The Floating Point Precision and the Non-uniform distribution of values
“Floating-Point Precision and Non-uniform Distribution of Values: Impact on Data Storage and Object Drawing” In computer programming, the concept of floating-point precision and non-uniform distribution of values can challenge how data is stored or drawn within applications. The reason is that numbers when represented this way, the individual numerical precision does not accurately represent true values (Yegulalp (2015)). Furthermore, certain values are more likely to be identified than others because the floating-point precision of the values is limited. These inaccuracies could lead to data loss or difficulty when locating objects accurately. Furthermore, floating point formats require more data to store, so it is necessary that you use a greater number of bits (Yegulalp (2015)). This can potentially limit the application’s performance due to the extra memory required. It is important to understand and consider the possible consequences of floating-point precision, an uneven distribution and inconsistent values for object storage and drawing. References Caverly, D. (2021). Understanding Floating Point Numbers. Stackoverflow.com. Retrieved 23 March 2021, from https://stackoverflow.com/questions/15805026/understanding-floating-point-numbers Yegulalp, S. (2015). How floating-point numbers work. Howtogeek.com. Retrieved 23 March 2021, from https://www.howtogeek.com/231145/how-floating-point-numbers-work/Cont…
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