blob: bc254cf81b9dc93d52e60255c62d58cb4a88fdd0 [file] [log] [blame]
#
# (C) 2008-2009 Advanced Micro Devices, Inc. All Rights Reserved.
#
# This file is part of libacml_mv.
#
# libacml_mv is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 2.1 of the License, or (at your option) any later version.
#
# libacml_mv is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public
# License along with libacml_mv. If not, see
# <http://www.gnu.org/licenses/>.
#
#
#
# vrd4log2.asm
#
# A vector implementation of the log libm function.
#
# Prototype:
#
# __m128d,__m128d __vrd4_log2(__m128d x1, __m128d x2);
#
# Computes the natural log of x.
# Returns proper C99 values, but may not raise status flags properly.
# Less than 1 ulp of error. This version can compute 4 logs in
# 192 cycles, or 48 per value
#
# This routine computes 4 double precision log values at a time.
# The four values are passed as packed doubles in xmm0 and xmm1.
# The four results are returned as packed doubles in xmm0 and xmm1.
# Note that this represents a non-standard ABI usage, as no ABI
# ( and indeed C) currently allows returning 2 values for a function.
# It is expected that some compilers may be able to take advantage of this
# interface when implementing vectorized loops. Using the array implementation
# of the routine requires putting the inputs into memory, and retrieving
# the results from memory. This routine eliminates the need for this
# overhead if the data does not already reside in memory.
# This routine is derived directly from the array version.
#
#ifdef __ELF__
.section .note.GNU-stack,"",@progbits
#endif
# define local variable storage offsets
.equ p_x,0 # temporary for error checking operation
.equ p_idx,0x010 # index storage
.equ p_xexp,0x020 # index storage
.equ p_x2,0x030 # temporary for error checking operation
.equ p_idx2,0x040 # index storage
.equ p_xexp2,0x050 # index storage
.equ save_xa,0x060 #qword
.equ save_ya,0x068 #qword
.equ save_nv,0x070 #qword
.equ p_iter,0x078 # qword storage for number of loop iterations
.equ save_rbx,0x080 #qword
.equ p2_temp,0x090 # second temporary for get/put bits operation
.equ p2_temp1,0x0b0 # second temporary for exponent multiply
.equ p_n1,0x0c0 # temporary for near one check
.equ p_n12,0x0d0 # temporary for near one check
.equ stack_size,0x0e8
# parameters are expected as:
# xmm0 - __m128d x1
# xmm1 - __m128d x2
.text
.align 16
.p2align 4,,15
.globl __vrd4_log2
.type __vrd4_log2,@function
__vrd4_log2:
sub $stack_size,%rsp
mov %rbx,save_rbx(%rsp) # save rdi
# process 4 values at a time.
movdqa %xmm1,p_x2(%rsp) # save the input values
movdqa %xmm0,p_x(%rsp) # save the input values
# compute the logs
## if NaN or inf
# /* Store the exponent of x in xexp and put
# f into the range [0.5,1) */
pxor %xmm1,%xmm1
movdqa %xmm0,%xmm3
psrlq $52,%xmm3
psubq .L__mask_1023(%rip),%xmm3
packssdw %xmm1,%xmm3
cvtdq2pd %xmm3,%xmm6 # xexp
movdqa %xmm0,%xmm2
subpd .L__real_one(%rip),%xmm2
movapd %xmm6,p_xexp(%rsp)
andpd .L__real_notsign(%rip),%xmm2
xor %rax,%rax
movdqa %xmm0,%xmm3
pand .L__real_mant(%rip),%xmm3
cmppd $1,.L__real_threshold(%rip),%xmm2
movmskpd %xmm2,%ecx
movdqa %xmm3,%xmm4
mov %ecx,p_n1(%rsp)
#/* Now x = 2**xexp * f, 1/2 <= f < 1. */
psrlq $45,%xmm3
movdqa %xmm3,%xmm2
psrlq $1,%xmm3
paddq .L__mask_040(%rip),%xmm3
pand .L__mask_001(%rip),%xmm2
paddq %xmm2,%xmm3
packssdw %xmm1,%xmm3
cvtdq2pd %xmm3,%xmm1
pxor %xmm7,%xmm7
movdqa p_x2(%rsp),%xmm2
movapd p_x2(%rsp),%xmm5
psrlq $52,%xmm2
psubq .L__mask_1023(%rip),%xmm2
packssdw %xmm7,%xmm2
subpd .L__real_one(%rip),%xmm5
andpd .L__real_notsign(%rip),%xmm5
cvtdq2pd %xmm2,%xmm6 # xexp
xor %rcx,%rcx
cmppd $1,.L__real_threshold(%rip),%xmm5
movq %xmm3,p_idx(%rsp)
# reduce and get u
por .L__real_half(%rip),%xmm4
movdqa %xmm4,%xmm2
movapd %xmm6,p_xexp2(%rsp)
# do near one check
movmskpd %xmm5,%edx
mov %edx,p_n12(%rsp)
mulpd .L__real_3f80000000000000(%rip),%xmm1 # f1 = index/128
lea .L__np_ln_lead_table(%rip),%rdx
mov p_idx(%rsp),%eax
movdqa p_x2(%rsp),%xmm6
movapd .L__real_half(%rip),%xmm5 # .5
subpd %xmm1,%xmm2 # f2 = f - f1
pand .L__real_mant(%rip),%xmm6
mulpd %xmm2,%xmm5
addpd %xmm5,%xmm1
movdqa %xmm6,%xmm8
psrlq $45,%xmm6
movdqa %xmm6,%xmm4
psrlq $1,%xmm6
paddq .L__mask_040(%rip),%xmm6
pand .L__mask_001(%rip),%xmm4
paddq %xmm4,%xmm6
# do error checking here for scheduling. Saves a bunch of cycles as
# compared to doing this at the start of the routine.
## if NaN or inf
movapd %xmm0,%xmm3
andpd .L__real_inf(%rip),%xmm3
cmppd $0,.L__real_inf(%rip),%xmm3
movmskpd %xmm3,%r8d
packssdw %xmm7,%xmm6
por .L__real_half(%rip),%xmm8
movq %xmm6,p_idx2(%rsp)
cvtdq2pd %xmm6,%xmm9
cmppd $2,.L__real_zero(%rip),%xmm0
mulpd .L__real_3f80000000000000(%rip),%xmm9 # f1 = index/128
movmskpd %xmm0,%r9d
# delaying this divide helps, but moving the other one does not.
# it was after the paddq
divpd %xmm1,%xmm2 # u
# compute the index into the log tables
#
movlpd -512(%rdx,%rax,8),%xmm0 # z1
mov p_idx+4(%rsp),%ecx
movhpd -512(%rdx,%rcx,8),%xmm0 # z1
# solve for ln(1+u)
movapd %xmm2,%xmm1 # u
mulpd %xmm2,%xmm2 # u^2
movapd %xmm2,%xmm5
movapd .L__real_cb3(%rip),%xmm3
mulpd %xmm2,%xmm3 #Cu2
mulpd %xmm1,%xmm5 # u^3
addpd .L__real_cb2(%rip),%xmm3 #B+Cu2
mulpd %xmm5,%xmm2 # u^5
movapd .L__real_log2e_lead(%rip),%xmm4
mulpd .L__real_cb1(%rip),%xmm5 #Au3
addpd %xmm5,%xmm1 # u+Au3
movapd %xmm0,%xmm5 #z1 copy
mulpd %xmm3,%xmm2 # u5(B+Cu2)
movapd .L__real_log2e_tail(%rip),%xmm3
movapd p_xexp(%rsp),%xmm6 # xexp
addpd %xmm2,%xmm1 # poly
# recombine
lea .L__np_ln_tail_table(%rip),%rdx
movlpd -512(%rdx,%rax,8),%xmm2 #z2 +=q
movhpd -512(%rdx,%rcx,8),%xmm2 #z2 +=q
lea .L__np_ln_lead_table(%rip),%rdx
mov p_idx2(%rsp),%eax
mov p_idx2+4(%rsp),%ecx
addpd %xmm2,%xmm1 #z2
movapd %xmm1,%xmm2 #z2 copy
mulpd %xmm4,%xmm5
mulpd %xmm4,%xmm1
movapd .L__real_half(%rip),%xmm4 # .5
subpd %xmm9,%xmm8 # f2 = f - f1
mulpd %xmm8,%xmm4
addpd %xmm4,%xmm9
mulpd %xmm3,%xmm2 #z2*log2e_tail
mulpd %xmm3,%xmm0 #z1*log2e_tail
addpd %xmm6,%xmm5 #r1 = z1*log2e_lead + xexp
addpd %xmm2,%xmm0 #z1*log2e_tail + z2*log2e_tail
addpd %xmm1,%xmm0 #r2
divpd %xmm9,%xmm8 # u
movapd p_x2(%rsp),%xmm3
andpd .L__real_inf(%rip),%xmm3
cmppd $0,.L__real_inf(%rip),%xmm3
movmskpd %xmm3,%r10d
movapd p_x2(%rsp),%xmm6
cmppd $2,.L__real_zero(%rip),%xmm6
movmskpd %xmm6,%r11d
# check for nans/infs
test $3,%r8d
addpd %xmm5,%xmm0 #r1+r2
jnz .L__log_naninf
.L__vlog1:
# check for negative numbers or zero
test $3,%r9d
jnz .L__z_or_n
.L__vlog2:
# It seems like a good idea to try and interleave
# even more of the following code sooner into the
# program. But there were conflicts with the table
# index registers, making the problem difficult.
# After a lot of work in a branch of this file,
# I was not able to match the speed of this version.
# CodeAnalyst shows that there is lots of unused add
# pipe time around the divides, but the processor
# doesn't seem to be able to schedule in those slots.
movlpd -512(%rdx,%rax,8),%xmm7 #z2 +=q
movhpd -512(%rdx,%rcx,8),%xmm7 #z2 +=q
# check for near one
mov p_n1(%rsp),%r9d
test $3,%r9d
jnz .L__near_one1
.L__vlog2n:
# solve for ln(1+u)
movapd %xmm8,%xmm9 # u
mulpd %xmm8,%xmm8 # u^2
movapd %xmm8,%xmm5
movapd .L__real_cb3(%rip),%xmm3
mulpd %xmm8,%xmm3 #Cu2
mulpd %xmm9,%xmm5 # u^3
addpd .L__real_cb2(%rip),%xmm3 #B+Cu2
mulpd %xmm5,%xmm8 # u^5
movapd .L__real_log2e_lead(%rip),%xmm4
mulpd .L__real_cb1(%rip),%xmm5 #Au3
addpd %xmm5,%xmm9 # u+Au3
movapd %xmm7,%xmm5 #z1 copy
mulpd %xmm3,%xmm8 # u5(B+Cu2)
movapd .L__real_log2e_tail(%rip),%xmm3
movapd p_xexp2(%rsp),%xmm6 # xexp
addpd %xmm8,%xmm9 # poly
# recombine
lea .L__np_ln_tail_table(%rip),%rdx
movlpd -512(%rdx,%rax,8),%xmm2 #z2 +=q
movhpd -512(%rdx,%rcx,8),%xmm2 #z2 +=q
addpd %xmm2,%xmm9 #z2
movapd %xmm9,%xmm2 #z2 copy
mulpd %xmm4,%xmm5 #z1*log2e_lead
mulpd %xmm4,%xmm9 #z2*log2e_lead
mulpd %xmm3,%xmm2 #z2*log2e_tail
mulpd %xmm3,%xmm7 #z1*log2e_tail
addpd %xmm6,%xmm5 #r1 = z1*log2e_lead + xexp
addpd %xmm2,%xmm7 #z1*log2e_tail + z2*log2e_tail
addpd %xmm9,%xmm7 #r2
# check for nans/infs
test $3,%r10d
addpd %xmm5,%xmm7
jnz .L__log_naninf2
.L__vlog3:
# check for negative numbers or zero
test $3,%r11d
jnz .L__z_or_n2
.L__vlog4:
mov p_n12(%rsp),%r9d
test $3,%r9d
jnz .L__near_one2
.L__vlog4n:
# store the result _m128d
movapd %xmm7,%xmm1
.L__finish:
mov save_rbx(%rsp),%rbx # restore rbx
add $stack_size,%rsp
ret
.align 16
.Lboth_nearone:
# saves 10 cycles
# r = x - 1.0;
movapd .L__real_two(%rip),%xmm2
subpd .L__real_one(%rip),%xmm0 # r
# u = r / (2.0 + r);
addpd %xmm0,%xmm2
movapd %xmm0,%xmm1
divpd %xmm2,%xmm1 # u
movapd .L__real_ca4(%rip),%xmm4 #D
movapd .L__real_ca3(%rip),%xmm5 #C
# correction = r * u;
movapd %xmm0,%xmm6
mulpd %xmm1,%xmm6 # correction
# u = u + u;
addpd %xmm1,%xmm1 #u
movapd %xmm1,%xmm2
mulpd %xmm2,%xmm2 #v =u^2
# r2 = (u * v * (ca_1 + v * (ca_2 + v * (ca_3 + v * ca_4))) - correction);
mulpd %xmm1,%xmm5 # Cu
movapd %xmm1,%xmm3
mulpd %xmm2,%xmm3 # u^3
mulpd .L__real_ca2(%rip),%xmm2 #Bu^2
mulpd %xmm3,%xmm4 #Du^3
addpd .L__real_ca1(%rip),%xmm2 # +A
movapd %xmm3,%xmm1
mulpd %xmm1,%xmm1 # u^6
addpd %xmm4,%xmm5 #Cu+Du3
mulpd %xmm3,%xmm2 #u3(A+Bu2)
mulpd %xmm5,%xmm1 #u6(Cu+Du3)
addpd %xmm1,%xmm2
subpd %xmm6,%xmm2 # -correction
# loge to log2
movapd %xmm0,%xmm3 #r1 = r
pand .L__mask_lower(%rip),%xmm3
subpd %xmm3,%xmm0
addpd %xmm0,%xmm2 #r2 = r2 + (r - r1);
movapd %xmm3,%xmm0
movapd %xmm2,%xmm1
mulpd .L__real_log2e_tail(%rip),%xmm2
mulpd .L__real_log2e_tail(%rip),%xmm0
mulpd .L__real_log2e_lead(%rip),%xmm1
mulpd .L__real_log2e_lead(%rip),%xmm3
addpd %xmm2,%xmm0
addpd %xmm1,%xmm0
addpd %xmm3,%xmm0
# return r + r2;
# addpd %xmm2,%xmm0
ret
.align 16
.L__near_one1:
cmp $3,%r9d
jnz .L__n1nb1
movapd p_x(%rsp),%xmm0
call .Lboth_nearone
jmp .L__vlog2n
.align 16
.L__n1nb1:
test $1,%r9d
jz .L__lnn12
movlpd p_x(%rsp),%xmm0
call .L__ln1
.L__lnn12:
test $2,%r9d # second number?
jz .L__lnn1e
movlpd %xmm0,p_x(%rsp)
movlpd p_x+8(%rsp),%xmm0
call .L__ln1
movlpd %xmm0,p_x+8(%rsp)
movapd p_x(%rsp),%xmm0
.L__lnn1e:
jmp .L__vlog2n
.align 16
.L__near_one2:
cmp $3,%r9d
jnz .L__n1nb2
movapd %xmm0,%xmm8
movapd p_x2(%rsp),%xmm0
call .Lboth_nearone
movapd %xmm0,%xmm7
movapd %xmm8,%xmm0
jmp .L__vlog4n
.align 16
.L__n1nb2:
movapd %xmm0,%xmm8
test $1,%r9d
jz .L__lnn22
movapd %xmm7,%xmm0
movlpd p_x2(%rsp),%xmm0
call .L__ln1
movapd %xmm0,%xmm7
.L__lnn22:
test $2,%r9d # second number?
jz .L__lnn2e
movlpd %xmm7,p_x2(%rsp)
movlpd p_x2+8(%rsp),%xmm0
call .L__ln1
movlpd %xmm0,p_x2+8(%rsp)
movapd p_x2(%rsp),%xmm7
.L__lnn2e:
movapd %xmm8,%xmm0
jmp .L__vlog4n
.align 16
.L__ln1:
# saves 10 cycles
# r = x - 1.0;
movlpd .L__real_two(%rip),%xmm2
subsd .L__real_one(%rip),%xmm0 # r
# u = r / (2.0 + r);
addsd %xmm0,%xmm2
movsd %xmm0,%xmm1
divsd %xmm2,%xmm1 # u
movlpd .L__real_ca4(%rip),%xmm4 #D
movlpd .L__real_ca3(%rip),%xmm5 #C
# correction = r * u;
movsd %xmm0,%xmm6
mulsd %xmm1,%xmm6 # correction
# u = u + u;
addsd %xmm1,%xmm1 #u
movsd %xmm1,%xmm2
mulsd %xmm2,%xmm2 #v =u^2
# r2 = (u * v * (ca_1 + v * (ca_2 + v * (ca_3 + v * ca_4))) - correction);
mulsd %xmm1,%xmm5 # Cu
movsd %xmm1,%xmm3
mulsd %xmm2,%xmm3 # u^3
mulsd .L__real_ca2(%rip),%xmm2 #Bu^2
mulsd %xmm3,%xmm4 #Du^3
addsd .L__real_ca1(%rip),%xmm2 # +A
movsd %xmm3,%xmm1
mulsd %xmm1,%xmm1 # u^6
addsd %xmm4,%xmm5 #Cu+Du3
mulsd %xmm3,%xmm2 #u3(A+Bu2)
mulsd %xmm5,%xmm1 #u6(Cu+Du3)
addsd %xmm1,%xmm2
subsd %xmm6,%xmm2 # -correction
# loge to log2
movsd %xmm0,%xmm3 #r1 = r
pand .L__mask_lower(%rip),%xmm3
subsd %xmm3,%xmm0
addsd %xmm0,%xmm2 #r2 = r2 + (r - r1);
movsd %xmm3,%xmm0
movsd %xmm2,%xmm1
mulsd .L__real_log2e_tail(%rip),%xmm2
mulsd .L__real_log2e_tail(%rip),%xmm0
mulsd .L__real_log2e_lead(%rip),%xmm1
mulsd .L__real_log2e_lead(%rip),%xmm3
addsd %xmm2,%xmm0
addsd %xmm1,%xmm0
addsd %xmm3,%xmm0
# return r + r2;
# addsd %xmm2,%xmm0
ret
.align 16
# at least one of the numbers was a nan or infinity
.L__log_naninf:
test $1,%r8d # first number?
jz .L__lninf2
mov %rax,p2_temp(%rsp)
mov %rdx,p2_temp+8(%rsp)
movapd %xmm0,%xmm1 # save the inputs
mov p_x(%rsp),%rdx
movlpd p_x(%rsp),%xmm0
call .L__lni
shufpd $2,%xmm1,%xmm0
mov p2_temp(%rsp),%rax
mov p2_temp+8(%rsp),%rdx
.L__lninf2:
test $2,%r8d # second number?
jz .L__lninfe
mov %rax,p2_temp(%rsp)
mov %rdx,p2_temp+8(%rsp)
movapd %xmm0,%xmm1 # save the inputs
mov p_x+8(%rsp),%rdx
movlpd p_x+8(%rsp),%xmm0
call .L__lni
shufpd $0,%xmm0,%xmm1
movapd %xmm1,%xmm0
mov p2_temp(%rsp),%rax
mov p2_temp+8(%rsp),%rdx
.L__lninfe:
jmp .L__vlog1 # continue processing if not
# at least one of the numbers was a nan or infinity
.L__log_naninf2:
movapd %xmm0,%xmm2
test $1,%r10d # first number?
jz .L__lninf22
mov %rax,p2_temp(%rsp)
mov %rdx,p2_temp+8(%rsp)
movapd %xmm7,%xmm1 # save the inputs
mov p_x2(%rsp),%rdx
movlpd p_x2(%rsp),%xmm0
call .L__lni
shufpd $2,%xmm7,%xmm0
mov p2_temp(%rsp),%rax
mov p2_temp+8(%rsp),%rdx
movapd %xmm0,%xmm7
.L__lninf22:
test $2,%r10d # second number?
jz .L__lninfe2
mov %rax,p2_temp(%rsp)
mov %rdx,p2_temp+8(%rsp)
mov p_x2+8(%rsp),%rdx
movlpd p_x2+8(%rsp),%xmm0
call .L__lni
shufpd $0,%xmm0,%xmm7
mov p2_temp(%rsp),%rax
mov p2_temp+8(%rsp),%rdx
.L__lninfe2:
movapd %xmm2,%xmm0
jmp .L__vlog3 # continue processing if not
# a subroutine to treat one number for nan/infinity
# the number is expected in rdx and returned in the low
# half of xmm0
.L__lni:
mov $0x0000FFFFFFFFFFFFF,%rax
test %rax,%rdx
jnz .L__lnan # jump if mantissa not zero, so it's a NaN
# inf
rcl $1,%rdx
jnc .L__lne2 # log(+inf) = inf
# negative x
movlpd .L__real_nan(%rip),%xmm0
ret
#NaN
.L__lnan:
mov $0x00008000000000000,%rax # convert to quiet
or %rax,%rdx
.L__lne:
movd %rdx,%xmm0
.L__lne2:
ret
.align 16
# at least one of the numbers was a zero, a negative number, or both.
.L__z_or_n:
test $1,%r9d # first number?
jz .L__zn2
mov %rax,p2_temp(%rsp)
mov %rdx,p2_temp+8(%rsp)
movapd %xmm0,%xmm1 # save the inputs
mov p_x(%rsp),%rax
call .L__zni
shufpd $2,%xmm1,%xmm0
mov p2_temp(%rsp),%rax
mov p2_temp+8(%rsp),%rdx
.L__zn2:
test $2,%r9d # second number?
jz .L__zne
mov %rax,p2_temp(%rsp)
mov %rdx,p2_temp+8(%rsp)
movapd %xmm0,%xmm1 # save the inputs
mov p_x+8(%rsp),%rax
call .L__zni
shufpd $0,%xmm0,%xmm1
movapd %xmm1,%xmm0
mov p2_temp(%rsp),%rax
mov p2_temp+8(%rsp),%rdx
.L__zne:
jmp .L__vlog2
.L__z_or_n2:
movapd %xmm0,%xmm2
test $1,%r11d # first number?
jz .L__zn22
mov %rax,p2_temp(%rsp)
mov %rdx,p2_temp+8(%rsp)
mov p_x2(%rsp),%rax
call .L__zni
shufpd $2,%xmm7,%xmm0
movapd %xmm0,%xmm7
mov p2_temp(%rsp),%rax
mov p2_temp+8(%rsp),%rdx
.L__zn22:
test $2,%r11d # second number?
jz .L__zne2
mov %rax,p2_temp(%rsp)
mov %rdx,p2_temp+8(%rsp)
mov p_x2+8(%rsp),%rax
call .L__zni
shufpd $0,%xmm0,%xmm7
mov p2_temp(%rsp),%rax
mov p2_temp+8(%rsp),%rdx
.L__zne2:
movapd %xmm2,%xmm0
jmp .L__vlog4
# a subroutine to treat one number for zero or negative values
# the number is expected in rax and returned in the low
# half of xmm0
.L__zni:
shl $1,%rax
jnz .L__zn_x ## if just a carry, then must be negative
movlpd .L__real_ninf(%rip),%xmm0 # C99 specs -inf for +-0
ret
.L__zn_x:
movlpd .L__real_nan(%rip),%xmm0
ret
.data
.align 16
.L__real_one: .quad 0x03ff0000000000000 # 1.0
.quad 0x03ff0000000000000 # for alignment
.L__real_two: .quad 0x04000000000000000 # 1.0
.quad 0x04000000000000000
.L__real_ninf: .quad 0x0fff0000000000000 # -inf
.quad 0x0fff0000000000000
.L__real_inf: .quad 0x07ff0000000000000 # +inf
.quad 0x07ff0000000000000
.L__real_nan: .quad 0x07ff8000000000000 # NaN
.quad 0x07ff8000000000000
.L__real_zero: .quad 0x00000000000000000 # 0.0
.quad 0x00000000000000000
.L__real_sign: .quad 0x08000000000000000 # sign bit
.quad 0x08000000000000000
.L__real_notsign: .quad 0x07ffFFFFFFFFFFFFF # ^sign bit
.quad 0x07ffFFFFFFFFFFFFF
.L__real_threshold: .quad 0x03F9EB85000000000 # .03
.quad 0x03F9EB85000000000
.L__real_qnanbit: .quad 0x00008000000000000 # quiet nan bit
.quad 0x00008000000000000
.L__real_mant: .quad 0x0000FFFFFFFFFFFFF # mantissa bits
.quad 0x0000FFFFFFFFFFFFF
.L__real_3f80000000000000: .quad 0x03f80000000000000 # /* 0.0078125 = 1/128 */
.quad 0x03f80000000000000
.L__mask_1023: .quad 0x000000000000003ff #
.quad 0x000000000000003ff
.L__mask_040: .quad 0x00000000000000040 #
.quad 0x00000000000000040
.L__mask_001: .quad 0x00000000000000001 #
.quad 0x00000000000000001
.L__real_ca1: .quad 0x03fb55555555554e6 # 8.33333333333317923934e-02
.quad 0x03fb55555555554e6
.L__real_ca2: .quad 0x03f89999999bac6d4 # 1.25000000037717509602e-02
.quad 0x03f89999999bac6d4
.L__real_ca3: .quad 0x03f62492307f1519f # 2.23213998791944806202e-03
.quad 0x03f62492307f1519f
.L__real_ca4: .quad 0x03f3c8034c85dfff0 # 4.34887777707614552256e-04
.quad 0x03f3c8034c85dfff0
.L__real_cb1: .quad 0x03fb5555555555557 # 8.33333333333333593622e-02
.quad 0x03fb5555555555557
.L__real_cb2: .quad 0x03f89999999865ede # 1.24999999978138668903e-02
.quad 0x03f89999999865ede
.L__real_cb3: .quad 0x03f6249423bd94741 # 2.23219810758559851206e-03
.quad 0x03f6249423bd94741
.L__real_log2_lead: .quad 0x03fe62e42e0000000 # log2_lead 6.93147122859954833984e-01
.quad 0x03fe62e42e0000000
.L__real_log2_tail: .quad 0x03e6efa39ef35793c # log2_tail 5.76999904754328540596e-08
.quad 0x03e6efa39ef35793c
.L__real_half: .quad 0x03fe0000000000000 # 1/2
.quad 0x03fe0000000000000
.L__real_log2e_lead: .quad 0x03FF7154400000000 # log2e_lead 1.44269180297851562500E+00
.quad 0x03FF7154400000000
.L__real_log2e_tail : .quad 0x03ECB295C17F0BBBE # log2e_tail 3.23791044778235969970E-06
.quad 0x03ECB295C17F0BBBE
.L__mask_lower: .quad 0x0ffffffff00000000
.quad 0x0ffffffff00000000
.align 16
.L__np_ln_lead_table:
.quad 0x0000000000000000 # 0.00000000000000000000e+00
.quad 0x3f8fc0a800000000 # 1.55041813850402832031e-02
.quad 0x3f9f829800000000 # 3.07716131210327148438e-02
.quad 0x3fa7745800000000 # 4.58095073699951171875e-02
.quad 0x3faf0a3000000000 # 6.06245994567871093750e-02
.quad 0x3fb341d700000000 # 7.52233862876892089844e-02
.quad 0x3fb6f0d200000000 # 8.96121263504028320312e-02
.quad 0x3fba926d00000000 # 1.03796780109405517578e-01
.quad 0x3fbe270700000000 # 1.17783010005950927734e-01
.quad 0x3fc0d77e00000000 # 1.31576299667358398438e-01
.quad 0x3fc2955280000000 # 1.45181953907012939453e-01
.quad 0x3fc44d2b00000000 # 1.58604979515075683594e-01
.quad 0x3fc5ff3000000000 # 1.71850204467773437500e-01
.quad 0x3fc7ab8900000000 # 1.84922337532043457031e-01
.quad 0x3fc9525a80000000 # 1.97825729846954345703e-01
.quad 0x3fcaf3c900000000 # 2.10564732551574707031e-01
.quad 0x3fcc8ff780000000 # 2.23143517971038818359e-01
.quad 0x3fce270700000000 # 2.35566020011901855469e-01
.quad 0x3fcfb91800000000 # 2.47836112976074218750e-01
.quad 0x3fd0a324c0000000 # 2.59957492351531982422e-01
.quad 0x3fd1675c80000000 # 2.71933674812316894531e-01
.quad 0x3fd22941c0000000 # 2.83768117427825927734e-01
.quad 0x3fd2e8e280000000 # 2.95464158058166503906e-01
.quad 0x3fd3a64c40000000 # 3.07025015354156494141e-01
.quad 0x3fd4618bc0000000 # 3.18453729152679443359e-01
.quad 0x3fd51aad80000000 # 3.29753279685974121094e-01
.quad 0x3fd5d1bd80000000 # 3.40926527976989746094e-01
.quad 0x3fd686c800000000 # 3.51976394653320312500e-01
.quad 0x3fd739d7c0000000 # 3.62905442714691162109e-01
.quad 0x3fd7eaf800000000 # 3.73716354370117187500e-01
.quad 0x3fd89a3380000000 # 3.84411692619323730469e-01
.quad 0x3fd9479400000000 # 3.94993782043457031250e-01
.quad 0x3fd9f323c0000000 # 4.05465066432952880859e-01
.quad 0x3fda9cec80000000 # 4.15827870368957519531e-01
.quad 0x3fdb44f740000000 # 4.26084339618682861328e-01
.quad 0x3fdbeb4d80000000 # 4.36236739158630371094e-01
.quad 0x3fdc8ff7c0000000 # 4.46287095546722412109e-01
.quad 0x3fdd32fe40000000 # 4.56237375736236572266e-01
.quad 0x3fddd46a00000000 # 4.66089725494384765625e-01
.quad 0x3fde744240000000 # 4.75845873355865478516e-01
.quad 0x3fdf128f40000000 # 4.85507786273956298828e-01
.quad 0x3fdfaf5880000000 # 4.95077252388000488281e-01
.quad 0x3fe02552a0000000 # 5.04556000232696533203e-01
.quad 0x3fe0723e40000000 # 5.13945698738098144531e-01
.quad 0x3fe0be72e0000000 # 5.23248136043548583984e-01
.quad 0x3fe109f380000000 # 5.32464742660522460938e-01
.quad 0x3fe154c3c0000000 # 5.41597247123718261719e-01
.quad 0x3fe19ee6a0000000 # 5.50647079944610595703e-01
.quad 0x3fe1e85f40000000 # 5.59615731239318847656e-01
.quad 0x3fe23130c0000000 # 5.68504691123962402344e-01
.quad 0x3fe2795e00000000 # 5.77315330505371093750e-01
.quad 0x3fe2c0e9e0000000 # 5.86049020290374755859e-01
.quad 0x3fe307d720000000 # 5.94707071781158447266e-01
.quad 0x3fe34e2880000000 # 6.03290796279907226562e-01
.quad 0x3fe393e0c0000000 # 6.11801505088806152344e-01
.quad 0x3fe3d90260000000 # 6.20240390300750732422e-01
.quad 0x3fe41d8fe0000000 # 6.28608644008636474609e-01
.quad 0x3fe4618bc0000000 # 6.36907458305358886719e-01
.quad 0x3fe4a4f840000000 # 6.45137906074523925781e-01
.quad 0x3fe4e7d800000000 # 6.53301239013671875000e-01
.quad 0x3fe52a2d20000000 # 6.61398470401763916016e-01
.quad 0x3fe56bf9c0000000 # 6.69430613517761230469e-01
.quad 0x3fe5ad4040000000 # 6.77398800849914550781e-01
.quad 0x3fe5ee02a0000000 # 6.85303986072540283203e-01
.quad 0x3fe62e42e0000000 # 6.93147122859954833984e-01
.quad 0 # for alignment
.L__np_ln_tail_table:
.quad 0x00000000000000000 # 0 ; 0.00000000000000000000e+00
.quad 0x03e361f807c79f3db # 5.15092497094772879206e-09
.quad 0x03e6873c1980267c8 # 4.55457209735272790188e-08
.quad 0x03e5ec65b9f88c69e # 2.86612990859791781788e-08
.quad 0x03e58022c54cc2f99 # 2.23596477332056055352e-08
.quad 0x03e62c37a3a125330 # 3.49498983167142274770e-08
.quad 0x03e615cad69737c93 # 3.23392843005887000414e-08
.quad 0x03e4d256ab1b285e9 # 1.35722380472479366661e-08
.quad 0x03e5b8abcb97a7aa2 # 2.56504325268044191098e-08
.quad 0x03e6f34239659a5dc # 5.81213608741512136843e-08
.quad 0x03e6e07fd48d30177 # 5.59374849578288093334e-08
.quad 0x03e6b32df4799f4f6 # 5.06615629004996189970e-08
.quad 0x03e6c29e4f4f21cf8 # 5.24588857848400955725e-08
.quad 0x03e1086c848df1b59 # 9.61968535632653505972e-10
.quad 0x03e4cf456b4764130 # 1.34829655346594463137e-08
.quad 0x03e63a02ffcb63398 # 3.65557749306383026498e-08
.quad 0x03e61e6a6886b0976 # 3.33431709374069198903e-08
.quad 0x03e6b8abcb97a7aa2 # 5.13008650536088382197e-08
.quad 0x03e6b578f8aa35552 # 5.09285070380306053751e-08
.quad 0x03e6139c871afb9fc # 3.20853940845502057341e-08
.quad 0x03e65d5d30701ce64 # 4.06713248643004200446e-08
.quad 0x03e6de7bcb2d12142 # 5.57028186706125221168e-08
.quad 0x03e6d708e984e1664 # 5.48356693724804282546e-08
.quad 0x03e556945e9c72f36 # 1.99407553679345001938e-08
.quad 0x03e20e2f613e85bda # 1.96585517245087232086e-09
.quad 0x03e3cb7e0b42724f6 # 6.68649386072067321503e-09
.quad 0x03e6fac04e52846c7 # 5.89936034642113390002e-08
.quad 0x03e5e9b14aec442be # 2.85038578721554472484e-08
.quad 0x03e6b5de8034e7126 # 5.09746772910284482606e-08
.quad 0x03e6dc157e1b259d3 # 5.54234668933210171467e-08
.quad 0x03e3b05096ad69c62 # 6.29100830926604004874e-09
.quad 0x03e5c2116faba4cdd # 2.61974119468563937716e-08
.quad 0x03e665fcc25f95b47 # 4.16752115011186398935e-08
.quad 0x03e5a9a08498d4850 # 2.47747534460820790327e-08
.quad 0x03e6de647b1465f77 # 5.56922172017964209793e-08
.quad 0x03e5da71b7bf7861d # 2.76162876992552906035e-08
.quad 0x03e3e6a6886b09760 # 7.08169709942321478061e-09
.quad 0x03e6f0075eab0ef64 # 5.77453510221151779025e-08
.quad 0x03e33071282fb989b # 4.43021445893361960146e-09
.quad 0x03e60eb43c3f1bed2 # 3.15140984357495864573e-08
.quad 0x03e5faf06ecb35c84 # 2.95077445089736670973e-08
.quad 0x03e4ef1e63db35f68 # 1.44098510263167149349e-08
.quad 0x03e469743fb1a71a5 # 1.05196987538551827693e-08
.quad 0x03e6c1cdf404e5796 # 5.23641361722697546261e-08
.quad 0x03e4094aa0ada625e # 7.72099925253243069458e-09
.quad 0x03e6e2d4c96fde3ec # 5.62089493829364197156e-08
.quad 0x03e62f4d5e9a98f34 # 3.53090261098577946927e-08
.quad 0x03e6467c96ecc5cbe # 3.80080516835568242269e-08
.quad 0x03e6e7040d03dec5a # 5.66961038386146408282e-08
.quad 0x03e67bebf4282de36 # 4.42287063097349852717e-08
.quad 0x03e6289b11aeb783f # 3.45294525105681104660e-08
.quad 0x03e5a891d1772f538 # 2.47132034530447431509e-08
.quad 0x03e634f10be1fb591 # 3.59655343422487209774e-08
.quad 0x03e6d9ce1d316eb93 # 5.51581770357780862071e-08
.quad 0x03e63562a19a9c442 # 3.60171867511861372793e-08
.quad 0x03e54e2adf548084c # 1.94511067964296180547e-08
.quad 0x03e508ce55cc8c97a # 1.54137376631349347838e-08
.quad 0x03e30e2f613e85bda # 3.93171034490174464173e-09
.quad 0x03e6db03ebb0227bf # 5.52990607758839766440e-08
.quad 0x03e61b75bb09cb098 # 3.29990737637586136511e-08
.quad 0x03e496f16abb9df22 # 1.18436010922446096216e-08
.quad 0x03e65b3f399411c62 # 4.04248680368301346709e-08
.quad 0x03e586b3e59f65355 # 2.27418915900284316293e-08
.quad 0x03e52482ceae1ac12 # 1.70263791333409206020e-08
.quad 0x03e6efa39ef35793c # 5.76999904754328540596e-08
.quad 0 # for alignment