Thrashing (computer science)

In computer science, thrashing occurs in a system with virtual memory when a computer's real storage resources are overcommitted, leading to a constant state of paging and page faults, slowing most application-level processing.[1] This causes the performance of the computer to degrade or collapse. The situation can continue indefinitely until the user closes some running applications or the active processes free up additional virtual memory resources.

After initialization, most programs operate on a small number of code and data pages compared to the total memory the program requires. The pages most frequently accessed at any point are called the working set, which may change over time.

When the working set is not significantly greater than the system's total number of real storage page frames, virtual memory systems work most efficiently, and an insignificant amount of computing is spent resolving page faults. As the total of the working sets grows, resolving page faults remains manageable until the growth reaches a critical point at which the number of faults increases dramatically and the time spent resolving them overwhelms the time spent on the computing the program was written to do. This condition is referred to as thrashing. Thrashing may occur on a program that randomly accesses huge data structures, as its large working set causes continual page faults that drastically slow down the system. Satisfying page faults may require freeing pages that will soon have to be re-read from disk.

The term is also used for various similar phenomena, particularly movement between other levels of the memory hierarchy, wherein a process progresses slowly because significant time is being spent acquiring resources.

"Thrashing" is also used in contexts other than virtual memory systems—for example, to describe cache issues in computing or silly window syndrome in networking.

  1. ^ Denning, Peter J. (1968). "Thrashing: Its causes and prevention" (PDF). Proceedings AFIPS, Fall Joint Computer Conference. 33: 915–922. Retrieved 2012-02-15.

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