polynomial for __kernel_tanf(). The old one was the double-precision
polynomial with coefficients truncated to float. Truncation is not
a good way to convert minimax polynomials to lower precision. Optimize
for efficiency and use the lowest-degree polynomial that gives a
relative error of less than 1 ulp. It has degree 13 instead of 27,
and happens to be 2.5 times more accurate (in infinite precision) than
the old polynomial (the maximum error is 0.017 ulps instead of 0.041
ulps).
Unlike for cosf and sinf, the old accuracy was close to being inadequate
-- the polynomial for double precision has a max error of 0.014 ulps
and nearly this small an error is needed. The new accuracy is also a
bit small, but exhaustive checking shows that even the old accuracy
was enough. The increased accuracy reduces the maximum relative error
in the final result on amd64 -O1 from 0.9588 ulps to 0.9044 ulps.
special case pi/4 <= |x| < 3*pi/4. This gives a tiny optimization (it
saves 2 subtractions, which are scheduled well so they take a whole 1
cycle extra on an AthlonXP), and simplifies the code so that the
following optimization is not so ugly.
Optimize for the range 3*pi/4 < |x| < 9*Pi/2 in the same way. On
Athlon{XP,64} systems, this gives a 25-40% optimization (depending a
lot on CFLAGS) for the cosf() and sinf() consumers on this range.
Relative to i387 hardware fcos and fsin, it makes the software versions
faster in most cases instead of slower in most cases. The relative
optimization is smaller for tanf() the inefficient part is elsewhere.
The 53-bit approximation to pi/2 is good enough for pi/4 <= |x| <
3*pi/4 because after losing up to 24 bits to subtraction, we still
have 29 bits of precision and only need 25 bits. Even with only 5
extra bits, it is possible to get perfectly rounded results starting
with the reduced x, since if x is nearly a multiple of pi/2 then x is
not near a half-way case and if x is not nearly a multiple of pi/2
then we don't lose many bits. With our intentionally imperfect rounding
we get the same results for cosf(), sinf() and tanf() as without this
optimization.
standard in C99 and POSIX.1-2001+. They are also not deprecated, since
apart from being standard they can handle special args slightly better
than the ilogb() functions.
Move their documentation to ilogb.3. Try to use consistent and improved
wording for both sets of functions. All of ieee854, C99 and POSIX
have better wording and more details for special args.
Add history for the logb() functions and ilogbl(). Fix history for
ilogb().
so that it can be faster for tiny x and avoided for reduced x.
This improves things a little differently than for cosine and sine.
We still need to reclassify x in the "kernel" functions, but we get
an extra optimization for tiny x, and an overall optimization since
tiny reduced x rarely happens. We also get optimizations for space
and style. A large block of poorly duplicated code to fix a special
case is no longer needed. This supersedes the fixes in k_sin.c revs
1.9 and 1.11 and k_sinf.c 1.8 and 1.10.
Fixed wrong constant for the cutoff for "tiny" in tanf(). It was
2**-28, but should be almost the same as the cutoff in sinf() (2**-12).
The incorrect cutoff protected us from the bugs fixed in k_sinf.c 1.8
and 1.10, except 4 cases of reduced args passed the cutoff and needed
special handling in theory although not in practice. Now we essentially
use a cutoff of 0 for the case of reduced args, so we now have 0 special
args instead of 4.
This change makes no difference to the results for sinf() (since it
only changes the algorithm for the 4 special args and the results for
those happen not to change), but it changes lots of results for sin().
Exhaustive testing is impossible for sin(), but exhaustive testing
for sinf() (relative to a version with the old algorithm and a fixed
cutoff) shows that the changes in the error are either reductions or
from 0.5-epsilon ulps to 0.5+epsilon ulps. The new method just uses
some extra terms in approximations so it tends to give more accurate
results, and there are apparently no problems from having extra
accuracy. On amd64 with -O1, on all float args the error range in ulps
is reduced from (0.500, 0.665] to [0.335, 0.500) in 24168 cases and
increased from 0.500-epsilon to 0.500+epsilon in 24 cases. Non-
exhaustive testing by ucbtest shows no differences.
commit moved it). This includes a comment that the "kernel" sine no
longer works on arg -0, so callers must now handle this case. The kernel
sine still works on all other tiny args; without the optimization it is
just a little slower on these args. I intended it to keep working on
all tiny args, but that seems to be impossible without losing efficiency
or accuracy. (sin(x) ~ x * (1 + S1*x**2 + ...) would preserve -0, but
the approximation must be written as x + S1*x**3 + ... for accuracy.)
case never occurs since pi/2 is irrational so no multiple of it can
be represented as a float and we have precise arg reduction so we never
end up with a remainder of 0 in the "kernel" function unless the
original arg is 0.
If this case occurs, then we would now fall through to general code
that returns +-Inf (depending on the sign of the reduced arg) instead
of forcing +Inf. The correct handling would be to return NaN since
we would have lost so much precision that the correct result can be
anything _except_ +-Inf.
Don't reindent the else clause left over from this, although it was already
bogusly indented ("if (foo) return; else ..." just marches the indentation
to the right), since it will be removed too.
Index: k_tan.c
===================================================================
RCS file: /home/ncvs/src/lib/msun/src/k_tan.c,v
retrieving revision 1.10
diff -r1.10 k_tan.c
88,90c88
< if (((ix | low) | (iy + 1)) == 0)
< return one / fabs(x);
< else {
---
> {
a declaration was not translated to "float" although bit fiddling on
double variables was translated. This resulted in garbage being put
into the low word of one of the doubles instead of non-garbage being
put into the only word of the intended float. This had no effect on
any result because:
- with doubles, the algorithm for calculating -1/(x+y) is unnecessarily
complicated. Just returning -1/((double)x+y) would work, and the
misdeclaration gave something like that except for messing up some
low bits with the bit fiddling.
- doubles have plenty of bits to spare so messing up some of the low
bits is unlikely to matter.
- due to other bugs, the buggy code is reached for a whole 4 args out
of all 2**32 float args. The bug fixed by 1.8 only affects a small
percentage of cases and a small percentage of 4 is 0. The 4 args
happen to cause no problems without 1.8, so they are even less likely
to be affected by the bug in 1.8 than average args; in fact, neither
1.8 nor this commit makes any difference to the result for these 4
args (and thus for all args).
Corrections to the log message in 1.8: the bug only applies to tan()
and not tanf(), not because the float type can't represent numbers
large enough to trigger the problem (e.g., the example in the fdlibm-5.3
readme which is > 1.0e269), but because:
- the float type can't represent small enough numbers. For there to be
a possible problem, the original arg for tanf() must lie very near an
odd multiple of pi/2. Doubles can get nearer in absolute units. In
ulps there should be little difference, but ...
- ... the cutoff for "small" numbers is bogus in k_tanf.c. It is still
the double value (2**-28). Since this is 32 times smaller than
FLT_EPSILON and large float values are not very uniformly distributed,
only 6 args other than ones that are initially below the cutoff give
a reduced arg that passes the cutoff (the 4 problem cases mentioned
above and 2 non-problem cases).
Fixing the cutoff makes the bug affect tanf() and much easier to detect
than for tan(). With a cutoff of 2**-12 on amd64 with -O1, 670102
args pass the cutoff; of these, there are 337604 cases where there
might be an error of >= 1 ulp and 5826 cases where there is such an
error; the maximum error is 1.5382 ulps.
The fix in 1.8 works with the reduced cutoff in all cases despite the
bug in it. It changes the result in 84492 cases altogether to fix the
5826 broken cases. Fixing the fix by translating "double" to "float"
changes the result in 42 cases relative to 1.8. In 24 cases the
(absolute) error is increased and in 18 cases it is reduced, but it
remains less than 1 ulp in all cases.
rewritten, now timers created with same sigev_notify_attributes will
run in same thread, this allows user to organize which timers can
run in same thread to save some thread resource.
The log message for 1.5 said that some small (one or two ulp) inaccuracies
were fixed, and a comment implied that the critical change is to switch
the rounding mode to to-nearest, with a switch of the precision to
extended at no extra cost. Actually, the errors are very large (ucbtest
finds ones of several hundred ulps), and it is the switch of the
precision that is critical.
Another comment was wrong about NaNs being handled sloppily.
and medium size args too: instead of conditionally subtracting a float
17+24, 17+17+24 or 17+17+17+24 bit approximation to pi/2, always
subtract a double 33+53 bit one. The float version is now closer to
the double version than to old versions of itself -- it uses the same
33+53 bit approximation as the simplest cases in the double version,
and where the float version had to switch to the slow general case at
|x| == 2^7*pi/2, it now switches at |x| == 2^19*pi/2 the same as the
double version.
This speeds up arg reduction by a factor of 2 for |x| between 3*pi/4 and
2^7*pi/4, and by a factor of 7 for |x| between 2^7*pi/4 and 2^19*pi/4.
using under FreeBSD. Before this commit, all float precision functions
except exp2f() were implemented using only float precision, apparently
because Cygnus needed this in 1993 for embedded systems with slow or
inefficient double precision. For FreeBSD, except possibly on systems
that do floating point entirely in software (very old i386 and now
arm), this just gives a more complicated implementation, many bugs,
and usually worse performance for float precision than for double
precision. The bugs and worse performance were particulary large in
arg reduction for trig functions. We want to divide by an approximation
to pi/2 which has as many as 1584 bits, so we should use the widest
type that is efficient and/or easy to use, i.e., double. Use fdlibm's
__kernel_rem_pio2() to do this as Sun apparently intended. Cygnus's
k_rem_pio2f.c is now unused. e_rem_pio2f.c still needs to be separate
from e_rem_pio2.c so that it can be optimized for float args. Similarly
for long double precision.
This speeds up cosf(x) on large args by a factor of about 2. Correct
arg reduction on large args is still inherently very slow, so hopefully
these args rarely occur in practice. There is much more efficiency
to be gained by using double precision to speed up arg reduction on
medium and small float args.
__kernel_sinf(). The old ones were the double-precision polynomials
with coefficients truncated to float. Truncation is not a good way
to convert minimax polynomials to lower precision. Optimize for
efficiency and use the lowest-degree polynomials that give a relative
error of less than 1 ulp -- degree 8 instead of 14 for cosf and degree
9 instead of 13 for sinf. For sinf, the degree 8 polynomial happens
to be 6 times more accurate than the old degree 14 one, but this only
gives a tiny amount of extra accuracy in results -- we just need to
use a a degree high enough to give a polynomial whose relative accuracy
in infinite precision (but with float coefficients) is a small fraction
of a float ulp (fdlibm generally uses 1/32 for the small fraction, and
the fraction for our degree 8 polynomial is about 1/600).
The maximum relative errors for cosf() and sinf() are now 0.7719 ulps
and 0.7969 ulps, respectively.
This supersedes the fix for the old algorithm in rev.1.8 of k_cosf.c.
I want this change mainly because it is an optimization. It helps
make software cos[f](x) and sin[f](x) faster than the i387 hardware
versions for small x. It is also a simplification, and reduces the
maximum relative error for cosf() and sinf() on machines like amd64
from about 0.87 ulps to about 0.80 ulps. It was validated for cosf()
and sinf() by exhaustive testing. Exhaustive testing is not possible
for cos() and sin(), but ucbtest reports a similar reduction for the
worst case found by non-exhaustive testing. ucbtest's non-exhaustive
testing seems to be good enough to find problems in algorithms but not
maximum relative errors when there are spikes. E.g., short runs of
it find only 3 ulp error where the i387 hardware cos() has an error
of about 2**40 ulps near pi/2.
to floats (mainly i386's). All errors of more than 1 ulp for float
precision trig functions were supposed to have been fixed; however,
compiling with gcc -O2 uncovered 18250 more such errors for cosf(),
with a maximum error of 1.409 ulps.
Use essentially the same fix as in rev.1.8 of k_rem_pio2f.c (access a
non-volatile variable as a volatile). Here the -O1 case apparently
worked because the variable is in a 2-element array and it takes -O2
to mess up such a variable by putting it in a register.
The maximum error for cosf() on i386 with gcc -O2 is now 0.5467 (it
is still 0.5650 with gcc -O1). This shows that -O2 still causes some
extra precision, but the extra precision is now good.
Extra precision is harmful mainly for implementing extra precision in
software. We want to represent x+y as w+r where both "+" operations
are in infinite precision and r is tiny compared with w. There is a
standard algorithm for this (Knuth (1981) 4.2.2 Theorem C), and fdlibm
uses this routinely, but the algorithm requires w and r to have the
same precision as x and y. w is just x+y (calculated in the same
finite precision as x and y), and r is a tiny correction term. The
i386 gcc bugs tend to give extra precision in w, and then using this
extra precision in the calculation of r results in the correction
mostly staying in w and being missing from r. There still tends to
be no problem if the result is a simple expression involving w and r
-- modulo spills, w keeps its extra precision and r remains the right
correction for this wrong w. However, here we want to pass w and r
to extern functions. Extra precision is not retained in function args,
so w gets fixed up, but the change to the tiny r is tinier, so r almost
remains as a wrong correction for the right w.
{cos_sin}[f](x) so that x doesn't need to be reclassified in the
"kernel" functions to determine if it is tiny (it still needs to be
reclassified in the cosine case for other reasons that will go away).
This optimization is quite large for exponentially distributed x, since
x is tiny for almost half of the domain, but it is a pessimization for
uniformally distributed x since it takes a little time for all cases
but rarely applies. Arg reduction on exponentially distributed x
rarely gives a tiny x unless the reduction is null, so it is best to
only do the optimization if the initial x is tiny, which is what this
commit arranges. The imediate result is an average optimization of
1.4% relative to the previous version in a case that doesn't favour
the optimization (double cos(x) on all float x) and a large
pessimization for the relatively unimportant cases of lgamma[f][_r](x)
on tiny, negative, exponentially distributed x. The optimization should
be recovered for lgamma*() as part of fixing lgamma*()'s low-quality
arg reduction.
Fixed various wrong constants for the cutoff for "tiny". For cosine,
the cutoff is when x**2/2! == {FLT or DBL}_EPSILON/2. We round down
to an integral power of 2 (and for cos() reduce the power by another
1) because the exact cutoff doesn't matter and would take more work
to determine. For sine, the exact cutoff is larger due to the ration
of terms being x**2/3! instead of x**2/2!, but we use the same cutoff
as for cosine. We now use a cutoff of 2**-27 for double precision and
2**-12 for single precision. 2**-27 was used in all cases but was
misspelled 2**27 in comments. Wrong and sloppy cutoffs just cause
missed optimizations (provided the rounding mode is to nearest --
other modes just aren't supported).
