math with more good bits

extended precision math, accurate and performant

Julia IEEE decimal floating-point via the Intel decimal-float library

Julia math built-ins which return NaN and accumulator functions which ignore NaN

macro to change the default floating-point precision in Julia code

Julia library providing tracking of floating point errors through a program resources

An accurate and stable calculation of the angle separating two vectors.

A Julia package to manipulate very small IEEE 754 standard-compliant floating-point numbers.

Numbers that produce accurate results when used as arguments to trigonometric functions

This is new edited version of the known SigmoidNumbers

Toolkit for studying numerical analysis and floating point algebra round-off

building blocks for more accurate floating point results

Floats with neither Infinities nor NaNs nor signed zeros.

Precision-doubled floating point types nearly as performant as hardware floats.

Manipulate sign, exponent, significand of Float64, Float32, Float16 values.

Float32 results are computed using Float64s

Posit Numbers for Julia

Values of the initial and final bits of a significand, in absolute and relative units.

Floats that are markable, unmarkable and remarkable

Floats may be unmarked, marked or remarked without slowing computations.