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High-performance computing (HPC) as a term arose after the term "supercomputing". [4] HPC is sometimes used as a synonym for supercomputing; but, in other contexts, "supercomputer" is used to refer to a more powerful subset of "high-performance computers", and the term "supercomputing" becomes a subset of "high-performance computing".
The LINPACK performance gives some indication of performance for some real-world problems, but does not necessarily match the processing requirements of many other supercomputer workloads, which for example may require more memory bandwidth, or may require better integer computing performance, or may need a high performance I/O system to ...
The project aims to provide a reliable basis for tracking and detecting trends in high-performance computing and bases rankings on HPL benchmarks, [1] a portable implementation of the high-performance LINPACK benchmark written in Fortran for distributed-memory computers.
There are many differences between high-throughput computing, high-performance computing (HPC), and many-task computing (MTC). HPC tasks are characterized as needing large amounts of computing power for short periods of time, whereas HTC tasks also require large amounts of computing, but for much longer times (months and years, rather than hours and days).
The actual performance will always be lower than the peak performance. [2] The performance of a computer is a complex issue that depends on many interconnected variables. The performance measured by the LINPACK benchmark consists of the number of 64-bit floating-point operations, generally additions and multiplications, a computer can perform ...
In computing, computer performance is the amount of useful work accomplished by a computer system. Outside of specific contexts, computer performance is estimated in terms of accuracy, efficiency and speed of executing computer program instructions. When it comes to high computer performance, one or more of the following factors might be involved:
Example architecture of a geographically disperse computing system connecting many nodes over a network. Grid computing uses a large number of computers in distributed, diverse administrative domains. It is an opportunistic approach which uses resources whenever they are available. [10] An example is BOINC a volunteer-based, opportunistic grid ...
Historically parallel computing was used for scientific computing and the simulation of scientific problems, particularly in the natural and engineering sciences, such as meteorology. This led to the design of parallel hardware and software, as well as high performance computing. [8]
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