The Associativity of Floating-Point Arithmetic
Floating-point arithmetic is widely employed in scientific computing, yet a peculiar question arises: Is it associative for addition and multiplication? This seemingly simple query harbors hidden complexities.
In the realm of floating-point addition, associativity is not always guaranteed. A striking example is the following code:
cout << ((0.7 + 0.2 + 0.1) == 1) << endl; //output is 0 cout << ((0.7 + 0.1 + 0.2) == 1) << endl; //output is 1
To our astonishment, these two statements produce different results. Why is this so?
The explanation lies in the limitations of floating-point representation. Floating-point numbers are stored as an approximation of the actual value, introducing a degree of imprecision. When adding multiple floating-point values, the order of operations matters due to accumulated errors and rounding.
As the referenced standard paper, "What Every Computer Scientist Should Know about Floating Point Arithmetic," aptly states:
"Due to roundoff errors, the associative laws of algebra do not necessarily hold for floating-point numbers."
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