- "A computer cluster is a set of computers that work together so that they can be viewed as a single system."
A type of distributed computing in which a group of interconnected computers work together to solve a computing problem, typically used for high-performance computing.
Parallel Computing: The use of multiple processors in a system to solve problems more quickly.
Distributed Systems: A network of computers that work together to accomplish a goal.
Grid Computing: The use of resources from multiple computers in a grid to accomplish a goal.
Cloud Computing: The use of remote servers to store, manage, and process data.
Distributed File Systems: A file system that is spread over multiple computers in a distributed system.
Operating Systems: The software that manages the resources of a computer system.
Networking: The communication between computers in a system.
Programming Languages: The tools used to write software that can run on a cluster.
Data Storage Technologies: The ways data is stored and accessed in a cluster.
Load Balancing: The process of distributing workloads across multiple nodes in a cluster.
Fault Tolerance: The ability of a system to recover from hardware or software failures.
Task Scheduling: The process of scheduling tasks to be executed on a cluster.
Resource Management: The process of allocating and managing resources on a cluster.
Virtualization: The process of creating a virtual environment on a physical server.
High-Performance Networking: The technologies used to enable high-speed communication between nodes in a cluster.
Job Management: The process of managing jobs on a cluster.
Scalability: The ability of a system to scale to handle larger workloads.
Security: The measures taken to secure a cluster against unauthorized access.
Cluster Software: The software used to manage and run a cluster.
Performance Evaluation: The process of evaluating the performance of a cluster.
Beowulf clusters: A type of cluster that combines commodity hardware with open-source software to create a high-performance computing system.
Grid clusters: A cluster that combines multiple computing resources, often in geographically dispersed locations, to form a single virtual system.
Cloud clusters: A cluster that uses cloud computing technology to create a scalable, on-demand computing environment.
GPU clusters: A cluster that uses graphics processing units (GPUs) for general-purpose computing, which can greatly increase computational speed.
MPI clusters: A cluster that uses the MPI (Message Passing Interface) protocol to enable distributed computing across multiple nodes.
Hadoop clusters: A cluster designed to run Hadoop, which is an open-source framework for processing large datasets across clusters of computers.
Server clusters: A cluster that combines multiple server nodes into a single system, often serving as a high-availability solution.
Virtual clusters: A cluster that uses virtualization technology to create a distributed computing environment, often using containers or virtual machines.
In-memory clusters: A cluster that stores data in memory to enable faster processing and analysis.
Lustre clusters: A cluster that uses the Lustre file system, which is designed for high-performance computing and large-scale data storage.
- "The components of a cluster are usually connected to each other through fast local area networks."
- "Each node (computer used as a server) running its own instance of an operating system."
- "In most circumstances, all of the nodes use the same hardware and the same operating system."
- "Although in some setups (e.g. using Open Source Cluster Application Resources (OSCAR)), different operating systems can be used on each computer, or different hardware."
- "Clusters are usually deployed to improve performance and availability over that of a single computer while typically being much more cost-effective."
- "Computer clusters emerged as a result of the convergence of a number of computing trends including the availability of low-cost microprocessors, high-speed networks, and software for high-performance distributed computing."
- "They have a wide range of applicability and deployment, ranging from small business clusters with a handful of nodes to some of the fastest supercomputers in the world such as IBM's Sequoia."
- "Prior to the advent of clusters, single-unit fault-tolerant mainframes with modular redundancy were employed."
- "Clusters are cheaper to scale out but also have increased complexity in error handling."
- "The lower upfront cost of clusters, and increased speed of network fabric has favored the adoption of clusters."
- "Software for high-performance distributed computing."
- "The components of a cluster are usually connected to each other through fast local area networks."
- "Clusters are usually deployed to improve performance and availability over that of a single computer."
- "Typically being much more cost-effective than single computers of comparable speed or availability."
- "Ranging from small business clusters with a handful of nodes to some of the fastest supercomputers in the world such as IBM's Sequoia."
- "Clusters have increased complexity in error handling, as in clusters, error modes are not opaque to running programs."
- "Computer clusters emerged as a result of the convergence of a number of computing trends including the availability of low-cost microprocessors."
- "Using Open Source Cluster Application Resources (OSCAR), different operating systems can be used on each computer, or different hardware."
- "Clusters are cheaper to scale out." Please note that some questions are answered directly in the quote provided, while others might require a combination of information from different parts of the given paragraph.