forked from simdjson/simdjson
-
Notifications
You must be signed in to change notification settings - Fork 0
/
simdjson.cpp
15982 lines (14436 loc) · 648 KB
/
simdjson.cpp
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
/* auto-generated on 2022-11-23 10:31:42 -0500. Do not edit! */
/* begin file src/simdjson.cpp */
#include "simdjson.h"
SIMDJSON_PUSH_DISABLE_WARNINGS
SIMDJSON_DISABLE_UNDESIRED_WARNINGS
/* begin file src/to_chars.cpp */
#include <cstring>
#include <cstdint>
#include <array>
#include <cmath>
namespace simdjson {
namespace internal {
/*!
implements the Grisu2 algorithm for binary to decimal floating-point
conversion.
Adapted from JSON for Modern C++
This implementation is a slightly modified version of the reference
implementation which may be obtained from
http://florian.loitsch.com/publications (bench.tar.gz).
The code is distributed under the MIT license, Copyright (c) 2009 Florian
Loitsch. For a detailed description of the algorithm see: [1] Loitsch, "Printing
Floating-Point Numbers Quickly and Accurately with Integers", Proceedings of the
ACM SIGPLAN 2010 Conference on Programming Language Design and Implementation,
PLDI 2010 [2] Burger, Dybvig, "Printing Floating-Point Numbers Quickly and
Accurately", Proceedings of the ACM SIGPLAN 1996 Conference on Programming
Language Design and Implementation, PLDI 1996
*/
namespace dtoa_impl {
template <typename Target, typename Source>
Target reinterpret_bits(const Source source) {
static_assert(sizeof(Target) == sizeof(Source), "size mismatch");
Target target;
std::memcpy(&target, &source, sizeof(Source));
return target;
}
struct diyfp // f * 2^e
{
static constexpr int kPrecision = 64; // = q
std::uint64_t f = 0;
int e = 0;
constexpr diyfp(std::uint64_t f_, int e_) noexcept : f(f_), e(e_) {}
/*!
@brief returns x - y
@pre x.e == y.e and x.f >= y.f
*/
static diyfp sub(const diyfp &x, const diyfp &y) noexcept {
return {x.f - y.f, x.e};
}
/*!
@brief returns x * y
@note The result is rounded. (Only the upper q bits are returned.)
*/
static diyfp mul(const diyfp &x, const diyfp &y) noexcept {
static_assert(kPrecision == 64, "internal error");
// Computes:
// f = round((x.f * y.f) / 2^q)
// e = x.e + y.e + q
// Emulate the 64-bit * 64-bit multiplication:
//
// p = u * v
// = (u_lo + 2^32 u_hi) (v_lo + 2^32 v_hi)
// = (u_lo v_lo ) + 2^32 ((u_lo v_hi ) + (u_hi v_lo )) +
// 2^64 (u_hi v_hi ) = (p0 ) + 2^32 ((p1 ) + (p2 ))
// + 2^64 (p3 ) = (p0_lo + 2^32 p0_hi) + 2^32 ((p1_lo +
// 2^32 p1_hi) + (p2_lo + 2^32 p2_hi)) + 2^64 (p3 ) =
// (p0_lo ) + 2^32 (p0_hi + p1_lo + p2_lo ) + 2^64 (p1_hi +
// p2_hi + p3) = (p0_lo ) + 2^32 (Q ) + 2^64 (H ) = (p0_lo ) +
// 2^32 (Q_lo + 2^32 Q_hi ) + 2^64 (H )
//
// (Since Q might be larger than 2^32 - 1)
//
// = (p0_lo + 2^32 Q_lo) + 2^64 (Q_hi + H)
//
// (Q_hi + H does not overflow a 64-bit int)
//
// = p_lo + 2^64 p_hi
const std::uint64_t u_lo = x.f & 0xFFFFFFFFu;
const std::uint64_t u_hi = x.f >> 32u;
const std::uint64_t v_lo = y.f & 0xFFFFFFFFu;
const std::uint64_t v_hi = y.f >> 32u;
const std::uint64_t p0 = u_lo * v_lo;
const std::uint64_t p1 = u_lo * v_hi;
const std::uint64_t p2 = u_hi * v_lo;
const std::uint64_t p3 = u_hi * v_hi;
const std::uint64_t p0_hi = p0 >> 32u;
const std::uint64_t p1_lo = p1 & 0xFFFFFFFFu;
const std::uint64_t p1_hi = p1 >> 32u;
const std::uint64_t p2_lo = p2 & 0xFFFFFFFFu;
const std::uint64_t p2_hi = p2 >> 32u;
std::uint64_t Q = p0_hi + p1_lo + p2_lo;
// The full product might now be computed as
//
// p_hi = p3 + p2_hi + p1_hi + (Q >> 32)
// p_lo = p0_lo + (Q << 32)
//
// But in this particular case here, the full p_lo is not required.
// Effectively we only need to add the highest bit in p_lo to p_hi (and
// Q_hi + 1 does not overflow).
Q += std::uint64_t{1} << (64u - 32u - 1u); // round, ties up
const std::uint64_t h = p3 + p2_hi + p1_hi + (Q >> 32u);
return {h, x.e + y.e + 64};
}
/*!
@brief normalize x such that the significand is >= 2^(q-1)
@pre x.f != 0
*/
static diyfp normalize(diyfp x) noexcept {
while ((x.f >> 63u) == 0) {
x.f <<= 1u;
x.e--;
}
return x;
}
/*!
@brief normalize x such that the result has the exponent E
@pre e >= x.e and the upper e - x.e bits of x.f must be zero.
*/
static diyfp normalize_to(const diyfp &x,
const int target_exponent) noexcept {
const int delta = x.e - target_exponent;
return {x.f << delta, target_exponent};
}
};
struct boundaries {
diyfp w;
diyfp minus;
diyfp plus;
};
/*!
Compute the (normalized) diyfp representing the input number 'value' and its
boundaries.
@pre value must be finite and positive
*/
template <typename FloatType> boundaries compute_boundaries(FloatType value) {
// Convert the IEEE representation into a diyfp.
//
// If v is denormal:
// value = 0.F * 2^(1 - bias) = ( F) * 2^(1 - bias - (p-1))
// If v is normalized:
// value = 1.F * 2^(E - bias) = (2^(p-1) + F) * 2^(E - bias - (p-1))
static_assert(std::numeric_limits<FloatType>::is_iec559,
"internal error: dtoa_short requires an IEEE-754 "
"floating-point implementation");
constexpr int kPrecision =
std::numeric_limits<FloatType>::digits; // = p (includes the hidden bit)
constexpr int kBias =
std::numeric_limits<FloatType>::max_exponent - 1 + (kPrecision - 1);
constexpr int kMinExp = 1 - kBias;
constexpr std::uint64_t kHiddenBit = std::uint64_t{1}
<< (kPrecision - 1); // = 2^(p-1)
using bits_type = typename std::conditional<kPrecision == 24, std::uint32_t,
std::uint64_t>::type;
const std::uint64_t bits = reinterpret_bits<bits_type>(value);
const std::uint64_t E = bits >> (kPrecision - 1);
const std::uint64_t F = bits & (kHiddenBit - 1);
const bool is_denormal = E == 0;
const diyfp v = is_denormal
? diyfp(F, kMinExp)
: diyfp(F + kHiddenBit, static_cast<int>(E) - kBias);
// Compute the boundaries m- and m+ of the floating-point value
// v = f * 2^e.
//
// Determine v- and v+, the floating-point predecessor and successor if v,
// respectively.
//
// v- = v - 2^e if f != 2^(p-1) or e == e_min (A)
// = v - 2^(e-1) if f == 2^(p-1) and e > e_min (B)
//
// v+ = v + 2^e
//
// Let m- = (v- + v) / 2 and m+ = (v + v+) / 2. All real numbers _strictly_
// between m- and m+ round to v, regardless of how the input rounding
// algorithm breaks ties.
//
// ---+-------------+-------------+-------------+-------------+--- (A)
// v- m- v m+ v+
//
// -----------------+------+------+-------------+-------------+--- (B)
// v- m- v m+ v+
const bool lower_boundary_is_closer = F == 0 && E > 1;
const diyfp m_plus = diyfp(2 * v.f + 1, v.e - 1);
const diyfp m_minus = lower_boundary_is_closer
? diyfp(4 * v.f - 1, v.e - 2) // (B)
: diyfp(2 * v.f - 1, v.e - 1); // (A)
// Determine the normalized w+ = m+.
const diyfp w_plus = diyfp::normalize(m_plus);
// Determine w- = m- such that e_(w-) = e_(w+).
const diyfp w_minus = diyfp::normalize_to(m_minus, w_plus.e);
return {diyfp::normalize(v), w_minus, w_plus};
}
// Given normalized diyfp w, Grisu needs to find a (normalized) cached
// power-of-ten c, such that the exponent of the product c * w = f * 2^e lies
// within a certain range [alpha, gamma] (Definition 3.2 from [1])
//
// alpha <= e = e_c + e_w + q <= gamma
//
// or
//
// f_c * f_w * 2^alpha <= f_c 2^(e_c) * f_w 2^(e_w) * 2^q
// <= f_c * f_w * 2^gamma
//
// Since c and w are normalized, i.e. 2^(q-1) <= f < 2^q, this implies
//
// 2^(q-1) * 2^(q-1) * 2^alpha <= c * w * 2^q < 2^q * 2^q * 2^gamma
//
// or
//
// 2^(q - 2 + alpha) <= c * w < 2^(q + gamma)
//
// The choice of (alpha,gamma) determines the size of the table and the form of
// the digit generation procedure. Using (alpha,gamma)=(-60,-32) works out well
// in practice:
//
// The idea is to cut the number c * w = f * 2^e into two parts, which can be
// processed independently: An integral part p1, and a fractional part p2:
//
// f * 2^e = ( (f div 2^-e) * 2^-e + (f mod 2^-e) ) * 2^e
// = (f div 2^-e) + (f mod 2^-e) * 2^e
// = p1 + p2 * 2^e
//
// The conversion of p1 into decimal form requires a series of divisions and
// modulos by (a power of) 10. These operations are faster for 32-bit than for
// 64-bit integers, so p1 should ideally fit into a 32-bit integer. This can be
// achieved by choosing
//
// -e >= 32 or e <= -32 := gamma
//
// In order to convert the fractional part
//
// p2 * 2^e = p2 / 2^-e = d[-1] / 10^1 + d[-2] / 10^2 + ...
//
// into decimal form, the fraction is repeatedly multiplied by 10 and the digits
// d[-i] are extracted in order:
//
// (10 * p2) div 2^-e = d[-1]
// (10 * p2) mod 2^-e = d[-2] / 10^1 + ...
//
// The multiplication by 10 must not overflow. It is sufficient to choose
//
// 10 * p2 < 16 * p2 = 2^4 * p2 <= 2^64.
//
// Since p2 = f mod 2^-e < 2^-e,
//
// -e <= 60 or e >= -60 := alpha
constexpr int kAlpha = -60;
constexpr int kGamma = -32;
struct cached_power // c = f * 2^e ~= 10^k
{
std::uint64_t f;
int e;
int k;
};
/*!
For a normalized diyfp w = f * 2^e, this function returns a (normalized) cached
power-of-ten c = f_c * 2^e_c, such that the exponent of the product w * c
satisfies (Definition 3.2 from [1])
alpha <= e_c + e + q <= gamma.
*/
inline cached_power get_cached_power_for_binary_exponent(int e) {
// Now
//
// alpha <= e_c + e + q <= gamma (1)
// ==> f_c * 2^alpha <= c * 2^e * 2^q
//
// and since the c's are normalized, 2^(q-1) <= f_c,
//
// ==> 2^(q - 1 + alpha) <= c * 2^(e + q)
// ==> 2^(alpha - e - 1) <= c
//
// If c were an exact power of ten, i.e. c = 10^k, one may determine k as
//
// k = ceil( log_10( 2^(alpha - e - 1) ) )
// = ceil( (alpha - e - 1) * log_10(2) )
//
// From the paper:
// "In theory the result of the procedure could be wrong since c is rounded,
// and the computation itself is approximated [...]. In practice, however,
// this simple function is sufficient."
//
// For IEEE double precision floating-point numbers converted into
// normalized diyfp's w = f * 2^e, with q = 64,
//
// e >= -1022 (min IEEE exponent)
// -52 (p - 1)
// -52 (p - 1, possibly normalize denormal IEEE numbers)
// -11 (normalize the diyfp)
// = -1137
//
// and
//
// e <= +1023 (max IEEE exponent)
// -52 (p - 1)
// -11 (normalize the diyfp)
// = 960
//
// This binary exponent range [-1137,960] results in a decimal exponent
// range [-307,324]. One does not need to store a cached power for each
// k in this range. For each such k it suffices to find a cached power
// such that the exponent of the product lies in [alpha,gamma].
// This implies that the difference of the decimal exponents of adjacent
// table entries must be less than or equal to
//
// floor( (gamma - alpha) * log_10(2) ) = 8.
//
// (A smaller distance gamma-alpha would require a larger table.)
// NB:
// Actually this function returns c, such that -60 <= e_c + e + 64 <= -34.
constexpr int kCachedPowersMinDecExp = -300;
constexpr int kCachedPowersDecStep = 8;
static constexpr std::array<cached_power, 79> kCachedPowers = {{
{0xAB70FE17C79AC6CA, -1060, -300}, {0xFF77B1FCBEBCDC4F, -1034, -292},
{0xBE5691EF416BD60C, -1007, -284}, {0x8DD01FAD907FFC3C, -980, -276},
{0xD3515C2831559A83, -954, -268}, {0x9D71AC8FADA6C9B5, -927, -260},
{0xEA9C227723EE8BCB, -901, -252}, {0xAECC49914078536D, -874, -244},
{0x823C12795DB6CE57, -847, -236}, {0xC21094364DFB5637, -821, -228},
{0x9096EA6F3848984F, -794, -220}, {0xD77485CB25823AC7, -768, -212},
{0xA086CFCD97BF97F4, -741, -204}, {0xEF340A98172AACE5, -715, -196},
{0xB23867FB2A35B28E, -688, -188}, {0x84C8D4DFD2C63F3B, -661, -180},
{0xC5DD44271AD3CDBA, -635, -172}, {0x936B9FCEBB25C996, -608, -164},
{0xDBAC6C247D62A584, -582, -156}, {0xA3AB66580D5FDAF6, -555, -148},
{0xF3E2F893DEC3F126, -529, -140}, {0xB5B5ADA8AAFF80B8, -502, -132},
{0x87625F056C7C4A8B, -475, -124}, {0xC9BCFF6034C13053, -449, -116},
{0x964E858C91BA2655, -422, -108}, {0xDFF9772470297EBD, -396, -100},
{0xA6DFBD9FB8E5B88F, -369, -92}, {0xF8A95FCF88747D94, -343, -84},
{0xB94470938FA89BCF, -316, -76}, {0x8A08F0F8BF0F156B, -289, -68},
{0xCDB02555653131B6, -263, -60}, {0x993FE2C6D07B7FAC, -236, -52},
{0xE45C10C42A2B3B06, -210, -44}, {0xAA242499697392D3, -183, -36},
{0xFD87B5F28300CA0E, -157, -28}, {0xBCE5086492111AEB, -130, -20},
{0x8CBCCC096F5088CC, -103, -12}, {0xD1B71758E219652C, -77, -4},
{0x9C40000000000000, -50, 4}, {0xE8D4A51000000000, -24, 12},
{0xAD78EBC5AC620000, 3, 20}, {0x813F3978F8940984, 30, 28},
{0xC097CE7BC90715B3, 56, 36}, {0x8F7E32CE7BEA5C70, 83, 44},
{0xD5D238A4ABE98068, 109, 52}, {0x9F4F2726179A2245, 136, 60},
{0xED63A231D4C4FB27, 162, 68}, {0xB0DE65388CC8ADA8, 189, 76},
{0x83C7088E1AAB65DB, 216, 84}, {0xC45D1DF942711D9A, 242, 92},
{0x924D692CA61BE758, 269, 100}, {0xDA01EE641A708DEA, 295, 108},
{0xA26DA3999AEF774A, 322, 116}, {0xF209787BB47D6B85, 348, 124},
{0xB454E4A179DD1877, 375, 132}, {0x865B86925B9BC5C2, 402, 140},
{0xC83553C5C8965D3D, 428, 148}, {0x952AB45CFA97A0B3, 455, 156},
{0xDE469FBD99A05FE3, 481, 164}, {0xA59BC234DB398C25, 508, 172},
{0xF6C69A72A3989F5C, 534, 180}, {0xB7DCBF5354E9BECE, 561, 188},
{0x88FCF317F22241E2, 588, 196}, {0xCC20CE9BD35C78A5, 614, 204},
{0x98165AF37B2153DF, 641, 212}, {0xE2A0B5DC971F303A, 667, 220},
{0xA8D9D1535CE3B396, 694, 228}, {0xFB9B7CD9A4A7443C, 720, 236},
{0xBB764C4CA7A44410, 747, 244}, {0x8BAB8EEFB6409C1A, 774, 252},
{0xD01FEF10A657842C, 800, 260}, {0x9B10A4E5E9913129, 827, 268},
{0xE7109BFBA19C0C9D, 853, 276}, {0xAC2820D9623BF429, 880, 284},
{0x80444B5E7AA7CF85, 907, 292}, {0xBF21E44003ACDD2D, 933, 300},
{0x8E679C2F5E44FF8F, 960, 308}, {0xD433179D9C8CB841, 986, 316},
{0x9E19DB92B4E31BA9, 1013, 324},
}};
// This computation gives exactly the same results for k as
// k = ceil((kAlpha - e - 1) * 0.30102999566398114)
// for |e| <= 1500, but doesn't require floating-point operations.
// NB: log_10(2) ~= 78913 / 2^18
const int f = kAlpha - e - 1;
const int k = (f * 78913) / (1 << 18) + static_cast<int>(f > 0);
const int index = (-kCachedPowersMinDecExp + k + (kCachedPowersDecStep - 1)) /
kCachedPowersDecStep;
const cached_power cached = kCachedPowers[static_cast<std::size_t>(index)];
return cached;
}
/*!
For n != 0, returns k, such that pow10 := 10^(k-1) <= n < 10^k.
For n == 0, returns 1 and sets pow10 := 1.
*/
inline int find_largest_pow10(const std::uint32_t n, std::uint32_t &pow10) {
// LCOV_EXCL_START
if (n >= 1000000000) {
pow10 = 1000000000;
return 10;
}
// LCOV_EXCL_STOP
else if (n >= 100000000) {
pow10 = 100000000;
return 9;
} else if (n >= 10000000) {
pow10 = 10000000;
return 8;
} else if (n >= 1000000) {
pow10 = 1000000;
return 7;
} else if (n >= 100000) {
pow10 = 100000;
return 6;
} else if (n >= 10000) {
pow10 = 10000;
return 5;
} else if (n >= 1000) {
pow10 = 1000;
return 4;
} else if (n >= 100) {
pow10 = 100;
return 3;
} else if (n >= 10) {
pow10 = 10;
return 2;
} else {
pow10 = 1;
return 1;
}
}
inline void grisu2_round(char *buf, int len, std::uint64_t dist,
std::uint64_t delta, std::uint64_t rest,
std::uint64_t ten_k) {
// <--------------------------- delta ---->
// <---- dist --------->
// --------------[------------------+-------------------]--------------
// M- w M+
//
// ten_k
// <------>
// <---- rest ---->
// --------------[------------------+----+--------------]--------------
// w V
// = buf * 10^k
//
// ten_k represents a unit-in-the-last-place in the decimal representation
// stored in buf.
// Decrement buf by ten_k while this takes buf closer to w.
// The tests are written in this order to avoid overflow in unsigned
// integer arithmetic.
while (rest < dist && delta - rest >= ten_k &&
(rest + ten_k < dist || dist - rest > rest + ten_k - dist)) {
buf[len - 1]--;
rest += ten_k;
}
}
/*!
Generates V = buffer * 10^decimal_exponent, such that M- <= V <= M+.
M- and M+ must be normalized and share the same exponent -60 <= e <= -32.
*/
inline void grisu2_digit_gen(char *buffer, int &length, int &decimal_exponent,
diyfp M_minus, diyfp w, diyfp M_plus) {
static_assert(kAlpha >= -60, "internal error");
static_assert(kGamma <= -32, "internal error");
// Generates the digits (and the exponent) of a decimal floating-point
// number V = buffer * 10^decimal_exponent in the range [M-, M+]. The diyfp's
// w, M- and M+ share the same exponent e, which satisfies alpha <= e <=
// gamma.
//
// <--------------------------- delta ---->
// <---- dist --------->
// --------------[------------------+-------------------]--------------
// M- w M+
//
// Grisu2 generates the digits of M+ from left to right and stops as soon as
// V is in [M-,M+].
std::uint64_t delta =
diyfp::sub(M_plus, M_minus)
.f; // (significand of (M+ - M-), implicit exponent is e)
std::uint64_t dist =
diyfp::sub(M_plus, w)
.f; // (significand of (M+ - w ), implicit exponent is e)
// Split M+ = f * 2^e into two parts p1 and p2 (note: e < 0):
//
// M+ = f * 2^e
// = ((f div 2^-e) * 2^-e + (f mod 2^-e)) * 2^e
// = ((p1 ) * 2^-e + (p2 )) * 2^e
// = p1 + p2 * 2^e
const diyfp one(std::uint64_t{1} << -M_plus.e, M_plus.e);
auto p1 = static_cast<std::uint32_t>(
M_plus.f >>
-one.e); // p1 = f div 2^-e (Since -e >= 32, p1 fits into a 32-bit int.)
std::uint64_t p2 = M_plus.f & (one.f - 1); // p2 = f mod 2^-e
// 1)
//
// Generate the digits of the integral part p1 = d[n-1]...d[1]d[0]
std::uint32_t pow10;
const int k = find_largest_pow10(p1, pow10);
// 10^(k-1) <= p1 < 10^k, pow10 = 10^(k-1)
//
// p1 = (p1 div 10^(k-1)) * 10^(k-1) + (p1 mod 10^(k-1))
// = (d[k-1] ) * 10^(k-1) + (p1 mod 10^(k-1))
//
// M+ = p1 + p2 * 2^e
// = d[k-1] * 10^(k-1) + (p1 mod 10^(k-1)) + p2 * 2^e
// = d[k-1] * 10^(k-1) + ((p1 mod 10^(k-1)) * 2^-e + p2) * 2^e
// = d[k-1] * 10^(k-1) + ( rest) * 2^e
//
// Now generate the digits d[n] of p1 from left to right (n = k-1,...,0)
//
// p1 = d[k-1]...d[n] * 10^n + d[n-1]...d[0]
//
// but stop as soon as
//
// rest * 2^e = (d[n-1]...d[0] * 2^-e + p2) * 2^e <= delta * 2^e
int n = k;
while (n > 0) {
// Invariants:
// M+ = buffer * 10^n + (p1 + p2 * 2^e) (buffer = 0 for n = k)
// pow10 = 10^(n-1) <= p1 < 10^n
//
const std::uint32_t d = p1 / pow10; // d = p1 div 10^(n-1)
const std::uint32_t r = p1 % pow10; // r = p1 mod 10^(n-1)
//
// M+ = buffer * 10^n + (d * 10^(n-1) + r) + p2 * 2^e
// = (buffer * 10 + d) * 10^(n-1) + (r + p2 * 2^e)
//
buffer[length++] = static_cast<char>('0' + d); // buffer := buffer * 10 + d
//
// M+ = buffer * 10^(n-1) + (r + p2 * 2^e)
//
p1 = r;
n--;
//
// M+ = buffer * 10^n + (p1 + p2 * 2^e)
// pow10 = 10^n
//
// Now check if enough digits have been generated.
// Compute
//
// p1 + p2 * 2^e = (p1 * 2^-e + p2) * 2^e = rest * 2^e
//
// Note:
// Since rest and delta share the same exponent e, it suffices to
// compare the significands.
const std::uint64_t rest = (std::uint64_t{p1} << -one.e) + p2;
if (rest <= delta) {
// V = buffer * 10^n, with M- <= V <= M+.
decimal_exponent += n;
// We may now just stop. But instead look if the buffer could be
// decremented to bring V closer to w.
//
// pow10 = 10^n is now 1 ulp in the decimal representation V.
// The rounding procedure works with diyfp's with an implicit
// exponent of e.
//
// 10^n = (10^n * 2^-e) * 2^e = ulp * 2^e
//
const std::uint64_t ten_n = std::uint64_t{pow10} << -one.e;
grisu2_round(buffer, length, dist, delta, rest, ten_n);
return;
}
pow10 /= 10;
//
// pow10 = 10^(n-1) <= p1 < 10^n
// Invariants restored.
}
// 2)
//
// The digits of the integral part have been generated:
//
// M+ = d[k-1]...d[1]d[0] + p2 * 2^e
// = buffer + p2 * 2^e
//
// Now generate the digits of the fractional part p2 * 2^e.
//
// Note:
// No decimal point is generated: the exponent is adjusted instead.
//
// p2 actually represents the fraction
//
// p2 * 2^e
// = p2 / 2^-e
// = d[-1] / 10^1 + d[-2] / 10^2 + ...
//
// Now generate the digits d[-m] of p1 from left to right (m = 1,2,...)
//
// p2 * 2^e = d[-1]d[-2]...d[-m] * 10^-m
// + 10^-m * (d[-m-1] / 10^1 + d[-m-2] / 10^2 + ...)
//
// using
//
// 10^m * p2 = ((10^m * p2) div 2^-e) * 2^-e + ((10^m * p2) mod 2^-e)
// = ( d) * 2^-e + ( r)
//
// or
// 10^m * p2 * 2^e = d + r * 2^e
//
// i.e.
//
// M+ = buffer + p2 * 2^e
// = buffer + 10^-m * (d + r * 2^e)
// = (buffer * 10^m + d) * 10^-m + 10^-m * r * 2^e
//
// and stop as soon as 10^-m * r * 2^e <= delta * 2^e
int m = 0;
for (;;) {
// Invariant:
// M+ = buffer * 10^-m + 10^-m * (d[-m-1] / 10 + d[-m-2] / 10^2 + ...)
// * 2^e
// = buffer * 10^-m + 10^-m * (p2 )
// * 2^e = buffer * 10^-m + 10^-m * (1/10 * (10 * p2) ) * 2^e =
// buffer * 10^-m + 10^-m * (1/10 * ((10*p2 div 2^-e) * 2^-e +
// (10*p2 mod 2^-e)) * 2^e
//
p2 *= 10;
const std::uint64_t d = p2 >> -one.e; // d = (10 * p2) div 2^-e
const std::uint64_t r = p2 & (one.f - 1); // r = (10 * p2) mod 2^-e
//
// M+ = buffer * 10^-m + 10^-m * (1/10 * (d * 2^-e + r) * 2^e
// = buffer * 10^-m + 10^-m * (1/10 * (d + r * 2^e))
// = (buffer * 10 + d) * 10^(-m-1) + 10^(-m-1) * r * 2^e
//
buffer[length++] = static_cast<char>('0' + d); // buffer := buffer * 10 + d
//
// M+ = buffer * 10^(-m-1) + 10^(-m-1) * r * 2^e
//
p2 = r;
m++;
//
// M+ = buffer * 10^-m + 10^-m * p2 * 2^e
// Invariant restored.
// Check if enough digits have been generated.
//
// 10^-m * p2 * 2^e <= delta * 2^e
// p2 * 2^e <= 10^m * delta * 2^e
// p2 <= 10^m * delta
delta *= 10;
dist *= 10;
if (p2 <= delta) {
break;
}
}
// V = buffer * 10^-m, with M- <= V <= M+.
decimal_exponent -= m;
// 1 ulp in the decimal representation is now 10^-m.
// Since delta and dist are now scaled by 10^m, we need to do the
// same with ulp in order to keep the units in sync.
//
// 10^m * 10^-m = 1 = 2^-e * 2^e = ten_m * 2^e
//
const std::uint64_t ten_m = one.f;
grisu2_round(buffer, length, dist, delta, p2, ten_m);
// By construction this algorithm generates the shortest possible decimal
// number (Loitsch, Theorem 6.2) which rounds back to w.
// For an input number of precision p, at least
//
// N = 1 + ceil(p * log_10(2))
//
// decimal digits are sufficient to identify all binary floating-point
// numbers (Matula, "In-and-Out conversions").
// This implies that the algorithm does not produce more than N decimal
// digits.
//
// N = 17 for p = 53 (IEEE double precision)
// N = 9 for p = 24 (IEEE single precision)
}
/*!
v = buf * 10^decimal_exponent
len is the length of the buffer (number of decimal digits)
The buffer must be large enough, i.e. >= max_digits10.
*/
inline void grisu2(char *buf, int &len, int &decimal_exponent, diyfp m_minus,
diyfp v, diyfp m_plus) {
// --------(-----------------------+-----------------------)-------- (A)
// m- v m+
//
// --------------------(-----------+-----------------------)-------- (B)
// m- v m+
//
// First scale v (and m- and m+) such that the exponent is in the range
// [alpha, gamma].
const cached_power cached = get_cached_power_for_binary_exponent(m_plus.e);
const diyfp c_minus_k(cached.f, cached.e); // = c ~= 10^-k
// The exponent of the products is = v.e + c_minus_k.e + q and is in the range
// [alpha,gamma]
const diyfp w = diyfp::mul(v, c_minus_k);
const diyfp w_minus = diyfp::mul(m_minus, c_minus_k);
const diyfp w_plus = diyfp::mul(m_plus, c_minus_k);
// ----(---+---)---------------(---+---)---------------(---+---)----
// w- w w+
// = c*m- = c*v = c*m+
//
// diyfp::mul rounds its result and c_minus_k is approximated too. w, w- and
// w+ are now off by a small amount.
// In fact:
//
// w - v * 10^k < 1 ulp
//
// To account for this inaccuracy, add resp. subtract 1 ulp.
//
// --------+---[---------------(---+---)---------------]---+--------
// w- M- w M+ w+
//
// Now any number in [M-, M+] (bounds included) will round to w when input,
// regardless of how the input rounding algorithm breaks ties.
//
// And digit_gen generates the shortest possible such number in [M-, M+].
// Note that this does not mean that Grisu2 always generates the shortest
// possible number in the interval (m-, m+).
const diyfp M_minus(w_minus.f + 1, w_minus.e);
const diyfp M_plus(w_plus.f - 1, w_plus.e);
decimal_exponent = -cached.k; // = -(-k) = k
grisu2_digit_gen(buf, len, decimal_exponent, M_minus, w, M_plus);
}
/*!
v = buf * 10^decimal_exponent
len is the length of the buffer (number of decimal digits)
The buffer must be large enough, i.e. >= max_digits10.
*/
template <typename FloatType>
void grisu2(char *buf, int &len, int &decimal_exponent, FloatType value) {
static_assert(diyfp::kPrecision >= std::numeric_limits<FloatType>::digits + 3,
"internal error: not enough precision");
// If the neighbors (and boundaries) of 'value' are always computed for
// double-precision numbers, all float's can be recovered using strtod (and
// strtof). However, the resulting decimal representations are not exactly
// "short".
//
// The documentation for 'std::to_chars'
// (https://en.cppreference.com/w/cpp/utility/to_chars) says "value is
// converted to a string as if by std::sprintf in the default ("C") locale"
// and since sprintf promotes float's to double's, I think this is exactly
// what 'std::to_chars' does. On the other hand, the documentation for
// 'std::to_chars' requires that "parsing the representation using the
// corresponding std::from_chars function recovers value exactly". That
// indicates that single precision floating-point numbers should be recovered
// using 'std::strtof'.
//
// NB: If the neighbors are computed for single-precision numbers, there is a
// single float
// (7.0385307e-26f) which can't be recovered using strtod. The resulting
// double precision value is off by 1 ulp.
#if 0
const boundaries w = compute_boundaries(static_cast<double>(value));
#else
const boundaries w = compute_boundaries(value);
#endif
grisu2(buf, len, decimal_exponent, w.minus, w.w, w.plus);
}
/*!
@brief appends a decimal representation of e to buf
@return a pointer to the element following the exponent.
@pre -1000 < e < 1000
*/
inline char *append_exponent(char *buf, int e) {
if (e < 0) {
e = -e;
*buf++ = '-';
} else {
*buf++ = '+';
}
auto k = static_cast<std::uint32_t>(e);
if (k < 10) {
// Always print at least two digits in the exponent.
// This is for compatibility with printf("%g").
*buf++ = '0';
*buf++ = static_cast<char>('0' + k);
} else if (k < 100) {
*buf++ = static_cast<char>('0' + k / 10);
k %= 10;
*buf++ = static_cast<char>('0' + k);
} else {
*buf++ = static_cast<char>('0' + k / 100);
k %= 100;
*buf++ = static_cast<char>('0' + k / 10);
k %= 10;
*buf++ = static_cast<char>('0' + k);
}
return buf;
}
/*!
@brief prettify v = buf * 10^decimal_exponent
If v is in the range [10^min_exp, 10^max_exp) it will be printed in fixed-point
notation. Otherwise it will be printed in exponential notation.
@pre min_exp < 0
@pre max_exp > 0
*/
inline char *format_buffer(char *buf, int len, int decimal_exponent,
int min_exp, int max_exp) {
const int k = len;
const int n = len + decimal_exponent;
// v = buf * 10^(n-k)
// k is the length of the buffer (number of decimal digits)
// n is the position of the decimal point relative to the start of the buffer.
if (k <= n && n <= max_exp) {
// digits[000]
// len <= max_exp + 2
std::memset(buf + k, '0', static_cast<size_t>(n) - static_cast<size_t>(k));
// Make it look like a floating-point number (#362, #378)
buf[n + 0] = '.';
buf[n + 1] = '0';
return buf + (static_cast<size_t>(n)) + 2;
}
if (0 < n && n <= max_exp) {
// dig.its
// len <= max_digits10 + 1
std::memmove(buf + (static_cast<size_t>(n) + 1), buf + n,
static_cast<size_t>(k) - static_cast<size_t>(n));
buf[n] = '.';
return buf + (static_cast<size_t>(k) + 1U);
}
if (min_exp < n && n <= 0) {
// 0.[000]digits
// len <= 2 + (-min_exp - 1) + max_digits10
std::memmove(buf + (2 + static_cast<size_t>(-n)), buf,
static_cast<size_t>(k));
buf[0] = '0';
buf[1] = '.';
std::memset(buf + 2, '0', static_cast<size_t>(-n));
return buf + (2U + static_cast<size_t>(-n) + static_cast<size_t>(k));
}
if (k == 1) {
// dE+123
// len <= 1 + 5
buf += 1;
} else {
// d.igitsE+123
// len <= max_digits10 + 1 + 5
std::memmove(buf + 2, buf + 1, static_cast<size_t>(k) - 1);
buf[1] = '.';
buf += 1 + static_cast<size_t>(k);
}
*buf++ = 'e';
return append_exponent(buf, n - 1);
}
} // namespace dtoa_impl
/*!
The format of the resulting decimal representation is similar to printf's %g
format. Returns an iterator pointing past-the-end of the decimal representation.
@note The input number must be finite, i.e. NaN's and Inf's are not supported.
@note The buffer must be large enough.
@note The result is NOT null-terminated.
*/
char *to_chars(char *first, const char *last, double value) {
static_cast<void>(last); // maybe unused - fix warning
bool negative = std::signbit(value);
if (negative) {
value = -value;
*first++ = '-';
}
if (value == 0) // +-0
{
*first++ = '0';
// Make it look like a floating-point number (#362, #378)
*first++ = '.';
*first++ = '0';
return first;
}
// Compute v = buffer * 10^decimal_exponent.
// The decimal digits are stored in the buffer, which needs to be interpreted
// as an unsigned decimal integer.
// len is the length of the buffer, i.e. the number of decimal digits.
int len = 0;
int decimal_exponent = 0;
dtoa_impl::grisu2(first, len, decimal_exponent, value);
// Format the buffer like printf("%.*g", prec, value)
constexpr int kMinExp = -4;
constexpr int kMaxExp = std::numeric_limits<double>::digits10;
return dtoa_impl::format_buffer(first, len, decimal_exponent, kMinExp,
kMaxExp);
}
} // namespace internal
} // namespace simdjson
/* end file src/to_chars.cpp */
/* begin file src/from_chars.cpp */
#include <limits>
namespace simdjson {
namespace internal {
/**
* The code in the internal::from_chars function is meant to handle the floating-point number parsing
* when we have more than 19 digits in the decimal mantissa. This should only be seen
* in adversarial scenarios: we do not expect production systems to even produce
* such floating-point numbers.
*
* The parser is based on work by Nigel Tao (at https://github.com/google/wuffs/)
* who credits Ken Thompson for the design (via a reference to the Go source
* code). See
* https://github.com/google/wuffs/blob/aa46859ea40c72516deffa1b146121952d6dfd3b/internal/cgen/base/floatconv-submodule-data.c
* https://github.com/google/wuffs/blob/46cd8105f47ca07ae2ba8e6a7818ef9c0df6c152/internal/cgen/base/floatconv-submodule-code.c
* It is probably not very fast but it is a fallback that should almost never be
* called in real life. Google Wuffs is published under APL 2.0.
**/
namespace {
constexpr uint32_t max_digits = 768;
constexpr int32_t decimal_point_range = 2047;
} // namespace
struct adjusted_mantissa {
uint64_t mantissa;
int power2;
adjusted_mantissa() : mantissa(0), power2(0) {}
};
struct decimal {
uint32_t num_digits;
int32_t decimal_point;
bool negative;
bool truncated;
uint8_t digits[max_digits];
};
template <typename T> struct binary_format {
static constexpr int mantissa_explicit_bits();
static constexpr int minimum_exponent();
static constexpr int infinite_power();
static constexpr int sign_index();