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37 #include "gromacs/simd/simd_math.h"
48 #include "gromacs/math/utilities.h"
49 #include "gromacs/options/basicoptions.h"
50 #include "gromacs/simd/simd.h"
52 #include "testutils/refdata.h"
53 #include "testutils/testasserts.h"
65 /*! \addtogroup module_simd */
68 # if GMX_SIMD_HAVE_REAL
70 class SimdMathTest : public SimdTest
73 /*! \brief Type for half-open intervals specifying test ranges */
74 typedef std::pair<real, real> Range;
76 /*! \brief Control what is considered matching values
78 * Normal simply means that we request the values to be equal
79 * to within the specified tolerance.
80 * However, there are also two more cases that are special:
82 * - Even if we only care about normal (i.e., not denormal) values, some math
83 * libraries might clamp the value to zero, which means our SIMD output
84 * might not match their values. By using MatchRule::Dtz, we will consider
85 * all values both from the reference and test functions that are within the
86 * requested ulp tolerance of a denormal number to be equivalent to 0.0.
87 * - For some older architectures without fused multiply-add units (e.g. x86 SSE2),
88 * we might end up clamping the results to zero just before reaching
89 * denormal output, since the intermediate results e.g. in polynomial
90 * approximations can be smaller than the final one. We often simply don't
91 * care about those values, and then one can use
92 * MatchRule::ReferenceOrZero to allow the test value to either match
93 * the reference or be zero.
97 Normal, //!< Match function values
98 Dtz, //!< Match function values after setting denormals to zero both in test and reference
99 ReferenceOrZero, //!< Test values can either match reference or be zero
102 const std::map<MatchRule, std::string> matchRuleNames_ = {
103 { MatchRule::Normal, "Test should match reference." },
104 { MatchRule::Dtz, "Test should match reference, with denormals treated as 0.0." },
105 { MatchRule::ReferenceOrZero, "Test should match reference or 0.0." }
108 /*! \brief Settings used for simd math function comparisons */
109 struct CompareSettings
111 Range range; //!< Range over which to test function
112 std::int64_t ulpTol; //!< Ulp tolerance
113 real absTol; //!< Absolute tolerance
114 MatchRule matchRule; //!< Decide what we consider a match
117 ::testing::AssertionResult compareSimdMathFunction(const char* refFuncExpr,
118 const char* simdFuncExpr,
119 const char* compareSettingsExpr,
120 real refFunc(real x),
121 SimdReal gmx_simdcall simdFunc(SimdReal x),
122 const CompareSettings& compareSettings);
124 /*! \brief Generate test point vector
126 * \param range The test interval, half open. Upper limit is not included.
127 * Pass by value, since we need to modify in method anyway.
128 * \param points Number of points to generate. This might be increased
129 * slightly to account both for extra special values like 0.0
130 * and the SIMD width.
132 * This routine generates a vector with test points separated by constant
133 * multiplicative factors, based on the range and number of points in the
134 * class. If the range includes both negative and positive values, points
135 * will be generated separately for the negative/positive intervals down
136 * to the smallest real number that can be represented, and we also include
139 * This is highly useful for large test ranges. For example, with a linear
140 * 1000-point division of the range (1,1e10) the first three values to test
141 * would be 1, 10000000.999, and 20000000.998, etc. For large values we would
142 * commonly hit the point where adding the small delta has no effect due to
143 * limited numerical precision.
144 * When we instead use this routine, the values will be 1, 1.0239, 1.0471, etc.
145 * This will spread the entropy over all bits in the IEEE754 representation,
146 * and be a much better test of all potential input values.
148 * \note We do not use the static variable s_nPoints in the parent class
149 * to avoid altering any value the user has set on the command line; since
150 * it's a static member, changing it would have permanent effect.
152 static std::vector<real> generateTestPoints(Range range, std::size_t points);
154 /*! \brief Test routine for the test point vector generation
156 static void generateTestPointsTest();
159 /*! \brief Test approximate equality of SIMD vs reference version of a function.
161 * This macro takes vanilla C and SIMD flavors of a function and tests it with
162 * the number of points, range, and tolerances specified by the test fixture class.
164 * The third option controls the range, tolerances, and match settings.
166 # define GMX_EXPECT_SIMD_FUNC_NEAR(refFunc, tstFunc, compareSettings) \
167 EXPECT_PRED_FORMAT3(compareSimdMathFunction, refFunc, tstFunc, compareSettings)
169 std::vector<real> SimdMathTest::generateTestPoints(Range inputRange, std::size_t inputPoints)
172 std::vector<real> testPoints;
173 testPoints.reserve(inputPoints);
175 GMX_RELEASE_ASSERT(inputRange.first < inputRange.second,
176 "The start of the interval must come before the end");
178 std::vector<Range> testRanges;
180 if (inputRange.first < 0 && inputRange.second > 0)
182 testRanges.emplace_back(Range({ inputRange.first, -std::numeric_limits<real>::min() }));
183 testRanges.emplace_back(Range({ 0.0, inputRange.second }));
187 if (inputRange.second == 0)
189 inputRange.second = -std::numeric_limits<real>::min();
190 inputRange.first = std::min(inputRange.first, inputRange.second);
192 testRanges.push_back(inputRange);
195 for (Range& range : testRanges)
197 std::size_t points = inputPoints / testRanges.size();
199 // The value 0 is special, and can only occur at the start of
200 // the interval after the corrections outside this loop.
201 // Add it explicitly, and adjust the interval to continue
202 // at the first valid non-zero positive number.
203 if (range.first == 0)
205 testPoints.push_back(0.0);
206 range.first = std::numeric_limits<real>::min();
207 points--; // Used one point
212 std::conditional<sizeof(real) == sizeof(double), std::int64_t, std::int32_t>::type i;
216 high.r = range.second;
218 // IEEE754 floating-point numbers have the cool property that for any range of
219 // constant sign, for all non-zero numbers a constant (i.e., linear) difference
220 // in the bitwise representation corresponds to a constant multiplicative factor.
222 // Divide the ulp difference evenly
223 std::int64_t ulpDiff = high.i - low.i;
224 // dividend and divisor must both be signed types
225 std::int64_t ulpDelta = ulpDiff / static_cast<std::int64_t>(points);
226 std::int64_t minUlpDelta = (ulpDiff > 0) ? 1 : -1;
230 // Very short interval or very many points caused round-to-zero.
231 // Select the smallest possible change, which is one ulp (with correct sign)
232 ulpDelta = minUlpDelta;
233 points = std::abs(ulpDiff);
237 // Use an index-based loop to avoid floating-point comparisons with
238 // values that might have overflowed. Save one point for the very last
239 // bitwise value that is part of the interval
240 for (std::size_t i = 0; i < points - 1; i++)
242 testPoints.push_back(x.r);
246 // Make sure we test the very last point that is inside the interval
249 testPoints.push_back(x.r);
254 /*! \brief Implementation routine to compare SIMD vs reference functions.
256 * \param refFuncExpr Description of reference function expression
257 * \param simdFuncExpr Description of SIMD function expression
258 * \param compareSettingsExpr Description of compareSettings
259 * \param refFunc Reference math function pointer
260 * \param simdFunc SIMD math function pointer
261 * \param compareSettings Structure with the range, tolerances, and
262 * matching rules to use for the comparison.
264 * \note You should not never call this function directly, but use the
265 * macro GMX_EXPECT_SIMD_FUNC_NEAR(refFunc,tstFunc,matchRule) instead.
267 ::testing::AssertionResult SimdMathTest::compareSimdMathFunction(const char* refFuncExpr,
268 const char* simdFuncExpr,
269 const char gmx_unused* compareSettingsExpr,
270 real refFunc(real x),
271 SimdReal gmx_simdcall simdFunc(SimdReal x),
272 const CompareSettings& compareSettings)
274 std::vector<real> vx(GMX_SIMD_REAL_WIDTH);
275 std::vector<real> vref(GMX_SIMD_REAL_WIDTH);
276 std::vector<real> vtst(GMX_SIMD_REAL_WIDTH);
278 std::int64_t ulpDiff;
279 std::int64_t maxUlpDiff = 0;
281 real refValMaxUlpDiff, simdValMaxUlpDiff;
282 const int niter = s_nPoints / GMX_SIMD_REAL_WIDTH;
286 std::conditional<sizeof(real) == sizeof(double), std::int64_t, std::int32_t>::type i;
289 // Allow zero-size intervals - nothing to test means we succeeded at it
290 if (compareSettings.range.first == compareSettings.range.second)
292 ::testing::AssertionSuccess();
295 // Calculate the tolerance limit to use for denormals - we want
296 // values that are within the ulp tolerance of denormals to be considered matching
297 conv0.r = std::numeric_limits<real>::min();
298 conv0.i += compareSettings.ulpTol - 1; // min() itself is not denormal, but one ulp larger
299 const real denormalLimit = conv0.r;
301 // We want to test as many diverse bit combinations as possible over the range requested,
302 // and in particular do it evenly spaced in bit-space.
303 // Due to the way IEEE754 floating-point is represented, that means we should have a
304 // constant multiplicative factor between adjacent values. This gets a bit complicated
305 // when we have both positive and negative values, so we offload the generation of the
306 // specific testing values to a separate routine
307 std::vector<real> testPoints = generateTestPoints(compareSettings.range, s_nPoints);
309 size_t pointIndex = 0;
311 for (int iter = 0; iter < niter; iter++)
313 for (int i = 0; i < GMX_SIMD_REAL_WIDTH; i++)
315 vx[i] = testPoints[pointIndex];
316 vref[i] = refFunc(vx[i]);
317 // If we reach the end of the points, stop increasing index so we pad with
318 // extra copies of the last element up to the SIMD width
319 if (pointIndex + 1 < testPoints.size())
324 vtst = simdReal2Vector(simdFunc(vector2SimdReal(vx)));
326 bool absOk = true, signOk = true;
327 for (int i = 0; i < GMX_SIMD_REAL_WIDTH; i++)
329 if (compareSettings.matchRule == MatchRule::Dtz && std::abs(vref[i]) <= denormalLimit
330 && std::abs(vtst[i]) <= denormalLimit)
335 if (compareSettings.matchRule == MatchRule::ReferenceOrZero && vtst[i] == 0.0)
337 // If we accept 0.0 for the test function, we can continue to the next loop iteration.
341 absDiff = std::abs(vref[i] - vtst[i]);
342 absOk = absOk && (absDiff < compareSettings.absTol);
343 signOk = signOk && ((vref[i] >= 0 && vtst[i] >= 0) || (vref[i] <= 0 && vtst[i] <= 0));
345 if (absDiff >= compareSettings.absTol)
347 /* We replicate the trivial ulp differences comparison here rather than
348 * calling the lower-level routine for comparing them, since this enables
349 * us to run through the entire test range and report the largest deviation
350 * without lots of extra glue routines.
354 ulpDiff = llabs(conv0.i - conv1.i);
355 if (ulpDiff > maxUlpDiff)
357 maxUlpDiff = ulpDiff;
358 maxUlpDiffPos = vx[i];
359 refValMaxUlpDiff = vref[i];
360 simdValMaxUlpDiff = vtst[i];
364 if ((!absOk) && (!signOk))
366 return ::testing::AssertionFailure()
367 << "Failing SIMD math function comparison due to sign differences." << std::endl
368 << "Reference function: " << refFuncExpr << std::endl
369 << "Simd function: " << simdFuncExpr << std::endl
370 << "Test range is ( " << compareSettings.range.first << " , "
371 << compareSettings.range.second << " ) " << std::endl
372 << "Match rule: " << matchRuleNames_.at(compareSettings.matchRule) << std::endl
373 << "First sign difference around x=" << std::setprecision(20)
374 << ::testing::PrintToString(vx) << std::endl
375 << "Ref values: " << std::setprecision(20) << ::testing::PrintToString(vref)
377 << "SIMD values: " << std::setprecision(20) << ::testing::PrintToString(vtst)
382 GMX_RELEASE_ASSERT(compareSettings.ulpTol >= 0, "Invalid ulp value.");
383 if (maxUlpDiff <= compareSettings.ulpTol)
385 return ::testing::AssertionSuccess();
389 return ::testing::AssertionFailure()
390 << "Failing SIMD math function ulp comparison between " << refFuncExpr << " and "
391 << simdFuncExpr << std::endl
392 << "Requested ulp tolerance: " << compareSettings.ulpTol << std::endl
393 << "Requested abs tolerance: " << compareSettings.absTol << std::endl
394 << "Match rule: " << matchRuleNames_.at(compareSettings.matchRule) << std::endl
395 << "Largest Ulp difference occurs for x=" << std::setprecision(20) << maxUlpDiffPos
397 << "Ref values: " << std::setprecision(20) << refValMaxUlpDiff << std::endl
398 << "SIMD values: " << std::setprecision(20) << simdValMaxUlpDiff << std::endl
399 << "Ulp diff.: " << std::setprecision(20) << maxUlpDiff << std::endl;
403 // Actual routine to generate a small set of test points in current precision. This will
404 // be called by either the double or single precision test fixture, since we need different
405 // test names to compare to the right reference data.
406 void SimdMathTest::generateTestPointsTest()
409 gmx::test::TestReferenceData data;
410 gmx::test::TestReferenceChecker checker(data.rootChecker());
412 std::vector<real> result;
414 result = generateTestPoints(Range(-1e10, -1), points);
415 checker.checkSequence(result.begin(), result.end(), "Test points for interval [-1e10,-1[");
417 result = generateTestPoints(Range(-1e10, -1e-10), points);
418 checker.checkSequence(result.begin(), result.end(), "Test points for interval [-1e10, -1e-10[");
420 result = generateTestPoints(Range(1, 1e10), points);
421 checker.checkSequence(result.begin(), result.end(), "Test points for interval [1, 1e10[");
423 result = generateTestPoints(Range(1e-10, 1e10), points);
424 checker.checkSequence(result.begin(), result.end(), "Test points for interval [1e-10, 1e10[");
426 result = generateTestPoints(Range(-1e10, 1e-10), points);
427 checker.checkSequence(result.begin(), result.end(), "Test points for interval [-1e10, 1e-10[");
429 result = generateTestPoints(Range(-1e-10, 1e-10), points);
430 checker.checkSequence(result.begin(), result.end(), "Test points for interval [-1e-10, 1e-10[");
432 result = generateTestPoints(Range(-1e-10, 1e10), points);
433 checker.checkSequence(result.begin(), result.end(), "Test points for interval [-1e-10, 1e10[");
435 result = generateTestPoints(Range(-1e10, 1e10), points);
436 checker.checkSequence(result.begin(), result.end(), "Test points for interval [-1e10, 1e10[");
438 result = generateTestPoints(Range(-1000, 0), points);
439 checker.checkSequence(result.begin(), result.end(), "Test points for interval [-1000, 0[");
441 result = generateTestPoints(Range(0, 1000), points);
442 checker.checkSequence(result.begin(), result.end(), "Test points for interval [0, 1000[");
449 // Actual math function tests below
451 /*! \cond internal */
452 /*! \addtogroup module_simd */
458 // Reference data is selected based on test name, so make the test name precision-dependent
460 TEST_F(SimdMathTest, generateTestPointsDouble)
462 generateTestPointsTest();
465 TEST_F(SimdMathTest, generateTestPointsFloat)
467 generateTestPointsTest();
471 TEST_F(SimdMathTest, copysign)
473 GMX_EXPECT_SIMD_REAL_EQ(setSimdRealFrom3R(-c0, c1, c2),
474 copysign(setSimdRealFrom3R(c0, c1, c2), setSimdRealFrom3R(-c3, c4, 0)));
475 GMX_EXPECT_SIMD_REAL_EQ(setSimdRealFrom3R(-c0, c1, c2),
476 copysign(setSimdRealFrom3R(-c0, -c1, -c2), setSimdRealFrom3R(-c3, c4, 0)));
477 GMX_EXPECT_SIMD_REAL_EQ(setSimdRealFrom3R(c0, -c1, c2),
478 copysign(setSimdRealFrom3R(c0, c1, c2), setSimdRealFrom3R(c3, -c4, 0)));
479 GMX_EXPECT_SIMD_REAL_EQ(setSimdRealFrom3R(c0, -c1, c2),
480 copysign(setSimdRealFrom3R(-c0, -c1, -c2), setSimdRealFrom3R(c3, -c4, 0)));
483 /*! \brief Function wrapper to evaluate reference 1/sqrt(x) */
484 real refInvsqrt(real x)
486 return 1.0 / std::sqrt(x);
489 TEST_F(SimdMathTest, invsqrt)
491 const real low = std::numeric_limits<float>::min();
492 const real high = std::numeric_limits<float>::max();
493 CompareSettings settings{ Range(low, high), ulpTol_, absTol_, MatchRule::Normal };
495 GMX_EXPECT_SIMD_FUNC_NEAR(refInvsqrt, invsqrt, settings);
498 TEST_F(SimdMathTest, maskzInvsqrt)
500 SimdReal x = setSimdRealFrom3R(c1, 0.0, c2);
501 SimdBool m = (setZero() < x);
502 SimdReal ref = setSimdRealFrom3R(1.0 / std::sqrt(c1), 0.0, 1.0 / std::sqrt(c2));
503 GMX_EXPECT_SIMD_REAL_NEAR(ref, maskzInvsqrt(x, m));
506 /*! \brief Function wrapper to return first result when testing \ref invsqrtPair */
507 SimdReal gmx_simdcall tstInvsqrtPair0(SimdReal x)
510 invsqrtPair(x, x, &r0, &r1);
514 /*! \brief Function wrapper to return second result when testing \ref invsqrtPair */
515 SimdReal gmx_simdcall tstInvsqrtPair1(SimdReal x)
518 invsqrtPair(x, x, &r0, &r1);
522 TEST_F(SimdMathTest, invsqrtPair)
524 const real low = std::numeric_limits<float>::min();
525 const real high = std::numeric_limits<float>::max();
527 // Accuracy conversions lose a bit of accuracy compared to all-double,
528 // so increase the tolerance to 4*ulpTol_
529 CompareSettings settings{ Range(low, high), 4 * ulpTol_, absTol_, MatchRule::Normal };
531 GMX_EXPECT_SIMD_FUNC_NEAR(refInvsqrt, tstInvsqrtPair0, settings);
532 GMX_EXPECT_SIMD_FUNC_NEAR(refInvsqrt, tstInvsqrtPair1, settings);
535 /*! \brief Function wrapper to evaluate reference sqrt(x) */
541 TEST_F(SimdMathTest, sqrt)
543 // Since the first lookup step is sometimes performed in single precision,
544 // our SIMD sqrt can only handle single-precision input values, even when
545 // compiled in double precision.
547 const real minFloat = std::numeric_limits<float>::min();
548 const real minSafeFloat = minFloat * 10;
549 const real maxSafeFloat = std::numeric_limits<float>::max() * 0.1;
550 CompareSettings settings;
551 // The accuracy conversions lose a bit of extra accuracy compared to
552 // doing the iterations in all-double.
553 setUlpTol(4 * ulpTol_);
555 // First test that 0.0 and a few other values work
556 GMX_EXPECT_SIMD_REAL_NEAR(setSimdRealFrom3R(0, std::sqrt(c1), std::sqrt(c2)),
557 sqrt(setSimdRealFrom3R(0, c1, c2)));
560 // As mentioned above, we cannot guarantee that very small double precision
561 // input values (below std::numeric_limits<float>::min()) are handled correctly,
562 // so our implementation will clamp it to zero. In this range we allow either
563 // the correct value or zero, but it's important that it does not result in NaN or Inf values.
565 // This test range must not be called for single precision, since if we try to divide
566 // the interval (0.0, low( in npoints we will try to multiply by factors so small that
567 // they end up being flushed to zero, and the loop would never end.
568 settings = { Range(0.0, minFloat), ulpTol_, absTol_, MatchRule::ReferenceOrZero };
569 GMX_EXPECT_SIMD_FUNC_NEAR(refSqrt, sqrt, settings);
572 // Next range: Just about minFloat the lookup should always work, but the results
573 // might be a bit fragile due to issues with the N-R iterations being flushed to zero
574 // for denormals. We can probably relax the latter in double precision, but since we
575 // anyway cannot handle numbers that cannot be represented in single it's not worth
576 // worrying too much about whether we have zero or an exact values around 10^-38....
577 settings = { Range(minFloat, minSafeFloat), ulpTol_, absTol_, MatchRule::ReferenceOrZero };
578 GMX_EXPECT_SIMD_FUNC_NEAR(refSqrt, sqrt, settings);
580 settings = { Range(minSafeFloat, maxSafeFloat), ulpTol_, absTol_, MatchRule::Normal };
581 GMX_EXPECT_SIMD_FUNC_NEAR(refSqrt, sqrt, settings);
584 TEST_F(SimdMathTest, sqrtUnsafe)
586 const real minSafeFloat = std::numeric_limits<float>::min() * 10;
587 const real maxSafeFloat = std::numeric_limits<float>::max() * 0.1;
589 // The accuracy conversions lose a bit of extra accuracy compared to
590 // doing the iterations in all-double, so we use 4*ulpTol_
591 setUlpTol(4 * ulpTol_);
593 CompareSettings settings{ Range(minSafeFloat, maxSafeFloat), 4 * ulpTol_, absTol_, MatchRule::Normal };
594 GMX_EXPECT_SIMD_FUNC_NEAR(refSqrt, sqrt<MathOptimization::Unsafe>, settings);
597 /*! \brief Function wrapper to evaluate reference 1/x */
603 TEST_F(SimdMathTest, inv)
605 // Since the first lookup step is sometimes performed in single precision,
606 // our SIMD 1/x can only handle single-precision input values, even when
607 // compiled in double precision.
609 // Relevant threshold points
610 const real minSafeFloat = std::numeric_limits<float>::min()
611 * 10; // X value guaranteed not to result in Inf intermediates for 1/x calc.
612 const real maxSafeFloat = std::numeric_limits<float>::max()
613 * 0.1; // X value guaranteed not to result in DTZ intermediates for 1/x calc.
614 // Scale highest value by 1-eps, since we will do some arithmetics on this value
615 const real maxFloat =
616 std::numeric_limits<float>::max() * (1.0 - std::numeric_limits<float>::epsilon());
617 CompareSettings settings;
619 // Danger zone where intermediates might be flushed to zero and produce 1/x==0.0
620 settings = { Range(-maxFloat, -maxSafeFloat), ulpTol_, absTol_, MatchRule::ReferenceOrZero };
621 GMX_EXPECT_SIMD_FUNC_NEAR(refInv, inv, settings);
623 // Normal checks for x < 0
624 settings = { Range(-maxSafeFloat, -minSafeFloat), ulpTol_, absTol_, MatchRule::Normal };
625 GMX_EXPECT_SIMD_FUNC_NEAR(refInv, inv, settings);
627 // We do not care about the small range -minSafeFloat < x < +minSafeFloat where the result can be +/- Inf, since we don't require strict IEEE754.
629 // Normal checks for x > 0
630 settings = { Range(minSafeFloat, maxSafeFloat), ulpTol_, absTol_, MatchRule::Normal };
631 GMX_EXPECT_SIMD_FUNC_NEAR(refInv, inv, settings);
633 // Danger zone where intermediates might be flushed to zero and produce 1/x==0.0
634 settings = { Range(maxSafeFloat, maxFloat), ulpTol_, absTol_, MatchRule::ReferenceOrZero };
635 GMX_EXPECT_SIMD_FUNC_NEAR(refInv, inv, settings);
638 TEST_F(SimdMathTest, maskzInv)
640 SimdReal x = setSimdRealFrom3R(c1, 0.0, c2);
641 SimdBool m = (setZero() < x);
642 SimdReal ref = setSimdRealFrom3R(1.0 / c1, 0.0, 1.0 / c2);
643 GMX_EXPECT_SIMD_REAL_NEAR(ref, maskzInv(x, m));
646 TEST_F(SimdMathTest, cbrt)
648 const real low = -std::numeric_limits<real>::max();
649 const real high = std::numeric_limits<real>::max();
651 CompareSettings settings{ Range(low, high), ulpTol_, absTol_, MatchRule::Normal };
652 GMX_EXPECT_SIMD_FUNC_NEAR(std::cbrt, cbrt, settings);
655 /*! \brief Function wrapper to evaluate reference 1/cbrt(x) */
656 real refInvCbrt(real x)
658 return 1.0 / std::cbrt(x);
661 TEST_F(SimdMathTest, invcbrt)
663 // Negative values first
664 real low = -std::numeric_limits<real>::max();
665 real high = -std::numeric_limits<real>::min();
667 CompareSettings settings{ Range(low, high), ulpTol_, absTol_, MatchRule::Normal };
668 GMX_EXPECT_SIMD_FUNC_NEAR(refInvCbrt, invcbrt, settings);
671 low = std::numeric_limits<real>::min();
672 high = std::numeric_limits<real>::max();
673 settings = { Range(low, high), ulpTol_, absTol_, MatchRule::Normal };
674 GMX_EXPECT_SIMD_FUNC_NEAR(refInvCbrt, invcbrt, settings);
677 TEST_F(SimdMathTest, log2)
679 const real low = std::numeric_limits<real>::min();
680 const real high = std::numeric_limits<real>::max();
682 CompareSettings settings{ Range(low, high), ulpTol_, absTol_, MatchRule::Normal };
683 GMX_EXPECT_SIMD_FUNC_NEAR(std::log2, log2, settings);
686 TEST_F(SimdMathTest, log)
688 const real low = std::numeric_limits<real>::min();
689 const real high = std::numeric_limits<real>::max();
691 CompareSettings settings{ Range(low, high), ulpTol_, absTol_, MatchRule::Normal };
692 GMX_EXPECT_SIMD_FUNC_NEAR(std::log, log, settings);
695 TEST_F(SimdMathTest, exp2)
697 // Relevant threshold points
698 constexpr real lowestReal = -std::numeric_limits<real>::max();
699 constexpr real lowestRealThatProducesNormal =
700 std::numeric_limits<real>::min_exponent
701 - 1; // adding the significant corresponds to one more unit in exponent
702 constexpr real lowestRealThatProducesDenormal =
703 lowestRealThatProducesNormal
704 - std::numeric_limits<real>::digits; // digits refer to bits in significand, so 24/53 for float/double
705 constexpr real highestRealThatProducesNormal =
706 std::numeric_limits<real>::max_exponent
707 - 1; // adding the significant corresponds to one more unit in exponent
708 CompareSettings settings;
710 // Below subnormal range all results should be zero (so, match the reference)
711 settings = { Range(lowestReal, lowestRealThatProducesDenormal), ulpTol_, absTol_, MatchRule::Normal };
712 GMX_EXPECT_SIMD_FUNC_NEAR(std::exp2, exp2, settings);
714 // Subnormal range, require matching, but DTZ is fine
715 settings = { Range(lowestRealThatProducesDenormal, lowestRealThatProducesNormal),
719 GMX_EXPECT_SIMD_FUNC_NEAR(std::exp2, exp2, settings);
721 // Normal range, standard result expected
722 settings = { Range(lowestRealThatProducesNormal, highestRealThatProducesNormal),
726 GMX_EXPECT_SIMD_FUNC_NEAR(std::exp2, exp2, settings);
729 TEST_F(SimdMathTest, exp2Unsafe)
731 // The unsafe version is only defined in the normal range
732 constexpr real lowestRealThatProducesNormal =
733 std::numeric_limits<real>::min_exponent
734 - 1; // adding the significant corresponds to one more unit in exponent
735 constexpr real highestRealThatProducesNormal =
736 std::numeric_limits<real>::max_exponent
737 - 1; // adding the significant corresponds to one more unit in exponent
739 CompareSettings settings{ Range(lowestRealThatProducesNormal, highestRealThatProducesNormal),
743 GMX_EXPECT_SIMD_FUNC_NEAR(std::exp2, exp2<MathOptimization::Unsafe>, settings);
746 TEST_F(SimdMathTest, exp)
748 // Relevant threshold points. See the exp2 test for more details about the values; these are
749 // simply scaled by log(2) due to the difference between exp2 and exp.
750 const real lowestReal = -std::numeric_limits<real>::max();
751 // In theory the smallest value should be (min_exponent-1)*log(2), but rounding after the multiplication will cause this
752 // value to be a single ulp too low. This might cause failed tests on CPUs that use different DTZ modes for SIMD vs.
753 // non-SIMD arithmetics (e.g. ARM v7), so multiply by (1.0-eps) to increase it by a single ulp.
754 const real lowestRealThatProducesNormal = (std::numeric_limits<real>::min_exponent - 1)
756 * (1 - std::numeric_limits<real>::epsilon());
757 const real lowestRealThatProducesDenormal =
758 lowestRealThatProducesNormal - std::numeric_limits<real>::digits * std::log(2.0);
759 const real highestRealThatProducesNormal =
760 (std::numeric_limits<real>::max_exponent - 1) * std::log(2.0);
761 CompareSettings settings;
763 // Below subnormal range all results should be zero (so, match the reference)
764 settings = { Range(lowestReal, lowestRealThatProducesDenormal), ulpTol_, absTol_, MatchRule::Normal };
765 GMX_EXPECT_SIMD_FUNC_NEAR(std::exp, exp, settings);
767 // Subnormal range, require matching, but DTZ is fine
768 settings = { Range(lowestRealThatProducesDenormal, lowestRealThatProducesNormal),
772 GMX_EXPECT_SIMD_FUNC_NEAR(std::exp, exp, settings);
774 // Normal range, standard result expected
775 settings = { Range(lowestRealThatProducesNormal, highestRealThatProducesNormal),
779 GMX_EXPECT_SIMD_FUNC_NEAR(std::exp, exp, settings);
782 TEST_F(SimdMathTest, expUnsafe)
784 // See test of exp() for comments about test ranges
785 const real lowestRealThatProducesNormal = (std::numeric_limits<real>::min_exponent - 1)
787 * (1 - std::numeric_limits<real>::epsilon());
788 const real highestRealThatProducesNormal =
789 (std::numeric_limits<real>::max_exponent - 1) * std::log(2.0);
791 CompareSettings settings{ Range(lowestRealThatProducesNormal, highestRealThatProducesNormal),
795 GMX_EXPECT_SIMD_FUNC_NEAR(std::exp, exp<MathOptimization::Unsafe>, settings);
798 TEST_F(SimdMathTest, pow)
800 // We already test the log2/exp2 components of pow() extensively above, and it's a very
801 // simple single-line function, so here we just test a handful of values to catch typos
802 // and then some special values.
804 GMX_EXPECT_SIMD_REAL_NEAR(setSimdRealFrom3R(std::pow(c0, c3), std::pow(c1, c4), std::pow(c2, c5)),
805 pow(rSimd_c0c1c2, rSimd_c3c4c5));
807 GMX_EXPECT_SIMD_REAL_NEAR(setSimdRealFrom3R(std::pow(c0, -c3), std::pow(c1, -c0), std::pow(c2, -c4)),
808 pow(rSimd_c0c1c2, rSimd_m3m0m4));
810 // 0^0 = 1 , 0^c1=0, -c1^0=1
811 GMX_EXPECT_SIMD_REAL_NEAR(setSimdRealFrom3R(1.0, 0.0, 1.0),
812 pow(setSimdRealFrom3R(0, 0.0, -c1), setSimdRealFrom3R(0.0, c1, 0.0)));
815 TEST_F(SimdMathTest, powUnsafe)
817 // We already test the log2/exp2 components of pow() extensively above, and it's a very
818 // simple single-line function, so here we just test a handful of values to catch typos
819 // and then some special values.
821 GMX_EXPECT_SIMD_REAL_NEAR(setSimdRealFrom3R(std::pow(c0, c3), std::pow(c1, c4), std::pow(c2, c5)),
822 pow<MathOptimization::Unsafe>(rSimd_c0c1c2, rSimd_c3c4c5));
824 GMX_EXPECT_SIMD_REAL_NEAR(setSimdRealFrom3R(std::pow(c0, -c3), std::pow(c1, -c0), std::pow(c2, -c4)),
825 pow<MathOptimization::Unsafe>(rSimd_c0c1c2, rSimd_m3m0m4));
828 /*! \brief Function wrapper for erf(x), with argument/return in default Gromacs precision.
830 * \note Single-precision erf() in some libraries can be slightly lower precision
831 * than the SIMD flavor, so we use a cast to force double precision for reference.
835 return std::erf(static_cast<double>(x));
838 TEST_F(SimdMathTest, erf)
840 CompareSettings settings{ Range(-9, 9), ulpTol_, std::numeric_limits<real>::min(), MatchRule::Normal };
841 GMX_EXPECT_SIMD_FUNC_NEAR(refErf, erf, settings);
844 /*! \brief Function wrapper for erfc(x), with argument/return in default Gromacs precision.
846 * \note Single-precision erfc() in some libraries can be slightly lower precision
847 * than the SIMD flavor, so we use a cast to force double precision for reference.
851 return std::erfc(static_cast<double>(x));
854 TEST_F(SimdMathTest, erfc)
856 // Our erfc algorithm has 4 ulp accuracy, so relax tolerance a bit to 4*ulpTol
857 CompareSettings settings{ Range(-9, 9), 4 * ulpTol_, std::numeric_limits<real>::min(), MatchRule::Normal };
858 GMX_EXPECT_SIMD_FUNC_NEAR(refErfc, erfc, settings);
861 TEST_F(SimdMathTest, sin)
863 CompareSettings settings{ Range(-8 * M_PI, 8 * M_PI), ulpTol_, absTol_, MatchRule::Normal };
864 GMX_EXPECT_SIMD_FUNC_NEAR(std::sin, sin, settings);
866 // Range reduction leads to accuracy loss, so we might want higher tolerance here
867 settings = { Range(-10000, 10000), 2 * ulpTol_, absTol_, MatchRule::Normal };
868 GMX_EXPECT_SIMD_FUNC_NEAR(std::sin, sin, settings);
871 TEST_F(SimdMathTest, cos)
873 CompareSettings settings{ Range(-8 * M_PI, 8 * M_PI), ulpTol_, absTol_, MatchRule::Normal };
874 GMX_EXPECT_SIMD_FUNC_NEAR(std::cos, cos, settings);
876 // Range reduction leads to accuracy loss, so we might want higher tolerance here
877 settings = { Range(-10000, 10000), 2 * ulpTol_, absTol_, MatchRule::Normal };
878 GMX_EXPECT_SIMD_FUNC_NEAR(std::cos, cos, settings);
881 TEST_F(SimdMathTest, tan)
883 // Tan(x) is a little sensitive due to the division in the algorithm.
884 // Rather than using lots of extra FP operations, we accept the algorithm
885 // presently only achieves a ~3 ulp error and use the medium tolerance.
886 CompareSettings settings{ Range(-8 * M_PI, 8 * M_PI), ulpTol_, absTol_, MatchRule::Normal };
887 GMX_EXPECT_SIMD_FUNC_NEAR(std::tan, tan, settings);
889 // Range reduction leads to accuracy loss, so we might want higher tolerance here
890 settings = { Range(-10000, 10000), 2 * ulpTol_, absTol_, MatchRule::Normal };
891 GMX_EXPECT_SIMD_FUNC_NEAR(std::tan, tan, settings);
894 TEST_F(SimdMathTest, asin)
896 // Our present asin(x) algorithm achieves 2-3 ulp accuracy
897 CompareSettings settings{ Range(-1, 1), ulpTol_, absTol_, MatchRule::Normal };
898 GMX_EXPECT_SIMD_FUNC_NEAR(std::asin, asin, settings);
901 TEST_F(SimdMathTest, acos)
903 // Our present acos(x) algorithm achieves 2-3 ulp accuracy
904 CompareSettings settings{ Range(-1, 1), ulpTol_, absTol_, MatchRule::Normal };
905 GMX_EXPECT_SIMD_FUNC_NEAR(std::acos, acos, settings);
908 TEST_F(SimdMathTest, atan)
910 // Our present atan(x) algorithm achieves 1 ulp accuracy
911 CompareSettings settings{ Range(-10000, 10000), ulpTol_, absTol_, MatchRule::Normal };
912 GMX_EXPECT_SIMD_FUNC_NEAR(std::atan, atan, settings);
915 TEST_F(SimdMathTest, atan2)
917 // test each quadrant
918 GMX_EXPECT_SIMD_REAL_NEAR(
919 setSimdRealFrom3R(std::atan2(c0, c3), std::atan2(c1, c4), std::atan2(c2, c5)),
920 atan2(rSimd_c0c1c2, rSimd_c3c4c5));
921 GMX_EXPECT_SIMD_REAL_NEAR(
922 setSimdRealFrom3R(std::atan2(-c0, c3), std::atan2(-c1, c4), std::atan2(-c2, c5)),
923 atan2(rSimd_m0m1m2, rSimd_c3c4c5));
924 GMX_EXPECT_SIMD_REAL_NEAR(
925 setSimdRealFrom3R(std::atan2(-c0, -c3), std::atan2(-c1, -c0), std::atan2(-c2, -c4)),
926 atan2(rSimd_m0m1m2, rSimd_m3m0m4));
927 GMX_EXPECT_SIMD_REAL_NEAR(
928 setSimdRealFrom3R(std::atan2(c0, -c3), std::atan2(c1, -c0), std::atan2(c2, -c4)),
929 atan2(rSimd_c0c1c2, rSimd_m3m0m4));
931 // cases important for calculating angles
932 // values on coordinate axes
933 GMX_EXPECT_SIMD_REAL_NEAR(setSimdRealFrom3R(std::atan2(0, c0), std::atan2(0, c1), std::atan2(0, c2)),
934 atan2(setZero(), rSimd_c0c1c2));
935 GMX_EXPECT_SIMD_REAL_NEAR(setSimdRealFrom3R(std::atan2(c0, 0), std::atan2(c1, 0), std::atan2(c2, 0)),
936 atan2(rSimd_c0c1c2, setZero()));
937 GMX_EXPECT_SIMD_REAL_NEAR(
938 setSimdRealFrom3R(std::atan2(0, -c0), std::atan2(0, -c1), std::atan2(0, -c2)),
939 atan2(setZero(), rSimd_m0m1m2));
940 GMX_EXPECT_SIMD_REAL_NEAR(
941 setSimdRealFrom3R(std::atan2(-c0, 0), std::atan2(-c1, 0), std::atan2(-c2, 0)),
942 atan2(rSimd_m0m1m2, setZero()));
943 // degenerate value (origin) should return 0.0. At least IBM xlc 13.1.5 gets the reference
944 // value wrong (-nan) at -O3 optimization, so we compare to the correct value (0.0) instead.
945 GMX_EXPECT_SIMD_REAL_NEAR(setSimdRealFrom1R(0.0), atan2(setSimdRealFrom3R(0.0, 0.0, 0.0), setZero()));
948 /*! \brief Evaluate reference version of PME force correction. */
949 real refPmeForceCorrection(real x)
953 real y = std::sqrt(x);
954 return 2 * std::exp(-x) / (std::sqrt(M_PI) * x) - std::erf(static_cast<double>(y)) / (x * y);
958 return -4 / (3 * std::sqrt(M_PI));
962 // The PME corrections will be added to ~1/r2, so absolute tolerance of EPS is fine.
963 TEST_F(SimdMathTest, pmeForceCorrection)
965 // Pme correction relative accuracy only needs to be ~1e-6 accuracy single, 1e-10 double
966 const std::int64_t ulpTol = (GMX_DOUBLE ? 5e-10 : 5e-6) / GMX_REAL_EPS;
968 CompareSettings settings{ Range(0.15, 4), ulpTol, GMX_REAL_EPS, MatchRule::Normal };
969 GMX_EXPECT_SIMD_FUNC_NEAR(refPmeForceCorrection, pmeForceCorrection, settings);
972 /*! \brief Evaluate reference version of PME potential correction. */
973 real refPmePotentialCorrection(real x)
975 real y = std::sqrt(x);
976 return std::erf(static_cast<double>(y)) / y;
979 // The PME corrections will be added to ~1/r, so absolute tolerance of EPS is fine.
980 TEST_F(SimdMathTest, pmePotentialCorrection)
982 // Pme correction relative accuracy only needs to be ~1e-6 accuracy single, 1e-10 double
983 const std::int64_t ulpTol = (GMX_DOUBLE ? 5e-10 : 5e-6) / GMX_REAL_EPS;
985 CompareSettings settings{ Range(0.15, 4), ulpTol, GMX_REAL_EPS, MatchRule::Normal };
986 GMX_EXPECT_SIMD_FUNC_NEAR(refPmePotentialCorrection, pmePotentialCorrection, settings);
989 // Functions that only target single accuracy, even for double SIMD data
991 TEST_F(SimdMathTest, invsqrtSingleAccuracy)
993 // Here we always use float limits, since the lookup is not defined for numbers that
994 // cannot be represented in single precision.
995 const real low = std::numeric_limits<float>::min();
996 const real high = std::numeric_limits<float>::max();
997 /* Increase the allowed error by the difference between the actual precision and single */
998 setUlpTolSingleAccuracy(ulpTol_);
1000 CompareSettings settings{ Range(low, high), ulpTol_, absTol_, MatchRule::Normal };
1001 GMX_EXPECT_SIMD_FUNC_NEAR(refInvsqrt, invsqrtSingleAccuracy, settings);
1004 /*! \brief Function wrapper to return first result when testing \ref invsqrtPairSingleAccuracy */
1005 SimdReal gmx_simdcall tst_invsqrt_SingleAccuracy_pair0(SimdReal x)
1008 invsqrtPairSingleAccuracy(x, x, &r0, &r1);
1012 /*! \brief Function wrapper to return second result when testing \ref invsqrtPairSingleAccuracy */
1013 SimdReal gmx_simdcall tst_invsqrt_SingleAccuracy_pair1(SimdReal x)
1016 invsqrtPairSingleAccuracy(x, x, &r0, &r1);
1020 TEST_F(SimdMathTest, invsqrtPairSingleAccuracy)
1022 // Float limits since lookup is always performed in single
1023 const real low = std::numeric_limits<float>::min();
1024 const real high = std::numeric_limits<float>::max();
1025 /* Increase the allowed error by the difference between the actual precision and single */
1026 setUlpTolSingleAccuracy(ulpTol_);
1028 CompareSettings settings{ Range(low, high), ulpTol_, absTol_, MatchRule::Normal };
1029 GMX_EXPECT_SIMD_FUNC_NEAR(refInvsqrt, tst_invsqrt_SingleAccuracy_pair0, settings);
1030 GMX_EXPECT_SIMD_FUNC_NEAR(refInvsqrt, tst_invsqrt_SingleAccuracy_pair1, settings);
1033 TEST_F(SimdMathTest, sqrtSingleAccuracy)
1035 // Since the first lookup step is sometimes performed in single precision,
1036 // our SIMD sqrt can only handle single-precision input values, even when
1037 // compiled in double precision - thus we use single precision limits here.
1039 // Scale lowest value by 1+eps, since we will do some arithmetics on this value
1040 const real low = std::numeric_limits<float>::min() * (1.0 + std::numeric_limits<float>::epsilon());
1041 const real high = std::numeric_limits<float>::max();
1042 CompareSettings settings;
1044 // Increase the allowed error by the difference between the actual precision and single
1045 setUlpTolSingleAccuracy(ulpTol_);
1047 // First test that 0.0 and a few other values works
1048 GMX_EXPECT_SIMD_REAL_NEAR(setSimdRealFrom3R(0, std::sqrt(c0), std::sqrt(c1)),
1049 sqrtSingleAccuracy(setSimdRealFrom3R(0, c0, c1)));
1052 // As mentioned above, we cannot guarantee that very small double precision
1053 // input values (below std::numeric_limits<float>::min()) are handled correctly,
1054 // so our implementation will clamp it to zero. In this range we allow either
1055 // the correct value or zero, but it's important that it does not result in NaN or Inf values.
1057 // This test range must not be called for single precision, since if we try to divide
1058 // the interval (0.0, low( in npoints we will try to multiply by factors so small that
1059 // they end up being flushed to zero, and the loop would never end.
1060 settings = { Range(0.0, low), ulpTol_, absTol_, MatchRule::ReferenceOrZero };
1061 GMX_EXPECT_SIMD_FUNC_NEAR(refSqrt, sqrtSingleAccuracy, settings);
1064 settings = { Range(low, high), ulpTol_, absTol_, MatchRule::Normal };
1065 GMX_EXPECT_SIMD_FUNC_NEAR(refSqrt, sqrtSingleAccuracy, settings);
1068 TEST_F(SimdMathTest, sqrtSingleAccuracyUnsafe)
1070 // Test the full range, but stick to float limits since lookup is done in single.
1071 const real low = std::numeric_limits<float>::min();
1072 const real high = std::numeric_limits<float>::max();
1074 /* Increase the allowed error by the difference between the actual precision and single */
1075 setUlpTolSingleAccuracy(ulpTol_);
1077 CompareSettings settings{ Range(low, high), ulpTol_, absTol_, MatchRule::Normal };
1078 GMX_EXPECT_SIMD_FUNC_NEAR(refSqrt, sqrtSingleAccuracy<MathOptimization::Unsafe>, settings);
1081 TEST_F(SimdMathTest, invSingleAccuracy)
1083 // Since the first lookup step is sometimes performed in single precision,
1084 // our SIMD 1/x can only handle single-precision input values, even when
1085 // compiled in double precision.
1087 // Relevant threshold points
1088 const real minSafeFloat = std::numeric_limits<float>::min()
1089 * 10; // X value guaranteed not to result in Inf intermediates for 1/x calc.
1090 const real maxSafeFloat = std::numeric_limits<float>::max()
1091 * 0.1; // X value guaranteed not to result in DTZ intermediates for 1/x calc.
1092 // Scale highest value by 1-eps, since we will do some arithmetics on this value
1093 const real maxFloat =
1094 std::numeric_limits<float>::max() * (1.0 - std::numeric_limits<float>::epsilon());
1095 CompareSettings settings;
1097 // Increase the allowed error by the difference between the actual precision and single
1098 setUlpTolSingleAccuracy(ulpTol_);
1100 // Danger zone where intermediates might be flushed to zero and produce 1/x==0.0
1101 settings = { Range(-maxFloat, -maxSafeFloat), ulpTol_, absTol_, MatchRule::ReferenceOrZero };
1102 GMX_EXPECT_SIMD_FUNC_NEAR(refInv, inv, settings);
1104 // Normal checks for x < 0
1105 settings = { Range(-maxSafeFloat, -minSafeFloat), ulpTol_, absTol_, MatchRule::Normal };
1106 GMX_EXPECT_SIMD_FUNC_NEAR(refInv, inv, settings);
1108 // We do not care about the small range -minSafeFloat < x < +minSafeFloat where the result can be +/- Inf, since we don't require strict IEEE754.
1110 // Normal checks for x > 0
1111 settings = { Range(minSafeFloat, maxSafeFloat), ulpTol_, absTol_, MatchRule::Normal };
1112 GMX_EXPECT_SIMD_FUNC_NEAR(refInv, inv, settings);
1114 // Danger zone where intermediates might be flushed to zero and produce 1/x==0.0
1115 settings = { Range(maxSafeFloat, maxFloat), ulpTol_, absTol_, MatchRule::ReferenceOrZero };
1116 GMX_EXPECT_SIMD_FUNC_NEAR(refInv, inv, settings);
1119 TEST_F(SimdMathTest, cbrtSingleAccuracy)
1121 const real low = -std::numeric_limits<real>::max();
1122 const real high = std::numeric_limits<real>::max();
1124 // Increase the allowed error by the difference between the actual precision and single
1125 setUlpTolSingleAccuracy(ulpTol_);
1127 CompareSettings settings{ Range(low, high), ulpTol_, absTol_, MatchRule::Normal };
1128 GMX_EXPECT_SIMD_FUNC_NEAR(std::cbrt, cbrtSingleAccuracy, settings);
1131 TEST_F(SimdMathTest, invcbrtSingleAccuracy)
1133 // Increase the allowed error by the difference between the actual precision and single
1134 setUlpTolSingleAccuracy(ulpTol_);
1136 // Negative values first
1137 real low = -std::numeric_limits<real>::max();
1138 real high = -std::numeric_limits<real>::min();
1140 CompareSettings settings{ Range(low, high), ulpTol_, absTol_, MatchRule::Normal };
1141 GMX_EXPECT_SIMD_FUNC_NEAR(refInvCbrt, invcbrtSingleAccuracy, settings);
1144 low = std::numeric_limits<real>::min();
1145 high = std::numeric_limits<real>::max();
1146 settings = { Range(low, high), ulpTol_, absTol_, MatchRule::Normal };
1147 GMX_EXPECT_SIMD_FUNC_NEAR(refInvCbrt, invcbrtSingleAccuracy, settings);
1150 TEST_F(SimdMathTest, log2SingleAccuracy)
1152 const real low = std::numeric_limits<real>::min();
1153 const real high = std::numeric_limits<real>::max();
1155 // Increase the allowed error by the difference between the actual precision and single
1156 setUlpTolSingleAccuracy(ulpTol_);
1158 CompareSettings settings{ Range(low, high), ulpTol_, absTol_, MatchRule::Normal };
1159 GMX_EXPECT_SIMD_FUNC_NEAR(std::log2, log2SingleAccuracy, settings);
1162 TEST_F(SimdMathTest, logSingleAccuracy)
1164 const real low = std::numeric_limits<real>::min();
1165 const real high = std::numeric_limits<real>::max();
1167 // Increase the allowed error by the difference between the actual precision and single
1168 setUlpTolSingleAccuracy(ulpTol_);
1170 CompareSettings settings{ Range(low, high), ulpTol_, absTol_, MatchRule::Normal };
1171 GMX_EXPECT_SIMD_FUNC_NEAR(std::log, logSingleAccuracy, settings);
1174 TEST_F(SimdMathTest, exp2SingleAccuracy)
1176 // Relevant threshold points - float limits since we only target single accuracy
1177 constexpr real lowestReal = -std::numeric_limits<real>::max();
1178 constexpr real lowestRealThatProducesNormal =
1179 std::numeric_limits<real>::min_exponent
1180 - 1; // adding the significant corresponds to one more unit in exponent
1181 constexpr real lowestRealThatProducesDenormal =
1182 lowestRealThatProducesNormal
1183 - std::numeric_limits<real>::digits; // digits refer to bits in significand, so 24/53 for float/double
1184 constexpr real highestRealThatProducesNormal =
1185 std::numeric_limits<real>::max_exponent
1186 - 1; // adding the significant corresponds to one more unit in exponent
1187 CompareSettings settings;
1189 // Increase the allowed error by the difference between the actual precision and single
1190 setUlpTolSingleAccuracy(ulpTol_);
1192 // Below subnormal range all results should be zero
1193 settings = { Range(lowestReal, lowestRealThatProducesDenormal), ulpTol_, absTol_, MatchRule::Normal };
1194 GMX_EXPECT_SIMD_FUNC_NEAR(std::exp2, exp2SingleAccuracy, settings);
1196 // Subnormal range, require matching, but DTZ is fine
1197 settings = { Range(lowestRealThatProducesDenormal, lowestRealThatProducesNormal),
1201 GMX_EXPECT_SIMD_FUNC_NEAR(std::exp2, exp2SingleAccuracy, settings);
1203 // Normal range, standard result expected
1204 settings = { Range(lowestRealThatProducesNormal, highestRealThatProducesNormal),
1207 MatchRule::Normal };
1208 GMX_EXPECT_SIMD_FUNC_NEAR(std::exp2, exp2SingleAccuracy, settings);
1211 TEST_F(SimdMathTest, exp2SingleAccuracyUnsafe)
1213 // The unsafe version is only defined in the normal range
1214 constexpr real lowestRealThatProducesNormal =
1215 std::numeric_limits<real>::min_exponent
1216 - 1; // adding the significant corresponds to one more unit in exponent
1217 constexpr real highestRealThatProducesNormal =
1218 std::numeric_limits<real>::max_exponent
1219 - 1; // adding the significant corresponds to one more unit in exponent
1221 /* Increase the allowed error by the difference between the actual precision and single */
1222 setUlpTolSingleAccuracy(ulpTol_);
1224 CompareSettings settings{ Range(lowestRealThatProducesNormal, highestRealThatProducesNormal),
1227 MatchRule::Normal };
1228 GMX_EXPECT_SIMD_FUNC_NEAR(std::exp2, exp2SingleAccuracy<MathOptimization::Unsafe>, settings);
1231 TEST_F(SimdMathTest, expSingleAccuracy)
1233 // See threshold point comments in normal exp() test
1234 const real lowestReal = -std::numeric_limits<real>::max();
1235 // In theory the smallest value should be (min_exponent-1)*log(2), but rounding after the multiplication will cause this
1236 // value to be a single ulp too low. This might cause failed tests on CPUs that use different DTZ modes for SIMD vs.
1237 // non-SIMD arithmetics (e.g. ARM v7), so multiply by (1.0-eps) to increase it by a single ulp.
1238 const real lowestRealThatProducesNormal = (std::numeric_limits<real>::min_exponent - 1)
1240 * (1.0 - std::numeric_limits<real>::epsilon());
1241 const real lowestRealThatProducesDenormal =
1242 lowestRealThatProducesNormal - std::numeric_limits<real>::digits * std::log(2.0);
1243 const real highestRealThatProducesNormal =
1244 (std::numeric_limits<real>::max_exponent - 1) * std::log(2.0);
1245 CompareSettings settings;
1247 // Increase the allowed error by the difference between the actual precision and single
1248 setUlpTolSingleAccuracy(ulpTol_);
1250 // Below subnormal range all results should be zero (so, match the reference)
1251 settings = { Range(lowestReal, lowestRealThatProducesDenormal), ulpTol_, absTol_, MatchRule::Normal };
1252 GMX_EXPECT_SIMD_FUNC_NEAR(std::exp, expSingleAccuracy, settings);
1254 // Subnormal range, require matching, but DTZ is fine
1255 settings = { Range(lowestRealThatProducesDenormal, lowestRealThatProducesNormal),
1259 GMX_EXPECT_SIMD_FUNC_NEAR(std::exp, expSingleAccuracy, settings);
1261 // Normal range, standard result expected
1262 settings = { Range(lowestRealThatProducesNormal, highestRealThatProducesNormal),
1265 MatchRule::Normal };
1266 GMX_EXPECT_SIMD_FUNC_NEAR(std::exp, expSingleAccuracy, settings);
1269 TEST_F(SimdMathTest, expSingleAccuracyUnsafe)
1271 // See test of exp() for comments about test ranges
1272 const real lowestRealThatProducesNormal = (std::numeric_limits<real>::min_exponent - 1)
1274 * (1 - std::numeric_limits<real>::epsilon());
1275 const real highestRealThatProducesNormal =
1276 (std::numeric_limits<real>::max_exponent - 1) * std::log(2.0);
1278 // Increase the allowed error by the difference between the actual precision and single
1279 setUlpTolSingleAccuracy(ulpTol_);
1281 CompareSettings settings{ Range(lowestRealThatProducesNormal, highestRealThatProducesNormal),
1284 MatchRule::Normal };
1285 GMX_EXPECT_SIMD_FUNC_NEAR(std::exp, expSingleAccuracy<MathOptimization::Unsafe>, settings);
1288 TEST_F(SimdMathTest, powSingleAccuracy)
1290 // We already test the log2/exp2 components of pow() extensively above, and it's a very
1291 // simple single-line function, so here we just test a handful of values to catch typos
1292 // and then some special values.
1294 // Increase the allowed error by the difference between the actual precision and single
1295 setUlpTolSingleAccuracy(ulpTol_);
1297 GMX_EXPECT_SIMD_REAL_NEAR(setSimdRealFrom3R(std::pow(c0, c3), std::pow(c1, c4), std::pow(c2, c5)),
1298 powSingleAccuracy(rSimd_c0c1c2, rSimd_c3c4c5));
1300 GMX_EXPECT_SIMD_REAL_NEAR(setSimdRealFrom3R(std::pow(c0, -c3), std::pow(c1, -c0), std::pow(c2, -c4)),
1301 powSingleAccuracy(rSimd_c0c1c2, rSimd_m3m0m4));
1303 // 0^0 = 1 , 0^c1=0, -c1^0=1
1304 GMX_EXPECT_SIMD_REAL_NEAR(
1305 setSimdRealFrom3R(1.0, 0.0, 1.0),
1306 powSingleAccuracy(setSimdRealFrom3R(0, 0.0, -c1), setSimdRealFrom3R(0.0, c1, 0.0)));
1309 TEST_F(SimdMathTest, powSingleAccuracyUnsafe)
1311 // We already test the log2/exp2 components of pow() extensively above, and it's a very
1312 // simple single-line function, so here we just test a handful of values to catch typos
1313 // and then some special values.
1315 // Increase the allowed error by the difference between the actual precision and single
1316 setUlpTolSingleAccuracy(ulpTol_);
1318 GMX_EXPECT_SIMD_REAL_NEAR(setSimdRealFrom3R(std::pow(c0, c3), std::pow(c1, c4), std::pow(c2, c5)),
1319 powSingleAccuracy<MathOptimization::Unsafe>(rSimd_c0c1c2, rSimd_c3c4c5));
1321 GMX_EXPECT_SIMD_REAL_NEAR(setSimdRealFrom3R(std::pow(c0, -c3), std::pow(c1, -c0), std::pow(c2, -c4)),
1322 powSingleAccuracy<MathOptimization::Unsafe>(rSimd_c0c1c2, rSimd_m3m0m4));
1325 TEST_F(SimdMathTest, erfSingleAccuracy)
1327 // Increase the allowed error by the difference between the actual precision and single
1328 setUlpTolSingleAccuracy(ulpTol_);
1330 CompareSettings settings{ Range(-9, 9), ulpTol_, GMX_REAL_MIN, MatchRule::Normal };
1331 GMX_EXPECT_SIMD_FUNC_NEAR(refErf, erfSingleAccuracy, settings);
1334 TEST_F(SimdMathTest, erfcSingleAccuracy)
1336 // Increase the allowed error by the difference between the actual precision and single
1337 setUlpTolSingleAccuracy(ulpTol_);
1339 // Our erfc algorithm has 4 ulp accuracy, so relax tolerance a bit
1340 CompareSettings settings{ Range(-9, 9), 4 * ulpTol_, GMX_REAL_MIN, MatchRule::Normal };
1341 GMX_EXPECT_SIMD_FUNC_NEAR(refErfc, erfcSingleAccuracy, settings);
1345 TEST_F(SimdMathTest, sinSingleAccuracy)
1347 /* Increase the allowed error by the difference between the actual precision and single */
1348 setUlpTolSingleAccuracy(ulpTol_);
1350 CompareSettings settings{ Range(-8 * M_PI, 8 * M_PI), ulpTol_, absTol_, MatchRule::Normal };
1351 GMX_EXPECT_SIMD_FUNC_NEAR(std::sin, sinSingleAccuracy, settings);
1353 // Range reduction leads to accuracy loss, so we might want higher tolerance here
1354 settings = { Range(-10000, 10000), 2 * ulpTol_, absTol_, MatchRule::Normal };
1355 GMX_EXPECT_SIMD_FUNC_NEAR(std::sin, sinSingleAccuracy, settings);
1358 TEST_F(SimdMathTest, cosSingleAccuracy)
1360 /* Increase the allowed error by the difference between the actual precision and single */
1361 setUlpTolSingleAccuracy(ulpTol_);
1363 CompareSettings settings{ Range(-8 * M_PI, 8 * M_PI), ulpTol_, absTol_, MatchRule::Normal };
1364 GMX_EXPECT_SIMD_FUNC_NEAR(std::cos, cosSingleAccuracy, settings);
1366 // Range reduction leads to accuracy loss, so we might want higher tolerance here
1367 settings = { Range(-10000, 10000), ulpTol_, absTol_, MatchRule::Normal };
1368 GMX_EXPECT_SIMD_FUNC_NEAR(std::cos, cosSingleAccuracy, settings);
1371 TEST_F(SimdMathTest, tanSingleAccuracy)
1373 /* Increase the allowed error by the difference between the actual precision and single */
1374 setUlpTolSingleAccuracy(ulpTol_);
1376 // Tan(x) is a little sensitive due to the division in the algorithm.
1377 // Rather than using lots of extra FP operations, we accept the algorithm
1378 // presently only achieves a ~3 ulp error and use the medium tolerance.
1379 CompareSettings settings{ Range(-8 * M_PI, 8 * M_PI), ulpTol_, absTol_, MatchRule::Normal };
1380 GMX_EXPECT_SIMD_FUNC_NEAR(std::tan, tanSingleAccuracy, settings);
1382 // Range reduction leads to accuracy loss, so we might want higher tolerance here
1383 settings = { Range(-10000, 10000), ulpTol_, absTol_, MatchRule::Normal };
1384 GMX_EXPECT_SIMD_FUNC_NEAR(std::tan, tanSingleAccuracy, settings);
1387 TEST_F(SimdMathTest, asinSingleAccuracy)
1389 /* Increase the allowed error by the difference between the actual precision and single */
1390 setUlpTolSingleAccuracy(ulpTol_);
1392 // Our present asin(x) algorithm achieves 2-3 ulp accuracy
1393 CompareSettings settings{ Range(-1, 1), ulpTol_, absTol_, MatchRule::Normal };
1394 GMX_EXPECT_SIMD_FUNC_NEAR(std::asin, asinSingleAccuracy, settings);
1397 TEST_F(SimdMathTest, acosSingleAccuracy)
1399 /* Increase the allowed error by the difference between the actual precision and single */
1400 setUlpTolSingleAccuracy(ulpTol_);
1402 // Our present acos(x) algorithm achieves 2-3 ulp accuracy
1403 CompareSettings settings{ Range(-1, 1), ulpTol_, absTol_, MatchRule::Normal };
1404 GMX_EXPECT_SIMD_FUNC_NEAR(std::acos, acosSingleAccuracy, settings);
1407 TEST_F(SimdMathTest, atanSingleAccuracy)
1409 /* Increase the allowed error by the difference between the actual precision and single */
1410 setUlpTolSingleAccuracy(ulpTol_);
1412 // Our present atan(x) algorithm achieves 1 ulp accuracy
1413 CompareSettings settings{ Range(-10000, 10000), ulpTol_, absTol_, MatchRule::Normal };
1414 GMX_EXPECT_SIMD_FUNC_NEAR(std::atan, atanSingleAccuracy, settings);
1417 TEST_F(SimdMathTest, atan2SingleAccuracy)
1419 /* Increase the allowed error by the difference between the actual precision and single */
1420 setUlpTolSingleAccuracy(ulpTol_);
1422 // test each quadrant
1423 GMX_EXPECT_SIMD_REAL_NEAR(
1424 setSimdRealFrom3R(std::atan2(c0, c3), std::atan2(c1, c4), std::atan2(c2, c5)),
1425 atan2SingleAccuracy(rSimd_c0c1c2, rSimd_c3c4c5));
1426 GMX_EXPECT_SIMD_REAL_NEAR(
1427 setSimdRealFrom3R(std::atan2(-c0, c3), std::atan2(-c1, c4), std::atan2(-c2, c5)),
1428 atan2SingleAccuracy(rSimd_m0m1m2, rSimd_c3c4c5));
1429 GMX_EXPECT_SIMD_REAL_NEAR(
1430 setSimdRealFrom3R(std::atan2(-c0, -c3), std::atan2(-c1, -c0), std::atan2(-c2, -c4)),
1431 atan2SingleAccuracy(rSimd_m0m1m2, rSimd_m3m0m4));
1432 GMX_EXPECT_SIMD_REAL_NEAR(
1433 setSimdRealFrom3R(std::atan2(c0, -c3), std::atan2(c1, -c0), std::atan2(c2, -c4)),
1434 atan2SingleAccuracy(rSimd_c0c1c2, rSimd_m3m0m4));
1435 // cases important for calculating angles
1436 // values on coordinate axes
1437 GMX_EXPECT_SIMD_REAL_NEAR(setSimdRealFrom3R(std::atan2(0, c0), std::atan2(0, c1), std::atan2(0, c2)),
1438 atan2SingleAccuracy(setZero(), rSimd_c0c1c2));
1439 GMX_EXPECT_SIMD_REAL_NEAR(setSimdRealFrom3R(std::atan2(c0, 0), std::atan2(c1, 0), std::atan2(c2, 0)),
1440 atan2SingleAccuracy(rSimd_c0c1c2, setZero()));
1441 GMX_EXPECT_SIMD_REAL_NEAR(
1442 setSimdRealFrom3R(std::atan2(0, -c0), std::atan2(0, -c1), std::atan2(0, -c2)),
1443 atan2SingleAccuracy(setZero(), rSimd_m0m1m2));
1444 GMX_EXPECT_SIMD_REAL_NEAR(
1445 setSimdRealFrom3R(std::atan2(-c0, 0), std::atan2(-c1, 0), std::atan2(-c2, 0)),
1446 atan2SingleAccuracy(rSimd_m0m1m2, setZero()));
1448 // degenerate value (origin) should return 0.0. At least IBM xlc 13.1.5 gets the reference
1449 // value wrong (-nan) at -O3 optimization, so we compare to the correct value (0.0) instead.
1450 GMX_EXPECT_SIMD_REAL_NEAR(setSimdRealFrom1R(0.0),
1451 atan2SingleAccuracy(setSimdRealFrom3R(0.0, 0.0, 0.0), setZero()));
1454 TEST_F(SimdMathTest, pmeForceCorrectionSingleAccuracy)
1456 // The PME corrections will be added to ~1/r2, so absolute tolerance of EPS is fine.
1457 // Pme correction only needs to be ~1e-6 accuracy single.
1458 // Then increase the allowed error by the difference between the actual precision and single.
1459 setUlpTolSingleAccuracy(std::int64_t(5e-6 / GMX_FLOAT_EPS));
1461 CompareSettings settings{ Range(0.15, 4), ulpTol_, GMX_FLOAT_EPS, MatchRule::Normal };
1462 GMX_EXPECT_SIMD_FUNC_NEAR(refPmeForceCorrection, pmeForceCorrectionSingleAccuracy, settings);
1465 TEST_F(SimdMathTest, pmePotentialCorrectionSingleAccuracy)
1467 // The PME corrections will be added to ~1/r, so absolute tolerance of EPS is fine.
1468 // Pme correction only needs to be ~1e-6 accuracy single.
1469 // Then increase the allowed error by the difference between the actual precision and single.
1470 setUlpTolSingleAccuracy(std::int64_t(5e-6 / GMX_FLOAT_EPS));
1472 CompareSettings settings{ Range(0.15, 4), ulpTol_, GMX_FLOAT_EPS, MatchRule::Normal };
1473 GMX_EXPECT_SIMD_FUNC_NEAR(refPmePotentialCorrection, pmePotentialCorrectionSingleAccuracy, settings);
1478 # endif // GMX_SIMD_HAVE_REAL