For a given IEEE-754 floating point number X, if
2^E <= abs(X) < 2^(E+1)
then the distance from X to the next largest representable floating point number (epsilon) is:
epsilon = 2^(E-52) % For a 64-bit float (double precision)
epsilon = 2^(E-23) % For a 32-bit float (single precision)
epsilon = 2^(E-10) % For a 16-bit float (half precision)
The above equations allow us to compute the following:
For half precision...
If you want an accuracy of +/-0.5 (or 2^-1), the maximum size that the number can be is 2^10. Any larger than this and the distance between floating point numbers is greater than 0.5.
If you want an accuracy of +/-0.0005 (about 2^-11), the maximum size that the number can be is 1. Any larger than this and the distance between floating point numbers is greater than 0.0005.
For single precision...
If you want an accuracy of +/-0.5 (or 2^-1), the maximum size that the number can be is 2^23. Any larger than this and the distance between floating point numbers is greater than 0.5.
If you want an accuracy of +/-0.0005 (about 2^-11), the maximum size that the number can be is 2^13. Any larger than this and the distance between floating point numbers is greater than 0.0005.
For double precision...
If you want an accuracy of +/-0.5 (or 2^-1), the maximum size that the number can be is 2^52. Any larger than this and the distance between floating point numbers is greater than 0.5.
If you want an accuracy of +/-0.0005 (about 2^-11), the maximum size that the number can be is 2^42. Any larger than this and the distance between floating point numbers is greater than 0.0005.
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