Software hang can cause a significant decrease in computer performance and prevent further processor capacity from being used. It occurs when multiple processors attempt to modify a single data source, leading to corruption. Specialized operating system software can minimize software blocking by distributing data to processors in smaller pieces, ensuring each processing unit always has a task. The inefficiency of multiprocessor computers limits their scalability, and adding more processors becomes pointless beyond a certain point.
A software hang is a computer problem that can occur on multiprocessor systems. This blocking can cause a dramatic decrease in a computer’s performance and prevent further processor capacity from being used. In modern multiprocessor computers, it is necessary to use special operating system software to avoid software block malfunction.
The occurrence of software hang was first described by IBM scientist Stuart Madnick in 1968. At this early stage in computer history, Madnick predicted that personal computers would get smaller and cheaper over the next few decades, but would continued to be limited to roughly the same data rates. This prediction has proved to be mostly correct, and the usable power of computers is often increased simply by adding extra processors.
The root cause of the software crash is not a bug per se, but rather a feature. In a computer with multiple processors linked together, there is no benefit to having multiple processors each handling the same information. In fact, different processors attempting to modify a single data source can corrupt the original record. To prevent multiple drives from opening the same information, only one processor is allowed access while the remaining processing components are “locked down” by the file.
This locking method is effective for computers with a small number of processors. However, the approach becomes a problem in devices with a wide range of processing units attached. Software blocking severely limits the scalability and effectiveness of adding more processors to computers, because there are limits to how fast data is distributed between storage and processors.
No machine, including a computer, is completely efficient; this inherent inefficiency is compounded in multiprocessor computers. A computer with sixteen processors, for example, might have one of its processors idle all the time because data can’t be distributed quickly enough. At some point, compound inefficiency means that it’s no longer worthwhile to expand the number of processors in a computer. Adding a thousand processors to a system is pointless, as data rates are limited and most redundant processors would be stuck in a constant software block.
Software blocking can be minimized by using an operating system specifically designed for multiple processors. Specialized software is capable of splitting a data source into many different pieces and distributing these pieces to processors. This approach reduces the need to lock down processors, as each unit can only process a small portion of the original data. In essence, multiprocessor software ensures that each processing unit always has a task and keeps data flowing in a more distributed and evenly dispersed manner.
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