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Unified Diff: src/opts/Sk2x_neon.h

Issue 1048593002: Refactor Sk2x<T> + Sk4x<T> into SkNf<N,T> and SkNi<N,T> (Closed) Base URL: https://skia.googlesource.com/skia.git@master
Patch Set: This is actually faster Created 5 years, 9 months ago
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Index: src/opts/Sk2x_neon.h
diff --git a/src/opts/Sk2x_neon.h b/src/opts/Sk2x_neon.h
deleted file mode 100644
index 8e6e46164b9fde728303ed43854cd5798335055a..0000000000000000000000000000000000000000
--- a/src/opts/Sk2x_neon.h
+++ /dev/null
@@ -1,158 +0,0 @@
-/*
- * Copyright 2015 Google Inc.
- *
- * Use of this source code is governed by a BSD-style license that can be
- * found in the LICENSE file.
- */
-
-// It is important _not_ to put header guards here.
-// This file will be intentionally included three times.
-
-#include "SkTypes.h" // Keep this before any #ifdef for skbug.com/3362
-
-#if defined(SK2X_PREAMBLE)
- #include <arm_neon.h>
- #include <math.h>
- template <typename T> struct SkScalarToSIMD;
- template <> struct SkScalarToSIMD< float> { typedef float32x2_t Type; };
- #if defined(SK_CPU_ARM64)
- template <> struct SkScalarToSIMD<double> { typedef float64x2_t Type; };
- #else
- template <> struct SkScalarToSIMD<double> { typedef double Type[2]; };
- #endif
-
-
-#elif defined(SK2X_PRIVATE)
- typename SkScalarToSIMD<T>::Type fVec;
- /*implicit*/ Sk2x(const typename SkScalarToSIMD<T>::Type vec) { fVec = vec; }
-
-#else
-
-#define M(...) template <> inline __VA_ARGS__ Sk2x<float>::
-
-M() Sk2x() {}
-M() Sk2x(float val) { fVec = vdup_n_f32(val); }
-M() Sk2x(float a, float b) { fVec = (float32x2_t) { a, b }; }
-M(Sk2f&) operator=(const Sk2f& o) { fVec = o.fVec; return *this; }
-
-M(Sk2f) Load(const float vals[2]) { return vld1_f32(vals); }
-M(void) store(float vals[2]) const { vst1_f32(vals, fVec); }
-
-M(Sk2f) approxInvert() const {
- float32x2_t est0 = vrecpe_f32(fVec),
- est1 = vmul_f32(vrecps_f32(est0, fVec), est0);
- return est1;
-}
-
-M(Sk2f) invert() const {
- float32x2_t est1 = this->approxInvert().fVec,
- est2 = vmul_f32(vrecps_f32(est1, fVec), est1);
- return est2;
-}
-
-M(Sk2f) add(const Sk2f& o) const { return vadd_f32(fVec, o.fVec); }
-M(Sk2f) subtract(const Sk2f& o) const { return vsub_f32(fVec, o.fVec); }
-M(Sk2f) multiply(const Sk2f& o) const { return vmul_f32(fVec, o.fVec); }
-M(Sk2f) divide(const Sk2f& o) const {
-#if defined(SK_CPU_ARM64)
- return vdiv_f32(fVec, o.fVec);
-#else
- return vmul_f32(fVec, o.invert().fVec);
-#endif
-}
-
-M(Sk2f) Min(const Sk2f& a, const Sk2f& b) { return vmin_f32(a.fVec, b.fVec); }
-M(Sk2f) Max(const Sk2f& a, const Sk2f& b) { return vmax_f32(a.fVec, b.fVec); }
-
-M(Sk2f) rsqrt() const {
- float32x2_t est0 = vrsqrte_f32(fVec),
- est1 = vmul_f32(vrsqrts_f32(fVec, vmul_f32(est0, est0)), est0);
- return est1;
-}
-M(Sk2f) sqrt() const {
-#if defined(SK_CPU_ARM64)
- return vsqrt_f32(fVec);
-#else
- float32x2_t est1 = this->rsqrt().fVec,
- // An extra step of Newton's method to refine the estimate of 1/sqrt(this).
- est2 = vmul_f32(vrsqrts_f32(fVec, vmul_f32(est1, est1)), est1);
- return vmul_f32(fVec, est2);
-#endif
-}
-
-#undef M
-
-#define M(...) template <> inline __VA_ARGS__ Sk2x<double>::
-
-#if defined(SK_CPU_ARM64)
- M() Sk2x() {}
- M() Sk2x(double val) { fVec = vdupq_n_f64(val); }
- M() Sk2x(double a, double b) { fVec = (float64x2_t) { a, b }; }
- M(Sk2d&) operator=(const Sk2d& o) { fVec = o.fVec; return *this; }
-
- M(Sk2d) Load(const double vals[2]) { return vld1q_f64(vals); }
- M(void) store(double vals[2]) const { vst1q_f64(vals, fVec); }
-
- M(Sk2d) add(const Sk2d& o) const { return vaddq_f64(fVec, o.fVec); }
- M(Sk2d) subtract(const Sk2d& o) const { return vsubq_f64(fVec, o.fVec); }
- M(Sk2d) multiply(const Sk2d& o) const { return vmulq_f64(fVec, o.fVec); }
- M(Sk2d) divide(const Sk2d& o) const { return vdivq_f64(fVec, o.fVec); }
-
- M(Sk2d) Min(const Sk2d& a, const Sk2d& b) { return vminq_f64(a.fVec, b.fVec); }
- M(Sk2d) Max(const Sk2d& a, const Sk2d& b) { return vmaxq_f64(a.fVec, b.fVec); }
-
- M(Sk2d) rsqrt() const {
- float64x2_t est0 = vrsqrteq_f64(fVec),
- est1 = vmulq_f64(vrsqrtsq_f64(fVec, vmulq_f64(est0, est0)), est0);
- return est1;
- }
- M(Sk2d) sqrt() const { return vsqrtq_f64(fVec); }
-
- M(Sk2d) approxInvert() const {
- float64x2_t est0 = vrecpeq_f64(fVec),
- est1 = vmulq_f64(vrecpsq_f64(est0, fVec), est0);
- return est1;
- }
-
- M(Sk2d) invert() const {
- float64x2_t est1 = this->approxInvert().fVec,
- est2 = vmulq_f64(vrecpsq_f64(est1, fVec), est1),
- est3 = vmulq_f64(vrecpsq_f64(est2, fVec), est2);
- return est3;
- }
-
-#else // Scalar implementation for 32-bit chips, which don't have float64x2_t.
- M() Sk2x() {}
- M() Sk2x(double val) { fVec[0] = fVec[1] = val; }
- M() Sk2x(double a, double b) { fVec[0] = a; fVec[1] = b; }
- M(Sk2d&) operator=(const Sk2d& o) {
- fVec[0] = o.fVec[0];
- fVec[1] = o.fVec[1];
- return *this;
- }
-
- M(Sk2d) Load(const double vals[2]) { return Sk2d(vals[0], vals[1]); }
- M(void) store(double vals[2]) const { vals[0] = fVec[0]; vals[1] = fVec[1]; }
-
- M(Sk2d) add(const Sk2d& o) const { return Sk2d(fVec[0] + o.fVec[0], fVec[1] + o.fVec[1]); }
- M(Sk2d) subtract(const Sk2d& o) const { return Sk2d(fVec[0] - o.fVec[0], fVec[1] - o.fVec[1]); }
- M(Sk2d) multiply(const Sk2d& o) const { return Sk2d(fVec[0] * o.fVec[0], fVec[1] * o.fVec[1]); }
- M(Sk2d) divide(const Sk2d& o) const { return Sk2d(fVec[0] / o.fVec[0], fVec[1] / o.fVec[1]); }
-
- M(Sk2d) Min(const Sk2d& a, const Sk2d& b) {
- return Sk2d(SkTMin(a.fVec[0], b.fVec[0]), SkTMin(a.fVec[1], b.fVec[1]));
- }
- M(Sk2d) Max(const Sk2d& a, const Sk2d& b) {
- return Sk2d(SkTMax(a.fVec[0], b.fVec[0]), SkTMax(a.fVec[1], b.fVec[1]));
- }
-
- M(Sk2d) rsqrt() const { return Sk2d(1.0/::sqrt(fVec[0]), 1.0/::sqrt(fVec[1])); }
- M(Sk2d) sqrt() const { return Sk2d( ::sqrt(fVec[0]), ::sqrt(fVec[1])); }
-
- M(Sk2d) invert() const { return Sk2d(1.0 / fVec[0], 1.0 / fVec[1]); }
- M(Sk2d) approxInvert() const { return this->invert(); }
-#endif
-
-#undef M
-
-#endif
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