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The operating system MULTICS was intended to allow hundreds of users to access a large computer. Despite its limited adoption, it can be considered the precursor to cloud computing . The UNIX operating system originated as a development of MULTICS for a single user. [ 40 ]
This is an accepted version of this page This is the latest accepted revision, reviewed on 21 January 2025. Type of extremely powerful computer For other uses, see Supercomputer (disambiguation). The Blue Gene/P supercomputer "Intrepid" at Argonne National Laboratory (pictured 2007) runs 164,000 processor cores using normal data center air conditioning, grouped in 40 racks/cabinets connected ...
The activities of the computing nodes are orchestrated by "clustering middleware", a software layer that sits atop the nodes and allows the users to treat the cluster as by and large one cohesive computing unit, e.g. via a single system image concept. [30]
To support binary compatibility with old applications, operating system interfaces had to retain their use of 32-bit file sizes and new interfaces had to be designed specifically for large-file support. To support writing portable code that makes use of LFS where possible, C standard library authors devised mechanisms that, depending on ...
A system that does not have this property is known as a non-uniform memory access (NUMA) architecture. Distributed memory systems have non-uniform memory access. Computer systems make use of caches—small and fast memories located close to the processor which store temporary copies of memory values (nearby in both the physical and logical ...
An IBM System z9 mainframe. A mainframe computer, informally called a mainframe or big iron, [1] is a computer used primarily by large organizations for critical applications like bulk data processing for tasks such as censuses, industry and consumer statistics, enterprise resource planning, and large-scale transaction processing.
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Computer system architectures which can support data parallel applications were promoted in the early 2000s for large-scale data processing requirements of data-intensive computing. [12] Data-parallelism applied computation independently to each data item of a set of data, which allows the degree of parallelism to be scaled with the volume of data.