Although the solution is not immediately practical, it will in the future leveling the way for new data processing solutions.
The decentralization board is the principle of information structure that combines the keys to the memory of the computer. Inka Soveri
The decades -old presence of computer science has been resolved without even knowing the existence of one.
The story starts from 2021, Quantamagazine write. At that time a student at the University of Rutgers Andrew Krapiv I became acquainted with the research paper that talked about the concept of so -called decentrals familiar from computer science.
The decentralization board is a data structure that combines keys to the computer’s memory. For example, when a person’s name (key) is given on the decentralization board, it indicates the person’s phone number (value).
The key practical functionality of the decentry board includes retrieving, increasing and deleting information. Improving the performance of these functions has long been the subject of research into the scientific community.
In the aforementioned research paper, the diversification boards are approached by the image of small “arrows” that show the road for each of the data. Krapivin sought to reduce the arrows so that they would eat less computer memory.
Soon, however, he realized that the reduction would not succeed without the diversification boards. As he was thinking about this problem, Krapivin was unknowingly approaching the presence, which was made in 1985.
Assumption of the rubbish bin
At that time Andrew yao He ended up assuming that, in certain circumstances, linear execution time is the best way to find a single embryo or empty place on diversification boards.
In other words, the best way for a computer memory to find or store information is to go through any empty spaces in the decentralization table occasionally. The method is known as Uniform’s probing, or roughly translated into Finnish as a steady presence.
In addition, Yao assumed that in the worst scenario where the search is to the last remaining vacant location of the decentral charging table, the run does not exceed the value x.
X is an integer in the state of the decentralization table. For example, if X is 100, the diversification table is 99 % full. If the decentralization table is so full, in the worst case, 100 different places should go through to find a vacant place.
Krapivin, on the other hand, replaced the variable x logarithm with a square (log x) ², which meant the birth of a whole new diversification board. Together who have studied arrow objects Martín Farach-Colton and William KuszmaulN with Krapivin showed that a diversification table based on the aforementioned logarithm is the optimal way to find a single embryo or empty place.
– Not only did you create a new fine diversification board, you would sweep a 40 -year -old conjecture from the table, Kuszmaul recalls that she shouted to Krapivi as she brought her creation to the display.
Although research from Krapiviv and the colleagues is not immediately practical, it will in the future level the way to new data processing solutions and ultimately practical solutions.
