1// SPDX-License-Identifier: Apache-2.0
2// ----------------------------------------------------------------------------
3// Copyright 2019-2022 Arm Limited
4// Copyright 2008 Jose Fonseca
5//
6// Licensed under the Apache License, Version 2.0 (the "License"); you may not
7// use this file except in compliance with the License. You may obtain a copy
8// of the License at:
9//
10// http://www.apache.org/licenses/LICENSE-2.0
11//
12// Unless required by applicable law or agreed to in writing, software
13// distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
14// WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
15// License for the specific language governing permissions and limitations
16// under the License.
17// ----------------------------------------------------------------------------
18
19/*
20 * This module implements vector support for floats, ints, and vector lane
21 * control masks. It provides access to both explicit vector width types, and
22 * flexible N-wide types where N can be determined at compile time.
23 *
24 * The design of this module encourages use of vector length agnostic code, via
25 * the vint, vfloat, and vmask types. These will take on the widest SIMD vector
26 * with that is available at compile time. The current vector width is
27 * accessible for e.g. loop strides via the ASTCENC_SIMD_WIDTH constant.
28 *
29 * Explicit scalar types are accessible via the vint1, vfloat1, vmask1 types.
30 * These are provided primarily for prototyping and algorithm debug of VLA
31 * implementations.
32 *
33 * Explicit 4-wide types are accessible via the vint4, vfloat4, and vmask4
34 * types. These are provided for use by VLA code, but are also expected to be
35 * used as a fixed-width type and will supported a reference C++ fallback for
36 * use on platforms without SIMD intrinsics.
37 *
38 * Explicit 8-wide types are accessible via the vint8, vfloat8, and vmask8
39 * types. These are provide for use by VLA code, and are not expected to be
40 * used as a fixed-width type in normal code. No reference C implementation is
41 * provided on platforms without underlying SIMD intrinsics.
42 *
43 * With the current implementation ISA support is provided for:
44 *
45 * * 1-wide for scalar reference.
46 * * 4-wide for Armv8-A NEON.
47 * * 4-wide for x86-64 SSE2.
48 * * 4-wide for x86-64 SSE4.1.
49 * * 8-wide for x86-64 AVX2.
50 */
51
52#ifndef ASTC_VECMATHLIB_H_INCLUDED
53#define ASTC_VECMATHLIB_H_INCLUDED
54
55#if ASTCENC_SSE != 0 || ASTCENC_AVX != 0
56 #include <immintrin.h>
57#elif ASTCENC_NEON != 0
58 #include <arm_neon.h>
59#endif
60
61#if !defined(__clang__) && defined(_MSC_VER)
62 #define ASTCENC_SIMD_INLINE __forceinline
63 #define ASTCENC_NO_INLINE
64#elif defined(__GNUC__) && !defined(__clang__)
65 #define ASTCENC_SIMD_INLINE __attribute__((always_inline)) inline
66 #define ASTCENC_NO_INLINE __attribute__ ((noinline))
67#else
68 #define ASTCENC_SIMD_INLINE __attribute__((always_inline, nodebug)) inline
69 #define ASTCENC_NO_INLINE __attribute__ ((noinline))
70#endif
71
72#if ASTCENC_AVX >= 2
73 /* If we have AVX2 expose 8-wide VLA. */
74 #include "astcenc_vecmathlib_sse_4.h"
75 #include "astcenc_vecmathlib_common_4.h"
76 #include "astcenc_vecmathlib_avx2_8.h"
77
78 #define ASTCENC_SIMD_WIDTH 8
79
80 using vfloat = vfloat8;
81
82 #if defined(ASTCENC_NO_INVARIANCE)
83 using vfloatacc = vfloat8;
84 #else
85 using vfloatacc = vfloat4;
86 #endif
87
88 using vint = vint8;
89 using vmask = vmask8;
90
91 constexpr auto loada = vfloat8::loada;
92 constexpr auto load1 = vfloat8::load1;
93
94#elif ASTCENC_SSE >= 20
95 /* If we have SSE expose 4-wide VLA, and 4-wide fixed width. */
96 #include "astcenc_vecmathlib_sse_4.h"
97 #include "astcenc_vecmathlib_common_4.h"
98
99 #define ASTCENC_SIMD_WIDTH 4
100
101 using vfloat = vfloat4;
102 using vfloatacc = vfloat4;
103 using vint = vint4;
104 using vmask = vmask4;
105
106 constexpr auto loada = vfloat4::loada;
107 constexpr auto load1 = vfloat4::load1;
108
109#elif ASTCENC_NEON > 0
110 /* If we have NEON expose 4-wide VLA. */
111 #include "astcenc_vecmathlib_neon_4.h"
112 #include "astcenc_vecmathlib_common_4.h"
113
114 #define ASTCENC_SIMD_WIDTH 4
115
116 using vfloat = vfloat4;
117 using vfloatacc = vfloat4;
118 using vint = vint4;
119 using vmask = vmask4;
120
121 constexpr auto loada = vfloat4::loada;
122 constexpr auto load1 = vfloat4::load1;
123
124#else
125 // If we have nothing expose 4-wide VLA, and 4-wide fixed width.
126
127 // Note: We no longer expose the 1-wide scalar fallback because it is not
128 // invariant with the 4-wide path due to algorithms that use horizontal
129 // operations that accumulate a local vector sum before accumulating into
130 // a running sum.
131 //
132 // For 4 items adding into an accumulator using 1-wide vectors the sum is:
133 //
134 // result = ((((sum + l0) + l1) + l2) + l3)
135 //
136 // ... whereas the accumulator for a 4-wide vector sum is:
137 //
138 // result = sum + ((l0 + l2) + (l1 + l3))
139 //
140 // In "normal maths" this is the same, but the floating point reassociation
141 // differences mean that these will not produce the same result.
142
143 #include "astcenc_vecmathlib_none_4.h"
144 #include "astcenc_vecmathlib_common_4.h"
145
146 #define ASTCENC_SIMD_WIDTH 4
147
148 using vfloat = vfloat4;
149 using vfloatacc = vfloat4;
150 using vint = vint4;
151 using vmask = vmask4;
152
153 constexpr auto loada = vfloat4::loada;
154 constexpr auto load1 = vfloat4::load1;
155#endif
156
157/**
158 * @brief Round a count down to the largest multiple of 8.
159 *
160 * @param count The unrounded value.
161 *
162 * @return The rounded value.
163 */
164ASTCENC_SIMD_INLINE unsigned int round_down_to_simd_multiple_8(unsigned int count)
165{
166 return count & static_cast<unsigned int>(~(8 - 1));
167}
168
169/**
170 * @brief Round a count down to the largest multiple of 4.
171 *
172 * @param count The unrounded value.
173 *
174 * @return The rounded value.
175 */
176ASTCENC_SIMD_INLINE unsigned int round_down_to_simd_multiple_4(unsigned int count)
177{
178 return count & static_cast<unsigned int>(~(4 - 1));
179}
180
181/**
182 * @brief Round a count down to the largest multiple of the SIMD width.
183 *
184 * Assumption that the vector width is a power of two ...
185 *
186 * @param count The unrounded value.
187 *
188 * @return The rounded value.
189 */
190ASTCENC_SIMD_INLINE unsigned int round_down_to_simd_multiple_vla(unsigned int count)
191{
192 return count & static_cast<unsigned int>(~(ASTCENC_SIMD_WIDTH - 1));
193}
194
195/**
196 * @brief Round a count up to the largest multiple of the SIMD width.
197 *
198 * Assumption that the vector width is a power of two ...
199 *
200 * @param count The unrounded value.
201 *
202 * @return The rounded value.
203 */
204ASTCENC_SIMD_INLINE unsigned int round_up_to_simd_multiple_vla(unsigned int count)
205{
206 unsigned int multiples = (count + ASTCENC_SIMD_WIDTH - 1) / ASTCENC_SIMD_WIDTH;
207 return multiples * ASTCENC_SIMD_WIDTH;
208}
209
210/**
211 * @brief Return @c a with lanes negated if the @c b lane is negative.
212 */
213ASTCENC_SIMD_INLINE vfloat change_sign(vfloat a, vfloat b)
214{
215 vint ia = float_as_int(a);
216 vint ib = float_as_int(b);
217 vint sign_mask(static_cast<int>(0x80000000));
218 vint r = ia ^ (ib & sign_mask);
219 return int_as_float(r);
220}
221
222/**
223 * @brief Return fast, but approximate, vector atan(x).
224 *
225 * Max error of this implementation is 0.004883.
226 */
227ASTCENC_SIMD_INLINE vfloat atan(vfloat x)
228{
229 vmask c = abs(x) > vfloat(1.0f);
230 vfloat z = change_sign(vfloat(astc::PI_OVER_TWO), x);
231 vfloat y = select(x, vfloat(1.0f) / x, c);
232 y = y / (y * y * vfloat(0.28f) + vfloat(1.0f));
233 return select(y, z - y, c);
234}
235
236/**
237 * @brief Return fast, but approximate, vector atan2(x, y).
238 */
239ASTCENC_SIMD_INLINE vfloat atan2(vfloat y, vfloat x)
240{
241 vfloat z = atan(abs(y / x));
242 vmask xmask = vmask(float_as_int(x).m);
243 return change_sign(select_msb(z, vfloat(astc::PI) - z, xmask), y);
244}
245
246/*
247 * @brief Factory that returns a unit length 4 component vfloat4.
248 */
249static ASTCENC_SIMD_INLINE vfloat4 unit4()
250{
251 return vfloat4(0.5f);
252}
253
254/**
255 * @brief Factory that returns a unit length 3 component vfloat4.
256 */
257static ASTCENC_SIMD_INLINE vfloat4 unit3()
258{
259 float val = 0.577350258827209473f;
260 return vfloat4(val, val, val, 0.0f);
261}
262
263/**
264 * @brief Factory that returns a unit length 2 component vfloat4.
265 */
266static ASTCENC_SIMD_INLINE vfloat4 unit2()
267{
268 float val = 0.707106769084930420f;
269 return vfloat4(val, val, 0.0f, 0.0f);
270}
271
272/**
273 * @brief Factory that returns a 3 component vfloat4.
274 */
275static ASTCENC_SIMD_INLINE vfloat4 vfloat3(float a, float b, float c)
276{
277 return vfloat4(a, b, c, 0.0f);
278}
279
280/**
281 * @brief Factory that returns a 2 component vfloat4.
282 */
283static ASTCENC_SIMD_INLINE vfloat4 vfloat2(float a, float b)
284{
285 return vfloat4(a, b, 0.0f, 0.0f);
286}
287
288/**
289 * @brief Normalize a non-zero length vector to unit length.
290 */
291static ASTCENC_SIMD_INLINE vfloat4 normalize(vfloat4 a)
292{
293 vfloat4 length = dot(a, a);
294 return a / sqrt(length);
295}
296
297/**
298 * @brief Normalize a vector, returning @c safe if len is zero.
299 */
300static ASTCENC_SIMD_INLINE vfloat4 normalize_safe(vfloat4 a, vfloat4 safe)
301{
302 vfloat4 length = dot(a, a);
303 if (length.lane<0>() != 0.0f)
304 {
305 return a / sqrt(length);
306 }
307
308 return safe;
309}
310
311
312
313#define POLY0(x, c0) ( c0)
314#define POLY1(x, c0, c1) ((POLY0(x, c1) * x) + c0)
315#define POLY2(x, c0, c1, c2) ((POLY1(x, c1, c2) * x) + c0)
316#define POLY3(x, c0, c1, c2, c3) ((POLY2(x, c1, c2, c3) * x) + c0)
317#define POLY4(x, c0, c1, c2, c3, c4) ((POLY3(x, c1, c2, c3, c4) * x) + c0)
318#define POLY5(x, c0, c1, c2, c3, c4, c5) ((POLY4(x, c1, c2, c3, c4, c5) * x) + c0)
319
320/**
321 * @brief Compute an approximate exp2(x) for each lane in the vector.
322 *
323 * Based on 5th degree minimax polynomials, ported from this blog
324 * https://jrfonseca.blogspot.com/2008/09/fast-sse2-pow-tables-or-polynomials.html
325 */
326static ASTCENC_SIMD_INLINE vfloat4 exp2(vfloat4 x)
327{
328 x = clamp(-126.99999f, 129.0f, x);
329
330 vint4 ipart = float_to_int(x - 0.5f);
331 vfloat4 fpart = x - int_to_float(ipart);
332
333 // Integer contrib, using 1 << ipart
334 vfloat4 iexp = int_as_float(lsl<23>(ipart + 127));
335
336 // Fractional contrib, using polynomial fit of 2^x in range [-0.5, 0.5)
337 vfloat4 fexp = POLY5(fpart,
338 9.9999994e-1f,
339 6.9315308e-1f,
340 2.4015361e-1f,
341 5.5826318e-2f,
342 8.9893397e-3f,
343 1.8775767e-3f);
344
345 return iexp * fexp;
346}
347
348/**
349 * @brief Compute an approximate log2(x) for each lane in the vector.
350 *
351 * Based on 5th degree minimax polynomials, ported from this blog
352 * https://jrfonseca.blogspot.com/2008/09/fast-sse2-pow-tables-or-polynomials.html
353 */
354static ASTCENC_SIMD_INLINE vfloat4 log2(vfloat4 x)
355{
356 vint4 exp(0x7F800000);
357 vint4 mant(0x007FFFFF);
358 vint4 one(0x3F800000);
359
360 vint4 i = float_as_int(x);
361
362 vfloat4 e = int_to_float(lsr<23>(i & exp) - 127);
363
364 vfloat4 m = int_as_float((i & mant) | one);
365
366 // Polynomial fit of log2(x)/(x - 1), for x in range [1, 2)
367 vfloat4 p = POLY4(m,
368 2.8882704548164776201f,
369 -2.52074962577807006663f,
370 1.48116647521213171641f,
371 -0.465725644288844778798f,
372 0.0596515482674574969533f);
373
374 // Increases the polynomial degree, but ensures that log2(1) == 0
375 p = p * (m - 1.0f);
376
377 return p + e;
378}
379
380/**
381 * @brief Compute an approximate pow(x, y) for each lane in the vector.
382 *
383 * Power function based on the exp2(log2(x) * y) transform.
384 */
385static ASTCENC_SIMD_INLINE vfloat4 pow(vfloat4 x, vfloat4 y)
386{
387 vmask4 zero_mask = y == vfloat4(0.0f);
388 vfloat4 estimate = exp2(log2(x) * y);
389
390 // Guarantee that y == 0 returns exactly 1.0f
391 return select(estimate, vfloat4(1.0f), zero_mask);
392}
393
394/**
395 * @brief Count the leading zeros for each lane in @c a.
396 *
397 * Valid for all data values of @c a; will return a per-lane value [0, 32].
398 */
399static ASTCENC_SIMD_INLINE vint4 clz(vint4 a)
400{
401 // This function is a horrible abuse of floating point exponents to convert
402 // the original integer value into a 2^N encoding we can recover easily.
403
404 // Convert to float without risk of rounding up by keeping only top 8 bits.
405 // This trick is is guaranteed to keep top 8 bits and clear the 9th.
406 a = (~lsr<8>(a)) & a;
407 a = float_as_int(int_to_float(a));
408
409 // Extract and unbias exponent
410 a = vint4(127 + 31) - lsr<23>(a);
411
412 // Clamp result to a valid 32-bit range
413 return clamp(0, 32, a);
414}
415
416/**
417 * @brief Return lanewise 2^a for each lane in @c a.
418 *
419 * Use of signed int means that this is only valid for values in range [0, 31].
420 */
421static ASTCENC_SIMD_INLINE vint4 two_to_the_n(vint4 a)
422{
423 // 2^30 is the largest signed number than can be represented
424 assert(all(a < vint4(31)));
425
426 // This function is a horrible abuse of floating point to use the exponent
427 // and float conversion to generate a 2^N multiple.
428
429 // Bias the exponent
430 vint4 exp = a + 127;
431 exp = lsl<23>(exp);
432
433 // Reinterpret the bits as a float, and then convert to an int
434 vfloat4 f = int_as_float(exp);
435 return float_to_int(f);
436}
437
438/**
439 * @brief Convert unorm16 [0, 65535] to float16 in range [0, 1].
440 */
441static ASTCENC_SIMD_INLINE vint4 unorm16_to_sf16(vint4 p)
442{
443 vint4 fp16_one = vint4(0x3C00);
444 vint4 fp16_small = lsl<8>(p);
445
446 vmask4 is_one = p == vint4(0xFFFF);
447 vmask4 is_small = p < vint4(4);
448
449 // Manually inline clz() on Visual Studio to avoid release build codegen bug
450 // see https://github.com/ARM-software/astc-encoder/issues/259
451#if !defined(__clang__) && defined(_MSC_VER)
452 vint4 a = (~lsr<8>(p)) & p;
453 a = float_as_int(int_to_float(a));
454 a = vint4(127 + 31) - lsr<23>(a);
455 vint4 lz = clamp(0, 32, a) - 16;
456#else
457 vint4 lz = clz(p) - 16;
458#endif
459
460 p = p * two_to_the_n(lz + 1);
461 p = p & vint4(0xFFFF);
462
463 p = lsr<6>(p);
464
465 p = p | lsl<10>(vint4(14) - lz);
466
467 vint4 r = select(p, fp16_one, is_one);
468 r = select(r, fp16_small, is_small);
469 return r;
470}
471
472/**
473 * @brief Convert 16-bit LNS to float16.
474 */
475static ASTCENC_SIMD_INLINE vint4 lns_to_sf16(vint4 p)
476{
477 vint4 mc = p & 0x7FF;
478 vint4 ec = lsr<11>(p);
479
480 vint4 mc_512 = mc * 3;
481 vmask4 mask_512 = mc < vint4(512);
482
483 vint4 mc_1536 = mc * 4 - 512;
484 vmask4 mask_1536 = mc < vint4(1536);
485
486 vint4 mc_else = mc * 5 - 2048;
487
488 vint4 mt = mc_else;
489 mt = select(mt, mc_1536, mask_1536);
490 mt = select(mt, mc_512, mask_512);
491
492 vint4 res = lsl<10>(ec) | lsr<3>(mt);
493 return min(res, vint4(0x7BFF));
494}
495
496/**
497 * @brief Extract mantissa and exponent of a float value.
498 *
499 * @param a The input value.
500 * @param[out] exp The output exponent.
501 *
502 * @return The mantissa.
503 */
504static ASTCENC_SIMD_INLINE vfloat4 frexp(vfloat4 a, vint4& exp)
505{
506 // Interpret the bits as an integer
507 vint4 ai = float_as_int(a);
508
509 // Extract and unbias the exponent
510 exp = (lsr<23>(ai) & 0xFF) - 126;
511
512 // Extract and unbias the mantissa
513 vint4 manti = (ai & static_cast<int>(0x807FFFFF)) | 0x3F000000;
514 return int_as_float(manti);
515}
516
517/**
518 * @brief Convert float to 16-bit LNS.
519 */
520static ASTCENC_SIMD_INLINE vfloat4 float_to_lns(vfloat4 a)
521{
522 vint4 exp;
523 vfloat4 mant = frexp(a, exp);
524
525 // Do these early before we start messing about ...
526 vmask4 mask_underflow_nan = ~(a > vfloat4(1.0f / 67108864.0f));
527 vmask4 mask_infinity = a >= vfloat4(65536.0f);
528
529 // If input is smaller than 2^-14, multiply by 2^25 and don't bias.
530 vmask4 exp_lt_m13 = exp < vint4(-13);
531
532 vfloat4 a1a = a * 33554432.0f;
533 vint4 expa = vint4::zero();
534
535 vfloat4 a1b = (mant - 0.5f) * 4096;
536 vint4 expb = exp + 14;
537
538 a = select(a1b, a1a, exp_lt_m13);
539 exp = select(expb, expa, exp_lt_m13);
540
541 vmask4 a_lt_384 = a < vfloat4(384.0f);
542 vmask4 a_lt_1408 = a <= vfloat4(1408.0f);
543
544 vfloat4 a2a = a * (4.0f / 3.0f);
545 vfloat4 a2b = a + 128.0f;
546 vfloat4 a2c = (a + 512.0f) * (4.0f / 5.0f);
547
548 a = a2c;
549 a = select(a, a2b, a_lt_1408);
550 a = select(a, a2a, a_lt_384);
551
552 a = a + (int_to_float(exp) * 2048.0f) + 1.0f;
553
554 a = select(a, vfloat4(65535.0f), mask_infinity);
555 a = select(a, vfloat4::zero(), mask_underflow_nan);
556
557 return a;
558}
559
560namespace astc
561{
562
563static ASTCENC_SIMD_INLINE float pow(float x, float y)
564{
565 return pow(vfloat4(x), vfloat4(y)).lane<0>();
566}
567
568}
569
570#endif // #ifndef ASTC_VECMATHLIB_H_INCLUDED
571