Float32 results are computed using Float64s
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Updated
Feb 25, 2020 - Julia
Float32 results are computed using Float64s
Values of the initial and final bits of a significand, in absolute and relative units.
Floats that are markable, unmarkable and remarkable
A 64-bit floating point implementation for the unit interval with increased dynamic range (41 exponent bits) and the same precision as float32 (23 fraction bits).
Floats may be unmarked, marked or remarked without slowing computations.
A more robust kind of Float32.
Floating Point Arithmetic Standard IEEE 754-2019
Floats with neither Infinities nor NaNs nor signed zeros.
building blocks for more accurate floating point results
Manipulate sign, exponent, significand of Float64, Float32, Float16 values.
Precision-doubled floating point types nearly as performant as hardware floats.
This is new edited version of the known SigmoidNumbers
Toolkit for studying numerical analysis and floating point algebra round-off
Numbers that produce accurate results when used as arguments to trigonometric functions
A Julia package to manipulate very small IEEE 754 standard-compliant floating-point numbers.
Julia library providing tracking of floating point errors through a program resources
An accurate and stable calculation of the angle separating two vectors.
macro to change the default floating-point precision in Julia code
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