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authorGravatar Gael Guennebaud <g.gael@free.fr>2016-10-12 16:30:51 +0000
committerGravatar Gael Guennebaud <g.gael@free.fr>2016-10-12 16:30:51 +0000
commit5c366fe1d7a5efe31aeaec6162adcadf9279503a (patch)
treea7ce87f37f457d859818aeca70a2195d1e57420b
parent89e315152c759f298c144fd25f67b1a9a375ee08 (diff)
parent47150af1c8e22174296d6b2077d719c5b786b1b0 (diff)
Merged in rmlarsen/eigen (pull request PR-230)
Fix a bug in psqrt for SSE and AVX when EIGEN_FAST_MATH=1
-rw-r--r--Eigen/src/Core/arch/AVX/MathFunctions.h35
-rw-r--r--Eigen/src/Core/arch/SSE/MathFunctions.h28
-rw-r--r--test/packetmath.cpp31
3 files changed, 48 insertions, 46 deletions
diff --git a/Eigen/src/Core/arch/AVX/MathFunctions.h b/Eigen/src/Core/arch/AVX/MathFunctions.h
index d21ec39dd..6af67ce2d 100644
--- a/Eigen/src/Core/arch/AVX/MathFunctions.h
+++ b/Eigen/src/Core/arch/AVX/MathFunctions.h
@@ -355,30 +355,27 @@ pexp<Packet4d>(const Packet4d& _x) {
// Functions for sqrt.
// The EIGEN_FAST_MATH version uses the _mm_rsqrt_ps approximation and one step
// of Newton's method, at a cost of 1-2 bits of precision as opposed to the
-// exact solution. The main advantage of this approach is not just speed, but
-// also the fact that it can be inlined and pipelined with other computations,
-// further reducing its effective latency.
+// exact solution. It does not handle +inf, or denormalized numbers correctly.
+// The main advantage of this approach is not just speed, but also the fact that
+// it can be inlined and pipelined with other computations, further reducing its
+// effective latency. This is similar to Quake3's fast inverse square root.
+// For detail see here: http://www.beyond3d.com/content/articles/8/
#if EIGEN_FAST_MATH
template <>
EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8f
psqrt<Packet8f>(const Packet8f& _x) {
- _EIGEN_DECLARE_CONST_Packet8f(one_point_five, 1.5f);
- _EIGEN_DECLARE_CONST_Packet8f(minus_half, -0.5f);
- _EIGEN_DECLARE_CONST_Packet8f_FROM_INT(flt_min, 0x00800000);
-
- Packet8f neg_half = pmul(_x, p8f_minus_half);
-
- // select only the inverse sqrt of positive normal inputs (denormals are
- // flushed to zero and cause infs as well).
- Packet8f non_zero_mask = _mm256_cmp_ps(_x, p8f_flt_min, _CMP_GE_OQ);
- Packet8f x = _mm256_and_ps(non_zero_mask, _mm256_rsqrt_ps(_x));
-
+ Packet8f half = pmul(_x, pset1<Packet8f>(.5f));
+ Packet8f denormal_mask = _mm256_and_ps(
+ _mm256_cmp_ps(_x, pset1<Packet8f>((std::numeric_limits<float>::min)()),
+ _CMP_LT_OQ),
+ _mm256_cmp_ps(_x, _mm256_setzero_ps(), _CMP_GE_OQ));
+
+ // Compute approximate reciprocal sqrt.
+ Packet8f x = _mm256_rsqrt_ps(_x);
// Do a single step of Newton's iteration.
- x = pmul(x, pmadd(neg_half, pmul(x, x), p8f_one_point_five));
-
- // Multiply the original _x by it's reciprocal square root to extract the
- // square root.
- return pmul(_x, x);
+ x = pmul(x, psub(pset1<Packet8f>(1.5f), pmul(half, pmul(x,x))));
+ // Flush results for denormals to zero.
+ return _mm256_andnot_ps(denormal_mask, pmul(_x,x));
}
#else
template <> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
diff --git a/Eigen/src/Core/arch/SSE/MathFunctions.h b/Eigen/src/Core/arch/SSE/MathFunctions.h
index ac2fd8103..7b5f948e1 100644
--- a/Eigen/src/Core/arch/SSE/MathFunctions.h
+++ b/Eigen/src/Core/arch/SSE/MathFunctions.h
@@ -32,7 +32,7 @@ Packet4f plog<Packet4f>(const Packet4f& _x)
/* the smallest non denormalized float number */
_EIGEN_DECLARE_CONST_Packet4f_FROM_INT(min_norm_pos, 0x00800000);
_EIGEN_DECLARE_CONST_Packet4f_FROM_INT(minus_inf, 0xff800000);//-1.f/0.f);
-
+
/* natural logarithm computed for 4 simultaneous float
return NaN for x <= 0
*/
@@ -444,25 +444,33 @@ Packet4f pcos<Packet4f>(const Packet4f& _x)
#if EIGEN_FAST_MATH
-// This is based on Quake3's fast inverse square root.
+// Functions for sqrt.
+// The EIGEN_FAST_MATH version uses the _mm_rsqrt_ps approximation and one step
+// of Newton's method, at a cost of 1-2 bits of precision as opposed to the
+// exact solution. It does not handle +inf, or denormalized numbers correctly.
+// The main advantage of this approach is not just speed, but also the fact that
+// it can be inlined and pipelined with other computations, further reducing its
+// effective latency. This is similar to Quake3's fast inverse square root.
// For detail see here: http://www.beyond3d.com/content/articles/8/
-// It lacks 1 (or 2 bits in some rare cases) of precision, and does not handle negative, +inf, or denormalized numbers correctly.
template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
Packet4f psqrt<Packet4f>(const Packet4f& _x)
{
Packet4f half = pmul(_x, pset1<Packet4f>(.5f));
+ Packet4f denormal_mask = _mm_and_ps(
+ _mm_cmpge_ps(_x, _mm_setzero_ps()),
+ _mm_cmplt_ps(_x, pset1<Packet4f>((std::numeric_limits<float>::min)())));
- /* select only the inverse sqrt of non-zero inputs */
- Packet4f non_zero_mask = _mm_cmpge_ps(_x, pset1<Packet4f>((std::numeric_limits<float>::min)()));
- Packet4f x = _mm_and_ps(non_zero_mask, _mm_rsqrt_ps(_x));
-
+ // Compute approximate reciprocal sqrt.
+ Packet4f x = _mm_rsqrt_ps(_x);
+ // Do a single step of Newton's iteration.
x = pmul(x, psub(pset1<Packet4f>(1.5f), pmul(half, pmul(x,x))));
- return pmul(_x,x);
+ // Flush results for denormals to zero.
+ return _mm_andnot_ps(denormal_mask, pmul(_x,x));
}
#else
-template<>EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+template<>EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
Packet4f psqrt<Packet4f>(const Packet4f& x) { return _mm_sqrt_ps(x); }
#endif
@@ -491,7 +499,7 @@ Packet4f prsqrt<Packet4f>(const Packet4f& _x) {
Packet4f neg_mask = _mm_cmplt_ps(_x, _mm_setzero_ps());
Packet4f zero_mask = _mm_andnot_ps(neg_mask, le_zero_mask);
Packet4f infs_and_nans = _mm_or_ps(_mm_and_ps(neg_mask, p4f_nan),
- _mm_and_ps(zero_mask, p4f_inf));
+ _mm_and_ps(zero_mask, p4f_inf));
// Do a single step of Newton's iteration.
x = pmul(x, pmadd(neg_half, pmul(x, x), p4f_one_point_five));
diff --git a/test/packetmath.cpp b/test/packetmath.cpp
index 1394d9f2b..c3d3e1521 100644
--- a/test/packetmath.cpp
+++ b/test/packetmath.cpp
@@ -193,7 +193,7 @@ template<typename Scalar> void packetmath()
internal::pstore(data2+3*PacketSize, A3);
VERIFY(areApprox(ref, data2, 4*PacketSize) && "internal::pbroadcast4");
}
-
+
{
for (int i=0; i<PacketSize*2; ++i)
ref[i] = data1[i/PacketSize];
@@ -203,9 +203,9 @@ template<typename Scalar> void packetmath()
internal::pstore(data2+1*PacketSize, A1);
VERIFY(areApprox(ref, data2, 2*PacketSize) && "internal::pbroadcast2");
}
-
+
VERIFY(internal::isApprox(data1[0], internal::pfirst(internal::pload<Packet>(data1))) && "internal::pfirst");
-
+
if(PacketSize>1)
{
for(int offset=0;offset<4;++offset)
@@ -315,7 +315,7 @@ template<typename Scalar> void packetmath_real()
CHECK_CWISE1_IF(PacketTraits::HasRound, numext::round, internal::pround);
CHECK_CWISE1_IF(PacketTraits::HasCeil, numext::ceil, internal::pceil);
CHECK_CWISE1_IF(PacketTraits::HasFloor, numext::floor, internal::pfloor);
-
+
for (int i=0; i<size; ++i)
{
data1[i] = internal::random<Scalar>(-1,1);
@@ -440,12 +440,9 @@ template<typename Scalar> void packetmath_real()
data1[0] = Scalar(-1.0f);
h.store(data2, internal::plog(h.load(data1)));
VERIFY((numext::isnan)(data2[0]));
-#if !EIGEN_FAST_MATH
h.store(data2, internal::psqrt(h.load(data1)));
VERIFY((numext::isnan)(data2[0]));
VERIFY((numext::isnan)(data2[1]));
-#endif
-
}
}
@@ -459,7 +456,7 @@ template<typename Scalar> void packetmath_notcomplex()
EIGEN_ALIGN_MAX Scalar data1[PacketTraits::size*4];
EIGEN_ALIGN_MAX Scalar data2[PacketTraits::size*4];
EIGEN_ALIGN_MAX Scalar ref[PacketTraits::size*4];
-
+
Array<Scalar,Dynamic,1>::Map(data1, PacketTraits::size*4).setRandom();
ref[0] = data1[0];
@@ -478,7 +475,7 @@ template<typename Scalar> void packetmath_notcomplex()
for (int i=0; i<PacketSize; ++i)
ref[0] = (std::max)(ref[0],data1[i]);
VERIFY(internal::isApprox(ref[0], internal::predux_max(internal::pload<Packet>(data1))) && "internal::predux_max");
-
+
for (int i=0; i<PacketSize; ++i)
ref[i] = data1[0]+Scalar(i);
internal::pstore(data2, internal::plset<Packet>(data1[0]));
@@ -490,12 +487,12 @@ template<typename Scalar,bool ConjLhs,bool ConjRhs> void test_conj_helper(Scalar
typedef internal::packet_traits<Scalar> PacketTraits;
typedef typename PacketTraits::type Packet;
const int PacketSize = PacketTraits::size;
-
+
internal::conj_if<ConjLhs> cj0;
internal::conj_if<ConjRhs> cj1;
internal::conj_helper<Scalar,Scalar,ConjLhs,ConjRhs> cj;
internal::conj_helper<Packet,Packet,ConjLhs,ConjRhs> pcj;
-
+
for(int i=0;i<PacketSize;++i)
{
ref[i] = cj0(data1[i]) * cj1(data2[i]);
@@ -503,7 +500,7 @@ template<typename Scalar,bool ConjLhs,bool ConjRhs> void test_conj_helper(Scalar
}
internal::pstore(pval,pcj.pmul(internal::pload<Packet>(data1),internal::pload<Packet>(data2)));
VERIFY(areApprox(ref, pval, PacketSize) && "conj_helper pmul");
-
+
for(int i=0;i<PacketSize;++i)
{
Scalar tmp = ref[i];
@@ -531,12 +528,12 @@ template<typename Scalar> void packetmath_complex()
data1[i] = internal::random<Scalar>() * Scalar(1e2);
data2[i] = internal::random<Scalar>() * Scalar(1e2);
}
-
+
test_conj_helper<Scalar,false,false> (data1,data2,ref,pval);
test_conj_helper<Scalar,false,true> (data1,data2,ref,pval);
test_conj_helper<Scalar,true,false> (data1,data2,ref,pval);
test_conj_helper<Scalar,true,true> (data1,data2,ref,pval);
-
+
{
for(int i=0;i<PacketSize;++i)
ref[i] = Scalar(std::imag(data1[i]),std::real(data1[i]));
@@ -556,9 +553,9 @@ template<typename Scalar> void packetmath_scatter_gather()
for (int i=0; i<PacketSize; ++i) {
data1[i] = internal::random<Scalar>()/RealScalar(PacketSize);
}
-
+
int stride = internal::random<int>(1,20);
-
+
EIGEN_ALIGN_MAX Scalar buffer[PacketSize*20];
memset(buffer, 0, 20*sizeof(Packet));
Packet packet = internal::pload<Packet>(data1);
@@ -594,7 +591,7 @@ void test_packetmath()
CALL_SUBTEST_1( packetmath_notcomplex<float>() );
CALL_SUBTEST_2( packetmath_notcomplex<double>() );
CALL_SUBTEST_3( packetmath_notcomplex<int>() );
-
+
CALL_SUBTEST_1( packetmath_real<float>() );
CALL_SUBTEST_2( packetmath_real<double>() );