped-down server computer with a modular design optimized to minimize the use of physical space and energy. Blade servers have many components removed to save space, minimize power consumption and other considerations, while still having all the functional components to be considered a computer. Unlike a rack-mount server, a blade server fits inside a blade enclosure, which can hold multiple blade servers, providing services such as power, cooling, networking, various interconnects and management.
Volunteer computingVolunteer computing is a type of distributed computing in which people donate their computers' unused resources to a research-oriented project, and sometimes in exchange for credit points. The fundamental idea behind it is that a modern desktop computer is sufficiently powerful to perform billions of operations a second, but for most users only between 10–15% of its capacity is used. Common tasks such as word processing or web browsing leave the computer mostly idle.
Grid computingGrid computing is the use of widely distributed computer resources to reach a common goal. A computing grid can be thought of as a distributed system with non-interactive workloads that involve many files. Grid computing is distinguished from conventional high-performance computing systems such as cluster computing in that grid computers have each node set to perform a different task/application. Grid computers also tend to be more heterogeneous and geographically dispersed (thus not physically coupled) than cluster computers.
Shared-nothing architectureA shared-nothing architecture (SN) is a distributed computing architecture in which each update request is satisfied by a single node (processor/memory/storage unit) in a computer cluster. The intent is to eliminate contention among nodes. Nodes do not share (independently access) the same memory or storage. One alternative architecture is shared everything, in which requests are satisfied by arbitrary combinations of nodes. This may introduce contention, as multiple nodes may seek to update the same data at the same time.
Beowulf clusterA Beowulf cluster is a computer cluster of what are normally identical, commodity-grade computers networked into a small local area network with libraries and programs installed which allow processing to be shared among them. The result is a high-performance parallel computing cluster from inexpensive personal computer hardware. The name Beowulf originally referred to a specific computer built in 1994 by Thomas Sterling and Donald Becker at NASA. The name "Beowulf" comes from the Old English epic poem of the same name.
Multiple instruction, multiple dataIn computing, multiple instruction, multiple data (MIMD) is a technique employed to achieve parallelism. Machines using MIMD have a number of processors that function asynchronously and independently. At any time, different processors may be executing different instructions on different pieces of data. MIMD architectures may be used in a number of application areas such as computer-aided design/computer-aided manufacturing, simulation, modeling, and as communication switches.
Burroughs Large SystemsThe Burroughs Large Systems Group produced a family of large 48-bit mainframes using stack machine instruction sets with dense syllables. The first machine in the family was the B5000 in 1961, which was optimized for compiling ALGOL 60 programs extremely well, using single-pass compilers. The B5000 evolved into the B5500 (disk rather than drum) and the B5700 (up to four systems running as a cluster). Subsequent major redesigns include the B6500/B6700 line and its successors, as well as the separate B8500 line.
Kernel (operating system)The kernel is a computer program at the core of a computer's operating system and generally has complete control over everything in the system. It is the portion of the operating system code that is always resident in memory and facilitates interactions between hardware and software components. A full kernel controls all hardware resources (e.g. I/O, memory, cryptography) via device drivers, arbitrates conflicts between processes concerning such resources, and optimizes the utilization of common resources e.
Parallel computingParallel computing is a type of computation in which many calculations or processes are carried out simultaneously. Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism. Parallelism has long been employed in high-performance computing, but has gained broader interest due to the physical constraints preventing frequency scaling.
