Error-free transformations are used to get results with extra accuracy.
- The number that begins a function name always matches the number of values returned.
- the values returned are of descending magnitude and non-overlapping when added.
- The number that begins a function name often matches the number of arguments expected.
two_inv
andtwo_sqrt
are single argument functions returning two values
These are error-free transformations.
two_sum
,two_diff
,two_prod
two_square
,two_cube
three_sum
,three_diff
,three_prod
two_fma
,three_fma
four_sum
,four_diff
These are error-free transformations with magnitude sorted arguments.
two_hilo_sum
,two_lohi_sum
two_hilo_diff
,two_lohi_diff
three_hilo_sum
,three_lohi_sum
three_hilo_diff
,three_lohi_diff
four_hilo_sum
,four_lohi_sum
four_hilo_diff
,four_lohi_diff
These are least-error transformations, as close to error-free as possible.
two_inv
,two_sqrt
two_div
The routines named with the prefix two_
return a two-tuple holding (high_order_part, low_order_part)
.
Those named with the prefix three_
return a three-tuple holding (high_part, mid_part, low_part)
.
Error-free transformations return a tuple of the nominal result and the residual from the result (the left-over part).
Error-free addition sums two floating point values (a, b) and returns two floating point values (hi, lo) such that:
(+)(a, b) == hi
|hi| > |lo|
and(+)(hi, lo) == hi
abs(hi) and abs(lo) do not share significant bits
Here is how it is done:
function add_errorfree(a::T, b::T) where T<:Union{Float64, Float32}
a_plus_b_hipart = a + b
b_asthe_summand = a_plus_b_hipart - a
a_plus_b_lopart = (a - (a_plus_b_hipart - b_asthe_summand)) + (b - b_asthe_summand)
return a_plus_b_hipart, a_plus_b_lopart
end
a = Float32(1/golden^2) # 0.3819_6602f0
b = Float32(pi^3) # 31.0062_7700f0
a_plus_b = a + b # 31.3882_4300f0
hi, lo = add_errorfree(a,b) # (31.3882_4300f0, 3.8743_0270f-7)
a_plus_b == hi # true
abs(hi) > abs(lo) && hi + lo == hi # true
The lo
part is a portion of the accurate value, it is (most of) the residuum that the hi
part could not represent.
The hi
part runs out of significant bits before the all of the accurate value is represented. We can see this:
a = Float32(1/golden^2) # 0.3819_6602f0
b = Float32(pi^3) # 31.0062_7700f0
hi, lo = add_errorfree(a,b) # (31.3882_4300f0, 3.8743_0270f-7)
a_plus_b_accurate = BigFloat(a) + BigFloat(b)
lo_accurate = Float32(a_plus_b_accurate - hi)
lo == lo_accurate # true
This package is intended to be used in the support of other work.
All routines expect Float64 or Float32 or Float16 values.
[CG2023] Thomas R Cameron and Stef Graillat.
Accurate Horner Methods in Real and Complex Floating-Point Arithmetic
HAL Id: hal-04030542, 2023
paper retreived from https://hal.science/hal-04030542v1
C code available from https://github.com/trcameron/HornerK
[LO2020] Marko Lange and Shin'ichi Oishi
A note on Dekker’s FastTwoSum algorithm
Numerische Mathematik (2020) 145:383–403
https://doi.org/10.1007/s00211-020-01114-2
[BGM2017] Sylvie Boldo, Stef Graillat, and Jean-Michel Muller
On the robustness of the 2Sum and Fast2Sum algorithms
ACM Transactions on Mathematical Software, Association for Computing Machinery, 2017
https://hal.inria.fr/ensl-01310023
[GMM2007] Stef Graillat, Valérie Ménissier-Morain
Error-Free Transformations in Real and Complex Floating Point Arithmetic
International Symposium on Nonlinear Theory and its Applications (NOLTA'07), Sep 2007, Vancouver, Canada.
Proceedings of International Symposium on Nonlinear Theory and its Applications (NOLTA'07), pp.341-344.
https://hal.archives-ouvertes.fr/hal-01306229
[ORO2006] Takeshi Ogita, Siegfried M. Rump, and Shin'ichi Oishi
Accurate Sum and Dot Product
SIAM J. Sci. Comput., 26(6), 1955–1988.
Published online: 25 July 2006
DOI: 10.1137/030601818
[D1971] T.J. Dekker
A floating-point technique for extending the available precision
Numer. Math. 18, 224–242 (1971).
https://doi.org/10.1007/BF01397083