| /* |
| * Copyright 2019 Google Inc. |
| * |
| * Use of this source code is governed by a BSD-style license that can be |
| * found in the LICENSE file. |
| */ |
| |
| #ifndef SKVX_DEFINED |
| #define SKVX_DEFINED |
| |
| // skvx::Vec<N,T> are SIMD vectors of N T's, a v1.5 successor to SkNx<N,T>. |
| // |
| // This time we're leaning a bit less on platform-specific intrinsics and a bit |
| // more on Clang/GCC vector extensions, but still keeping the option open to |
| // drop in platform-specific intrinsics, actually more easily than before. |
| // |
| // We've also fixed a few of the caveats that used to make SkNx awkward to work |
| // with across translation units. skvx::Vec<N,T> always has N*sizeof(T) size |
| // and alignment and is safe to use across translation units freely. |
| // (Ideally we'd only align to T, but that tanks ARMv7 NEON codegen.) |
| |
| // Please try to keep this file independent of Skia headers. |
| #include <algorithm> // std::min, std::max |
| #include <cassert> // assert() |
| #include <cmath> // ceilf, floorf, truncf, roundf, sqrtf, etc. |
| #include <cstdint> // intXX_t |
| #include <cstring> // memcpy() |
| #include <initializer_list> // std::initializer_list |
| #include <utility> // std::index_sequence |
| |
| #if defined(__SSE__) || defined(__AVX__) || defined(__AVX2__) |
| #include <immintrin.h> |
| #elif defined(__ARM_NEON) |
| #include <arm_neon.h> |
| #elif defined(__wasm_simd128__) |
| #include <wasm_simd128.h> |
| #endif |
| |
| // To avoid ODR violations, all methods must be force-inlined... |
| #if defined(_MSC_VER) |
| #define SKVX_ALWAYS_INLINE __forceinline |
| #else |
| #define SKVX_ALWAYS_INLINE __attribute__((always_inline)) |
| #endif |
| |
| // ... and all standalone functions must be static. Please use these helpers: |
| #define SI static inline |
| #define SIT template < typename T> SI |
| #define SIN template <int N > SI |
| #define SINT template <int N, typename T> SI |
| #define SINTU template <int N, typename T, typename U, \ |
| typename=std::enable_if_t<std::is_convertible<U,T>::value>> SI |
| |
| namespace skvx { |
| |
| template <int N, typename T> |
| struct alignas(N*sizeof(T)) Vec; |
| |
| template <int... Ix, int N, typename T> |
| SI Vec<sizeof...(Ix),T> shuffle(const Vec<N,T>&); |
| |
| template <typename D, typename S> |
| SI D bit_pun(const S&); |
| |
| // All Vec have the same simple memory layout, the same as `T vec[N]`. |
| template <int N, typename T> |
| struct alignas(N*sizeof(T)) VecStorage { |
| SKVX_ALWAYS_INLINE VecStorage() = default; |
| SKVX_ALWAYS_INLINE VecStorage(T s) : lo(s), hi(s) {} |
| |
| Vec<N/2,T> lo, hi; |
| }; |
| |
| template <typename T> |
| struct VecStorage<4,T> { |
| SKVX_ALWAYS_INLINE VecStorage() = default; |
| SKVX_ALWAYS_INLINE VecStorage(T s) : lo(s), hi(s) {} |
| SKVX_ALWAYS_INLINE VecStorage(T x, T y, T z, T w) : lo(x,y), hi(z, w) {} |
| SKVX_ALWAYS_INLINE VecStorage(Vec<2,T> xy, T z, T w) : lo(xy), hi(z,w) {} |
| SKVX_ALWAYS_INLINE VecStorage(T x, T y, Vec<2,T> zw) : lo(x,y), hi(zw) {} |
| SKVX_ALWAYS_INLINE VecStorage(Vec<2,T> xy, Vec<2,T> zw) : lo(xy), hi(zw) {} |
| |
| SKVX_ALWAYS_INLINE Vec<2,T>& xy() { return lo; } |
| SKVX_ALWAYS_INLINE Vec<2,T>& zw() { return hi; } |
| SKVX_ALWAYS_INLINE T& x() { return lo.lo.val; } |
| SKVX_ALWAYS_INLINE T& y() { return lo.hi.val; } |
| SKVX_ALWAYS_INLINE T& z() { return hi.lo.val; } |
| SKVX_ALWAYS_INLINE T& w() { return hi.hi.val; } |
| |
| SKVX_ALWAYS_INLINE Vec<2,T> xy() const { return lo; } |
| SKVX_ALWAYS_INLINE Vec<2,T> zw() const { return hi; } |
| SKVX_ALWAYS_INLINE T x() const { return lo.lo.val; } |
| SKVX_ALWAYS_INLINE T y() const { return lo.hi.val; } |
| SKVX_ALWAYS_INLINE T z() const { return hi.lo.val; } |
| SKVX_ALWAYS_INLINE T w() const { return hi.hi.val; } |
| |
| // Exchange-based swizzles. These should take 1 cycle on NEON and 3 (pipelined) cycles on SSE. |
| SKVX_ALWAYS_INLINE Vec<4,T> yxwz() const { return shuffle<1,0,3,2>(bit_pun<Vec<4,T>>(*this)); } |
| SKVX_ALWAYS_INLINE Vec<4,T> zwxy() const { return shuffle<2,3,0,1>(bit_pun<Vec<4,T>>(*this)); } |
| |
| Vec<2,T> lo, hi; |
| }; |
| |
| template <typename T> |
| struct VecStorage<2,T> { |
| SKVX_ALWAYS_INLINE VecStorage() = default; |
| SKVX_ALWAYS_INLINE VecStorage(T s) : lo(s), hi(s) {} |
| SKVX_ALWAYS_INLINE VecStorage(T x, T y) : lo(x), hi(y) {} |
| |
| SKVX_ALWAYS_INLINE T& x() { return lo.val; } |
| SKVX_ALWAYS_INLINE T& y() { return hi.val; } |
| |
| SKVX_ALWAYS_INLINE T x() const { return lo.val; } |
| SKVX_ALWAYS_INLINE T y() const { return hi.val; } |
| |
| // This exchange-based swizzle should take 1 cycle on NEON and 3 (pipelined) cycles on SSE. |
| SKVX_ALWAYS_INLINE Vec<2,T> yx() const { return shuffle<1,0>(bit_pun<Vec<2,T>>(*this)); } |
| |
| SKVX_ALWAYS_INLINE Vec<4,T> xyxy() const { |
| return Vec<4,T>(bit_pun<Vec<2,T>>(*this), bit_pun<Vec<2,T>>(*this)); |
| } |
| |
| Vec<1,T> lo, hi; |
| }; |
| |
| template <int N, typename T> |
| struct alignas(N*sizeof(T)) Vec : public VecStorage<N,T> { |
| static_assert((N & (N-1)) == 0, "N must be a power of 2."); |
| static_assert(sizeof(T) >= alignof(T), "What kind of unusual T is this?"); |
| |
| // Methods belong here in the class declaration of Vec only if: |
| // - they must be here, like constructors or operator[]; |
| // - they'll definitely never want a specialized implementation. |
| // Other operations on Vec should be defined outside the type. |
| |
| SKVX_ALWAYS_INLINE Vec() = default; |
| |
| using VecStorage<N,T>::VecStorage; |
| |
| SKVX_ALWAYS_INLINE Vec(std::initializer_list<T> xs) { |
| T vals[N] = {0}; |
| memcpy(vals, xs.begin(), std::min(xs.size(), (size_t)N)*sizeof(T)); |
| |
| this->lo = Vec<N/2,T>::Load(vals + 0); |
| this->hi = Vec<N/2,T>::Load(vals + N/2); |
| } |
| |
| SKVX_ALWAYS_INLINE T operator[](int i) const { return i<N/2 ? this->lo[i] : this->hi[i-N/2]; } |
| SKVX_ALWAYS_INLINE T& operator[](int i) { return i<N/2 ? this->lo[i] : this->hi[i-N/2]; } |
| |
| SKVX_ALWAYS_INLINE static Vec Load(const void* ptr) { |
| Vec v; |
| memcpy(&v, ptr, sizeof(Vec)); |
| return v; |
| } |
| SKVX_ALWAYS_INLINE void store(void* ptr) const { |
| memcpy(ptr, this, sizeof(Vec)); |
| } |
| }; |
| |
| template <typename T> |
| struct Vec<1,T> { |
| T val; |
| |
| SKVX_ALWAYS_INLINE Vec() = default; |
| |
| Vec(T s) : val(s) {} |
| |
| SKVX_ALWAYS_INLINE Vec(std::initializer_list<T> xs) : val(xs.size() ? *xs.begin() : 0) {} |
| |
| SKVX_ALWAYS_INLINE T operator[](int) const { return val; } |
| SKVX_ALWAYS_INLINE T& operator[](int) { return val; } |
| |
| SKVX_ALWAYS_INLINE static Vec Load(const void* ptr) { |
| Vec v; |
| memcpy(&v, ptr, sizeof(Vec)); |
| return v; |
| } |
| SKVX_ALWAYS_INLINE void store(void* ptr) const { |
| memcpy(ptr, this, sizeof(Vec)); |
| } |
| }; |
| |
| // Ideally we'd only use bit_pun(), but until this file is always built as C++17 with constexpr if, |
| // we'll sometimes find need to use unchecked_bit_pun(). Please do check the call sites yourself! |
| template <typename D, typename S> |
| SI D unchecked_bit_pun(const S& s) { |
| D d; |
| memcpy(&d, &s, sizeof(D)); |
| return d; |
| } |
| |
| template <typename D, typename S> |
| SI D bit_pun(const S& s) { |
| static_assert(sizeof(D) == sizeof(S), ""); |
| return unchecked_bit_pun<D>(s); |
| } |
| |
| // Translate from a value type T to its corresponding Mask, the result of a comparison. |
| template <typename T> struct Mask { using type = T; }; |
| template <> struct Mask<float > { using type = int32_t; }; |
| template <> struct Mask<double> { using type = int64_t; }; |
| template <typename T> using M = typename Mask<T>::type; |
| |
| // Join two Vec<N,T> into one Vec<2N,T>. |
| SINT Vec<2*N,T> join(const Vec<N,T>& lo, const Vec<N,T>& hi) { |
| Vec<2*N,T> v; |
| v.lo = lo; |
| v.hi = hi; |
| return v; |
| } |
| |
| // We have three strategies for implementing Vec operations: |
| // 1) lean on Clang/GCC vector extensions when available; |
| // 2) use map() to apply a scalar function lane-wise; |
| // 3) recurse on lo/hi to scalar portable implementations. |
| // We can slot in platform-specific implementations as overloads for particular Vec<N,T>, |
| // or often integrate them directly into the recursion of style 3), allowing fine control. |
| |
| #if !defined(SKNX_NO_SIMD) && (defined(__clang__) || defined(__GNUC__)) |
| |
| // VExt<N,T> types have the same size as Vec<N,T> and support most operations directly. |
| #if defined(__clang__) |
| template <int N, typename T> |
| using VExt = T __attribute__((ext_vector_type(N))); |
| |
| #elif defined(__GNUC__) |
| template <int N, typename T> |
| struct VExtHelper { |
| typedef T __attribute__((vector_size(N*sizeof(T)))) type; |
| }; |
| |
| template <int N, typename T> |
| using VExt = typename VExtHelper<N,T>::type; |
| |
| // For some reason some (new!) versions of GCC cannot seem to deduce N in the generic |
| // to_vec<N,T>() below for N=4 and T=float. This workaround seems to help... |
| SI Vec<4,float> to_vec(VExt<4,float> v) { return bit_pun<Vec<4,float>>(v); } |
| #endif |
| |
| SINT VExt<N,T> to_vext(const Vec<N,T>& v) { return bit_pun<VExt<N,T>>(v); } |
| SINT Vec <N,T> to_vec(const VExt<N,T>& v) { return bit_pun<Vec <N,T>>(v); } |
| |
| SINT Vec<N,T> operator+(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return to_vec<N,T>(to_vext(x) + to_vext(y)); |
| } |
| SINT Vec<N,T> operator-(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return to_vec<N,T>(to_vext(x) - to_vext(y)); |
| } |
| SINT Vec<N,T> operator*(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return to_vec<N,T>(to_vext(x) * to_vext(y)); |
| } |
| SINT Vec<N,T> operator/(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return to_vec<N,T>(to_vext(x) / to_vext(y)); |
| } |
| |
| SINT Vec<N,T> operator^(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return to_vec<N,T>(to_vext(x) ^ to_vext(y)); |
| } |
| SINT Vec<N,T> operator&(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return to_vec<N,T>(to_vext(x) & to_vext(y)); |
| } |
| SINT Vec<N,T> operator|(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return to_vec<N,T>(to_vext(x) | to_vext(y)); |
| } |
| |
| SINT Vec<N,T> operator!(const Vec<N,T>& x) { return to_vec<N,T>(!to_vext(x)); } |
| SINT Vec<N,T> operator-(const Vec<N,T>& x) { return to_vec<N,T>(-to_vext(x)); } |
| SINT Vec<N,T> operator~(const Vec<N,T>& x) { return to_vec<N,T>(~to_vext(x)); } |
| |
| SINT Vec<N,T> operator<<(const Vec<N,T>& x, int k) { return to_vec<N,T>(to_vext(x) << k); } |
| SINT Vec<N,T> operator>>(const Vec<N,T>& x, int k) { return to_vec<N,T>(to_vext(x) >> k); } |
| |
| SINT Vec<N,M<T>> operator==(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return bit_pun<Vec<N,M<T>>>(to_vext(x) == to_vext(y)); |
| } |
| SINT Vec<N,M<T>> operator!=(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return bit_pun<Vec<N,M<T>>>(to_vext(x) != to_vext(y)); |
| } |
| SINT Vec<N,M<T>> operator<=(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return bit_pun<Vec<N,M<T>>>(to_vext(x) <= to_vext(y)); |
| } |
| SINT Vec<N,M<T>> operator>=(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return bit_pun<Vec<N,M<T>>>(to_vext(x) >= to_vext(y)); |
| } |
| SINT Vec<N,M<T>> operator< (const Vec<N,T>& x, const Vec<N,T>& y) { |
| return bit_pun<Vec<N,M<T>>>(to_vext(x) < to_vext(y)); |
| } |
| SINT Vec<N,M<T>> operator> (const Vec<N,T>& x, const Vec<N,T>& y) { |
| return bit_pun<Vec<N,M<T>>>(to_vext(x) > to_vext(y)); |
| } |
| |
| #else |
| |
| // Either SKNX_NO_SIMD is defined, or Clang/GCC vector extensions are not available. |
| // We'll implement things portably with N==1 scalar implementations and recursion onto them. |
| |
| // N == 1 scalar implementations. |
| SIT Vec<1,T> operator+(const Vec<1,T>& x, const Vec<1,T>& y) { return x.val + y.val; } |
| SIT Vec<1,T> operator-(const Vec<1,T>& x, const Vec<1,T>& y) { return x.val - y.val; } |
| SIT Vec<1,T> operator*(const Vec<1,T>& x, const Vec<1,T>& y) { return x.val * y.val; } |
| SIT Vec<1,T> operator/(const Vec<1,T>& x, const Vec<1,T>& y) { return x.val / y.val; } |
| |
| SIT Vec<1,T> operator^(const Vec<1,T>& x, const Vec<1,T>& y) { return x.val ^ y.val; } |
| SIT Vec<1,T> operator&(const Vec<1,T>& x, const Vec<1,T>& y) { return x.val & y.val; } |
| SIT Vec<1,T> operator|(const Vec<1,T>& x, const Vec<1,T>& y) { return x.val | y.val; } |
| |
| SIT Vec<1,T> operator!(const Vec<1,T>& x) { return !x.val; } |
| SIT Vec<1,T> operator-(const Vec<1,T>& x) { return -x.val; } |
| SIT Vec<1,T> operator~(const Vec<1,T>& x) { return ~x.val; } |
| |
| SIT Vec<1,T> operator<<(const Vec<1,T>& x, int k) { return x.val << k; } |
| SIT Vec<1,T> operator>>(const Vec<1,T>& x, int k) { return x.val >> k; } |
| |
| SIT Vec<1,M<T>> operator==(const Vec<1,T>& x, const Vec<1,T>& y) { |
| return x.val == y.val ? ~0 : 0; |
| } |
| SIT Vec<1,M<T>> operator!=(const Vec<1,T>& x, const Vec<1,T>& y) { |
| return x.val != y.val ? ~0 : 0; |
| } |
| SIT Vec<1,M<T>> operator<=(const Vec<1,T>& x, const Vec<1,T>& y) { |
| return x.val <= y.val ? ~0 : 0; |
| } |
| SIT Vec<1,M<T>> operator>=(const Vec<1,T>& x, const Vec<1,T>& y) { |
| return x.val >= y.val ? ~0 : 0; |
| } |
| SIT Vec<1,M<T>> operator< (const Vec<1,T>& x, const Vec<1,T>& y) { |
| return x.val < y.val ? ~0 : 0; |
| } |
| SIT Vec<1,M<T>> operator> (const Vec<1,T>& x, const Vec<1,T>& y) { |
| return x.val > y.val ? ~0 : 0; |
| } |
| |
| // Recurse on lo/hi down to N==1 scalar implementations. |
| SINT Vec<N,T> operator+(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return join(x.lo + y.lo, x.hi + y.hi); |
| } |
| SINT Vec<N,T> operator-(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return join(x.lo - y.lo, x.hi - y.hi); |
| } |
| SINT Vec<N,T> operator*(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return join(x.lo * y.lo, x.hi * y.hi); |
| } |
| SINT Vec<N,T> operator/(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return join(x.lo / y.lo, x.hi / y.hi); |
| } |
| |
| SINT Vec<N,T> operator^(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return join(x.lo ^ y.lo, x.hi ^ y.hi); |
| } |
| SINT Vec<N,T> operator&(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return join(x.lo & y.lo, x.hi & y.hi); |
| } |
| SINT Vec<N,T> operator|(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return join(x.lo | y.lo, x.hi | y.hi); |
| } |
| |
| SINT Vec<N,T> operator!(const Vec<N,T>& x) { return join(!x.lo, !x.hi); } |
| SINT Vec<N,T> operator-(const Vec<N,T>& x) { return join(-x.lo, -x.hi); } |
| SINT Vec<N,T> operator~(const Vec<N,T>& x) { return join(~x.lo, ~x.hi); } |
| |
| SINT Vec<N,T> operator<<(const Vec<N,T>& x, int k) { return join(x.lo << k, x.hi << k); } |
| SINT Vec<N,T> operator>>(const Vec<N,T>& x, int k) { return join(x.lo >> k, x.hi >> k); } |
| |
| SINT Vec<N,M<T>> operator==(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return join(x.lo == y.lo, x.hi == y.hi); |
| } |
| SINT Vec<N,M<T>> operator!=(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return join(x.lo != y.lo, x.hi != y.hi); |
| } |
| SINT Vec<N,M<T>> operator<=(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return join(x.lo <= y.lo, x.hi <= y.hi); |
| } |
| SINT Vec<N,M<T>> operator>=(const Vec<N,T>& x, const Vec<N,T>& y) { |
| return join(x.lo >= y.lo, x.hi >= y.hi); |
| } |
| SINT Vec<N,M<T>> operator< (const Vec<N,T>& x, const Vec<N,T>& y) { |
| return join(x.lo < y.lo, x.hi < y.hi); |
| } |
| SINT Vec<N,M<T>> operator> (const Vec<N,T>& x, const Vec<N,T>& y) { |
| return join(x.lo > y.lo, x.hi > y.hi); |
| } |
| #endif |
| |
| // Scalar/vector operations splat the scalar to a vector. |
| SINTU Vec<N,T> operator+ (U x, const Vec<N,T>& y) { return Vec<N,T>(x) + y; } |
| SINTU Vec<N,T> operator- (U x, const Vec<N,T>& y) { return Vec<N,T>(x) - y; } |
| SINTU Vec<N,T> operator* (U x, const Vec<N,T>& y) { return Vec<N,T>(x) * y; } |
| SINTU Vec<N,T> operator/ (U x, const Vec<N,T>& y) { return Vec<N,T>(x) / y; } |
| SINTU Vec<N,T> operator^ (U x, const Vec<N,T>& y) { return Vec<N,T>(x) ^ y; } |
| SINTU Vec<N,T> operator& (U x, const Vec<N,T>& y) { return Vec<N,T>(x) & y; } |
| SINTU Vec<N,T> operator| (U x, const Vec<N,T>& y) { return Vec<N,T>(x) | y; } |
| SINTU Vec<N,M<T>> operator==(U x, const Vec<N,T>& y) { return Vec<N,T>(x) == y; } |
| SINTU Vec<N,M<T>> operator!=(U x, const Vec<N,T>& y) { return Vec<N,T>(x) != y; } |
| SINTU Vec<N,M<T>> operator<=(U x, const Vec<N,T>& y) { return Vec<N,T>(x) <= y; } |
| SINTU Vec<N,M<T>> operator>=(U x, const Vec<N,T>& y) { return Vec<N,T>(x) >= y; } |
| SINTU Vec<N,M<T>> operator< (U x, const Vec<N,T>& y) { return Vec<N,T>(x) < y; } |
| SINTU Vec<N,M<T>> operator> (U x, const Vec<N,T>& y) { return Vec<N,T>(x) > y; } |
| |
| SINTU Vec<N,T> operator+ (const Vec<N,T>& x, U y) { return x + Vec<N,T>(y); } |
| SINTU Vec<N,T> operator- (const Vec<N,T>& x, U y) { return x - Vec<N,T>(y); } |
| SINTU Vec<N,T> operator* (const Vec<N,T>& x, U y) { return x * Vec<N,T>(y); } |
| SINTU Vec<N,T> operator/ (const Vec<N,T>& x, U y) { return x / Vec<N,T>(y); } |
| SINTU Vec<N,T> operator^ (const Vec<N,T>& x, U y) { return x ^ Vec<N,T>(y); } |
| SINTU Vec<N,T> operator& (const Vec<N,T>& x, U y) { return x & Vec<N,T>(y); } |
| SINTU Vec<N,T> operator| (const Vec<N,T>& x, U y) { return x | Vec<N,T>(y); } |
| SINTU Vec<N,M<T>> operator==(const Vec<N,T>& x, U y) { return x == Vec<N,T>(y); } |
| SINTU Vec<N,M<T>> operator!=(const Vec<N,T>& x, U y) { return x != Vec<N,T>(y); } |
| SINTU Vec<N,M<T>> operator<=(const Vec<N,T>& x, U y) { return x <= Vec<N,T>(y); } |
| SINTU Vec<N,M<T>> operator>=(const Vec<N,T>& x, U y) { return x >= Vec<N,T>(y); } |
| SINTU Vec<N,M<T>> operator< (const Vec<N,T>& x, U y) { return x < Vec<N,T>(y); } |
| SINTU Vec<N,M<T>> operator> (const Vec<N,T>& x, U y) { return x > Vec<N,T>(y); } |
| |
| SINT Vec<N,T>& operator+=(Vec<N,T>& x, const Vec<N,T>& y) { return (x = x + y); } |
| SINT Vec<N,T>& operator-=(Vec<N,T>& x, const Vec<N,T>& y) { return (x = x - y); } |
| SINT Vec<N,T>& operator*=(Vec<N,T>& x, const Vec<N,T>& y) { return (x = x * y); } |
| SINT Vec<N,T>& operator/=(Vec<N,T>& x, const Vec<N,T>& y) { return (x = x / y); } |
| SINT Vec<N,T>& operator^=(Vec<N,T>& x, const Vec<N,T>& y) { return (x = x ^ y); } |
| SINT Vec<N,T>& operator&=(Vec<N,T>& x, const Vec<N,T>& y) { return (x = x & y); } |
| SINT Vec<N,T>& operator|=(Vec<N,T>& x, const Vec<N,T>& y) { return (x = x | y); } |
| |
| SINTU Vec<N,T>& operator+=(Vec<N,T>& x, U y) { return (x = x + Vec<N,T>(y)); } |
| SINTU Vec<N,T>& operator-=(Vec<N,T>& x, U y) { return (x = x - Vec<N,T>(y)); } |
| SINTU Vec<N,T>& operator*=(Vec<N,T>& x, U y) { return (x = x * Vec<N,T>(y)); } |
| SINTU Vec<N,T>& operator/=(Vec<N,T>& x, U y) { return (x = x / Vec<N,T>(y)); } |
| SINTU Vec<N,T>& operator^=(Vec<N,T>& x, U y) { return (x = x ^ Vec<N,T>(y)); } |
| SINTU Vec<N,T>& operator&=(Vec<N,T>& x, U y) { return (x = x & Vec<N,T>(y)); } |
| SINTU Vec<N,T>& operator|=(Vec<N,T>& x, U y) { return (x = x | Vec<N,T>(y)); } |
| |
| SINT Vec<N,T>& operator<<=(Vec<N,T>& x, int bits) { return (x = x << bits); } |
| SINT Vec<N,T>& operator>>=(Vec<N,T>& x, int bits) { return (x = x >> bits); } |
| |
| // Some operations we want are not expressible with Clang/GCC vector extensions. |
| |
| // Clang can reason about naive_if_then_else() and optimize through it better |
| // than if_then_else(), so it's sometimes useful to call it directly when we |
| // think an entire expression should optimize away, e.g. min()/max(). |
| SINT Vec<N,T> naive_if_then_else(const Vec<N,M<T>>& cond, const Vec<N,T>& t, const Vec<N,T>& e) { |
| return bit_pun<Vec<N,T>>(( cond & bit_pun<Vec<N, M<T>>>(t)) | |
| (~cond & bit_pun<Vec<N, M<T>>>(e)) ); |
| } |
| |
| SIT Vec<1,T> if_then_else(const Vec<1,M<T>>& cond, const Vec<1,T>& t, const Vec<1,T>& e) { |
| // In practice this scalar implementation is unlikely to be used. See next if_then_else(). |
| return bit_pun<Vec<1,T>>(( cond & bit_pun<Vec<1, M<T>>>(t)) | |
| (~cond & bit_pun<Vec<1, M<T>>>(e)) ); |
| } |
| SINT Vec<N,T> if_then_else(const Vec<N,M<T>>& cond, const Vec<N,T>& t, const Vec<N,T>& e) { |
| // Specializations inline here so they can generalize what types the apply to. |
| // (This header is used in C++14 contexts, so we have to kind of fake constexpr if.) |
| #if defined(__AVX2__) |
| if /*constexpr*/ (N*sizeof(T) == 32) { |
| return unchecked_bit_pun<Vec<N,T>>(_mm256_blendv_epi8(unchecked_bit_pun<__m256i>(e), |
| unchecked_bit_pun<__m256i>(t), |
| unchecked_bit_pun<__m256i>(cond))); |
| } |
| #endif |
| #if defined(__SSE4_1__) |
| if /*constexpr*/ (N*sizeof(T) == 16) { |
| return unchecked_bit_pun<Vec<N,T>>(_mm_blendv_epi8(unchecked_bit_pun<__m128i>(e), |
| unchecked_bit_pun<__m128i>(t), |
| unchecked_bit_pun<__m128i>(cond))); |
| } |
| #endif |
| #if defined(__ARM_NEON) |
| if /*constexpr*/ (N*sizeof(T) == 16) { |
| return unchecked_bit_pun<Vec<N,T>>(vbslq_u8(unchecked_bit_pun<uint8x16_t>(cond), |
| unchecked_bit_pun<uint8x16_t>(t), |
| unchecked_bit_pun<uint8x16_t>(e))); |
| } |
| #endif |
| // Recurse for large vectors to try to hit the specializations above. |
| if /*constexpr*/ (N*sizeof(T) > 16) { |
| return join(if_then_else(cond.lo, t.lo, e.lo), |
| if_then_else(cond.hi, t.hi, e.hi)); |
| } |
| // This default can lead to better code than the recursing onto scalars. |
| return naive_if_then_else(cond, t, e); |
| } |
| |
| SIT bool any(const Vec<1,T>& x) { return x.val != 0; } |
| SINT bool any(const Vec<N,T>& x) { |
| #if defined(__wasm_simd128__) |
| if constexpr (N == 4 && sizeof(T) == 4) { |
| return wasm_i32x4_any_true(unchecked_bit_pun<VExt<4,int>>(x)); |
| } |
| #endif |
| return any(x.lo) |
| || any(x.hi); |
| } |
| |
| SIT bool all(const Vec<1,T>& x) { return x.val != 0; } |
| SINT bool all(const Vec<N,T>& x) { |
| #if defined(__AVX2__) |
| if /*constexpr*/ (N*sizeof(T) == 32) { |
| return _mm256_testc_si256(unchecked_bit_pun<__m256i>(x), |
| _mm256_set1_epi32(-1)); |
| } |
| #endif |
| #if defined(__SSE4_1__) |
| if /*constexpr*/ (N*sizeof(T) == 16) { |
| return _mm_testc_si128(unchecked_bit_pun<__m128i>(x), |
| _mm_set1_epi32(-1)); |
| } |
| #endif |
| #if defined(__wasm_simd128__) |
| if /*constexpr*/ (N == 4 && sizeof(T) == 4) { |
| return wasm_i32x4_all_true(unchecked_bit_pun<VExt<4,int>>(x)); |
| } |
| #endif |
| return all(x.lo) |
| && all(x.hi); |
| } |
| |
| // cast() Vec<N,S> to Vec<N,D>, as if applying a C-cast to each lane. |
| // TODO: implement with map()? |
| template <typename D, typename S> |
| SI Vec<1,D> cast(const Vec<1,S>& src) { return (D)src.val; } |
| |
| template <typename D, int N, typename S> |
| SI Vec<N,D> cast(const Vec<N,S>& src) { |
| #if !defined(SKNX_NO_SIMD) && defined(__clang__) |
| return to_vec(__builtin_convertvector(to_vext(src), VExt<N,D>)); |
| #else |
| return join(cast<D>(src.lo), cast<D>(src.hi)); |
| #endif |
| } |
| |
| // min/max match logic of std::min/std::max, which is important when NaN is involved. |
| SIT T min(const Vec<1,T>& x) { return x.val; } |
| SIT T max(const Vec<1,T>& x) { return x.val; } |
| SINT T min(const Vec<N,T>& x) { return std::min(min(x.lo), min(x.hi)); } |
| SINT T max(const Vec<N,T>& x) { return std::max(max(x.lo), max(x.hi)); } |
| |
| SINT Vec<N,T> min(const Vec<N,T>& x, const Vec<N,T>& y) { return naive_if_then_else(y < x, y, x); } |
| SINT Vec<N,T> max(const Vec<N,T>& x, const Vec<N,T>& y) { return naive_if_then_else(x < y, y, x); } |
| |
| SINTU Vec<N,T> min(const Vec<N,T>& x, U y) { return min(x, Vec<N,T>(y)); } |
| SINTU Vec<N,T> max(const Vec<N,T>& x, U y) { return max(x, Vec<N,T>(y)); } |
| SINTU Vec<N,T> min(U x, const Vec<N,T>& y) { return min(Vec<N,T>(x), y); } |
| SINTU Vec<N,T> max(U x, const Vec<N,T>& y) { return max(Vec<N,T>(x), y); } |
| |
| // pin matches the logic of SkTPin, which is important when NaN is involved. It always returns |
| // values in the range lo..hi, and if x is NaN, it returns lo. |
| SINT Vec<N,T> pin(const Vec<N,T>& x, const Vec<N,T>& lo, const Vec<N,T>& hi) { |
| return max(lo, min(x, hi)); |
| } |
| |
| // Shuffle values from a vector pretty arbitrarily: |
| // skvx::Vec<4,float> rgba = {R,G,B,A}; |
| // shuffle<2,1,0,3> (rgba) ~> {B,G,R,A} |
| // shuffle<2,1> (rgba) ~> {B,G} |
| // shuffle<2,1,2,1,2,1,2,1>(rgba) ~> {B,G,B,G,B,G,B,G} |
| // shuffle<3,3,3,3> (rgba) ~> {A,A,A,A} |
| // The only real restriction is that the output also be a legal N=power-of-two sknx::Vec. |
| template <int... Ix, int N, typename T> |
| SI Vec<sizeof...(Ix),T> shuffle(const Vec<N,T>& x) { |
| #if !defined(SKNX_NO_SIMD) && defined(__clang__) |
| // TODO: can we just always use { x[Ix]... }? |
| return to_vec<sizeof...(Ix),T>(__builtin_shufflevector(to_vext(x), to_vext(x), Ix...)); |
| #else |
| return { x[Ix]... }; |
| #endif |
| } |
| |
| // Call map(fn, x) for a vector with fn() applied to each lane of x, { fn(x[0]), fn(x[1]), ... }, |
| // or map(fn, x,y) for a vector of fn(x[i], y[i]), etc. |
| |
| template <typename Fn, typename... Args, size_t... I> |
| SI auto map(std::index_sequence<I...>, |
| Fn&& fn, const Args&... args) -> skvx::Vec<sizeof...(I), decltype(fn(args[0]...))> { |
| auto lane = [&](size_t i) |
| #if defined(__clang__) |
| // CFI, specifically -fsanitize=cfi-icall, seems to give a false positive here, |
| // with errors like "control flow integrity check for type 'float (float) |
| // noexcept' failed during indirect function call... note: sqrtf.cfi_jt defined |
| // here". But we can be quite sure fn is the right type: it's all inferred! |
| // So, stifle CFI in this function. |
| __attribute__((no_sanitize("cfi"))) |
| #endif |
| { return fn(args[i]...); }; |
| |
| return { lane(I)... }; |
| } |
| |
| template <typename Fn, int N, typename T, typename... Rest> |
| auto map(Fn&& fn, const Vec<N,T>& first, const Rest&... rest) { |
| // Derive an {0...N-1} index_sequence from the size of the first arg: N lanes in, N lanes out. |
| return map(std::make_index_sequence<N>{}, fn, first,rest...); |
| } |
| |
| SIN Vec<N,float> ceil(const Vec<N,float>& x) { return map( ceilf, x); } |
| SIN Vec<N,float> floor(const Vec<N,float>& x) { return map(floorf, x); } |
| SIN Vec<N,float> trunc(const Vec<N,float>& x) { return map(truncf, x); } |
| SIN Vec<N,float> round(const Vec<N,float>& x) { return map(roundf, x); } |
| SIN Vec<N,float> sqrt(const Vec<N,float>& x) { return map( sqrtf, x); } |
| SIN Vec<N,float> abs(const Vec<N,float>& x) { return map( fabsf, x); } |
| SIN Vec<N,float> fma(const Vec<N,float>& x, |
| const Vec<N,float>& y, |
| const Vec<N,float>& z) { |
| // I don't understand why Clang's codegen is terrible if we write map(fmaf, x,y,z) directly. |
| auto fn = [](float x, float y, float z) { return fmaf(x,y,z); }; |
| return map(fn, x,y,z); |
| } |
| |
| SI Vec<1,int> lrint(const Vec<1,float>& x) { |
| return (int)lrintf(x.val); |
| } |
| SIN Vec<N,int> lrint(const Vec<N,float>& x) { |
| #if defined(__AVX__) |
| if /*constexpr*/ (N == 8) { |
| return unchecked_bit_pun<Vec<N,int>>(_mm256_cvtps_epi32(unchecked_bit_pun<__m256>(x))); |
| } |
| #endif |
| #if defined(__SSE__) |
| if /*constexpr*/ (N == 4) { |
| return unchecked_bit_pun<Vec<N,int>>(_mm_cvtps_epi32(unchecked_bit_pun<__m128>(x))); |
| } |
| #endif |
| return join(lrint(x.lo), |
| lrint(x.hi)); |
| } |
| |
| SIN Vec<N,float> fract(const Vec<N,float>& x) { return x - floor(x); } |
| |
| // The default logic for to_half/from_half is borrowed from skcms, |
| // and assumes inputs are finite and treat/flush denorm half floats as/to zero. |
| // Key constants to watch for: |
| // - a float is 32-bit, 1-8-23 sign-exponent-mantissa, with 127 exponent bias; |
| // - a half is 16-bit, 1-5-10 sign-exponent-mantissa, with 15 exponent bias. |
| SIN Vec<N,uint16_t> to_half_finite_ftz(const Vec<N,float>& x) { |
| Vec<N,uint32_t> sem = bit_pun<Vec<N,uint32_t>>(x), |
| s = sem & 0x8000'0000, |
| em = sem ^ s, |
| is_denorm = em < 0x3880'0000; |
| return cast<uint16_t>(if_then_else(is_denorm, Vec<N,uint32_t>(0) |
| , (s>>16) + (em>>13) - ((127-15)<<10))); |
| } |
| SIN Vec<N,float> from_half_finite_ftz(const Vec<N,uint16_t>& x) { |
| Vec<N,uint32_t> wide = cast<uint32_t>(x), |
| s = wide & 0x8000, |
| em = wide ^ s; |
| auto is_denorm = bit_pun<Vec<N,int32_t>>(em < 0x0400); |
| return if_then_else(is_denorm, Vec<N,float>(0) |
| , bit_pun<Vec<N,float>>( (s<<16) + (em<<13) + ((127-15)<<23) )); |
| } |
| |
| // Like if_then_else(), these N=1 base cases won't actually be used unless explicitly called. |
| SI Vec<1,uint16_t> to_half(const Vec<1,float>& x) { return to_half_finite_ftz(x); } |
| SI Vec<1,float> from_half(const Vec<1,uint16_t>& x) { return from_half_finite_ftz(x); } |
| |
| SIN Vec<N,uint16_t> to_half(const Vec<N,float>& x) { |
| #if defined(__F16C__) |
| if /*constexpr*/ (N == 8) { |
| return unchecked_bit_pun<Vec<N,uint16_t>>(_mm256_cvtps_ph(unchecked_bit_pun<__m256>(x), |
| _MM_FROUND_CUR_DIRECTION)); |
| } |
| #endif |
| #if defined(__aarch64__) |
| if /*constexpr*/ (N == 4) { |
| return unchecked_bit_pun<Vec<N,uint16_t>>(vcvt_f16_f32(unchecked_bit_pun<float32x4_t>(x))); |
| |
| } |
| #endif |
| if /*constexpr*/ (N > 4) { |
| return join(to_half(x.lo), |
| to_half(x.hi)); |
| } |
| return to_half_finite_ftz(x); |
| } |
| |
| SIN Vec<N,float> from_half(const Vec<N,uint16_t>& x) { |
| #if defined(__F16C__) |
| if /*constexpr*/ (N == 8) { |
| return unchecked_bit_pun<Vec<N,float>>(_mm256_cvtph_ps(unchecked_bit_pun<__m128i>(x))); |
| } |
| #endif |
| #if defined(__aarch64__) |
| if /*constexpr*/ (N == 4) { |
| return unchecked_bit_pun<Vec<N,float>>(vcvt_f32_f16(unchecked_bit_pun<float16x4_t>(x))); |
| } |
| #endif |
| if /*constexpr*/ (N > 4) { |
| return join(from_half(x.lo), |
| from_half(x.hi)); |
| } |
| return from_half_finite_ftz(x); |
| } |
| |
| // div255(x) = (x + 127) / 255 is a bit-exact rounding divide-by-255, packing down to 8-bit. |
| SIN Vec<N,uint8_t> div255(const Vec<N,uint16_t>& x) { |
| return cast<uint8_t>( (x+127)/255 ); |
| } |
| |
| // approx_scale(x,y) approximates div255(cast<uint16_t>(x)*cast<uint16_t>(y)) within a bit, |
| // and is always perfect when x or y is 0 or 255. |
| SIN Vec<N,uint8_t> approx_scale(const Vec<N,uint8_t>& x, const Vec<N,uint8_t>& y) { |
| // All of (x*y+x)/256, (x*y+y)/256, and (x*y+255)/256 meet the criteria above. |
| // We happen to have historically picked (x*y+x)/256. |
| auto X = cast<uint16_t>(x), |
| Y = cast<uint16_t>(y); |
| return cast<uint8_t>( (X*Y+X)/256 ); |
| } |
| |
| // The ScaledDividerU32 takes a divisor > 1, and creates a function divide(numerator) that |
| // calculates a numerator / denominator. For this to be rounded properly, numerator should have |
| // half added in: |
| // divide(numerator + half) == floor(numerator/denominator + 1/2). |
| // |
| // This gives an answer within +/- 1 from the true value. |
| // |
| // Derivation of half: |
| // numerator/denominator + 1/2 = (numerator + half) / d |
| // numerator + denominator / 2 = numerator + half |
| // half = denominator / 2. |
| // |
| // Because half is divided by 2, that division must also be rounded. |
| // half == denominator / 2 = (denominator + 1) / 2. |
| // |
| // The divisorFactor is just a scaled value: |
| // divisorFactor = (1 / divisor) * 2 ^ 32. |
| // The maximum that can be divided and rounded is UINT_MAX - half. |
| class ScaledDividerU32 { |
| public: |
| explicit ScaledDividerU32(uint32_t divisor) |
| : fDivisorFactor{(uint32_t)(std::round((1.0 / divisor) * (1ull << 32)))} |
| , fHalf{(divisor + 1) >> 1} { |
| assert(divisor > 1); |
| } |
| |
| Vec<4, uint32_t> divide(const Vec<4, uint32_t>& numerator) const { |
| #if !defined(SKNX_NO_SIMD) && defined(__ARM_NEON) |
| uint64x2_t hi = vmull_n_u32(vget_high_u32(to_vext(numerator)), fDivisorFactor); |
| uint64x2_t lo = vmull_n_u32(vget_low_u32(to_vext(numerator)), fDivisorFactor); |
| |
| return to_vec<4, uint32_t>(vcombine_u32(vshrn_n_u64(lo,32), vshrn_n_u64(hi,32))); |
| #else |
| return cast<uint32_t>((cast<uint64_t>(numerator) * fDivisorFactor) >> 32); |
| #endif |
| } |
| |
| uint32_t half() const { return fHalf; } |
| |
| private: |
| const uint32_t fDivisorFactor; |
| const uint32_t fHalf; |
| }; |
| |
| #if !defined(SKNX_NO_SIMD) && defined(__ARM_NEON) |
| // With NEON we can do eight u8*u8 -> u16 in one instruction, vmull_u8 (read, mul-long). |
| SI Vec<8,uint16_t> mull(const Vec<8,uint8_t>& x, |
| const Vec<8,uint8_t>& y) { |
| return to_vec<8,uint16_t>(vmull_u8(to_vext(x), |
| to_vext(y))); |
| } |
| |
| SIN std::enable_if_t<(N < 8), Vec<N,uint16_t>> mull(const Vec<N,uint8_t>& x, |
| const Vec<N,uint8_t>& y) { |
| // N < 8 --> double up data until N == 8, returning the part we need. |
| return mull(join(x,x), |
| join(y,y)).lo; |
| } |
| |
| SIN std::enable_if_t<(N > 8), Vec<N,uint16_t>> mull(const Vec<N,uint8_t>& x, |
| const Vec<N,uint8_t>& y) { |
| // N > 8 --> usual join(lo,hi) strategy to recurse down to N == 8. |
| return join(mull(x.lo, y.lo), |
| mull(x.hi, y.hi)); |
| } |
| #else |
| // Nothing special when we don't have NEON... just cast up to 16-bit and multiply. |
| SIN Vec<N,uint16_t> mull(const Vec<N,uint8_t>& x, |
| const Vec<N,uint8_t>& y) { |
| return cast<uint16_t>(x) |
| * cast<uint16_t>(y); |
| } |
| #endif |
| |
| // Allow floating point contraction. e.g., allow a*x + y to be compiled to a single FMA even though |
| // it introduces LSB differences on platforms that don't have an FMA instruction. |
| #if defined(__clang__) |
| #pragma STDC FP_CONTRACT ON |
| #endif |
| |
| // Approximates the inverse cosine of x within 0.96 degrees using the rational polynomial: |
| // |
| // acos(x) ~= (bx^3 + ax) / (dx^4 + cx^2 + 1) + pi/2 |
| // |
| // See: https://stackoverflow.com/a/36387954 |
| // |
| // For a proof of max error, see the "SkVx_approx_acos" unit test. |
| // |
| // NOTE: This function deviates immediately from pi and 0 outside -1 and 1. (The derivatives are |
| // infinite at -1 and 1). So the input must still be clamped between -1 and 1. |
| #define SKVX_APPROX_ACOS_MAX_ERROR SkDegreesToRadians(.96f) |
| SIN Vec<N,float> approx_acos(Vec<N,float> x) { |
| constexpr static float a = -0.939115566365855f; |
| constexpr static float b = 0.9217841528914573f; |
| constexpr static float c = -1.2845906244690837f; |
| constexpr static float d = 0.295624144969963174f; |
| constexpr static float pi_over_2 = 1.5707963267948966f; |
| auto xx = x*x; |
| auto numer = b*xx + a; |
| auto denom = xx*(d*xx + c) + 1; |
| return x * (numer/denom) + pi_over_2; |
| } |
| |
| #if defined(__clang__) |
| #pragma STDC FP_CONTRACT DEFAULT |
| #endif |
| |
| // De-interleaving load of 4 vectors. |
| // |
| // WARNING: These are really only supported well on NEON. Consider restructuring your data before |
| // resorting to these methods. |
| SIT void strided_load4(const T* v, |
| skvx::Vec<1,T>& a, |
| skvx::Vec<1,T>& b, |
| skvx::Vec<1,T>& c, |
| skvx::Vec<1,T>& d) { |
| a.val = v[0]; |
| b.val = v[1]; |
| c.val = v[2]; |
| d.val = v[3]; |
| } |
| SINT void strided_load4(const T* v, |
| skvx::Vec<N,T>& a, |
| skvx::Vec<N,T>& b, |
| skvx::Vec<N,T>& c, |
| skvx::Vec<N,T>& d) { |
| strided_load4(v, a.lo, b.lo, c.lo, d.lo); |
| strided_load4(v + 4*(N/2), a.hi, b.hi, c.hi, d.hi); |
| } |
| #if !defined(SKNX_NO_SIMD) |
| #if defined(__ARM_NEON) |
| #define IMPL_LOAD4_TRANSPOSED(N, T, VLD) \ |
| SI void strided_load4(const T* v, \ |
| skvx::Vec<N,T>& a, \ |
| skvx::Vec<N,T>& b, \ |
| skvx::Vec<N,T>& c, \ |
| skvx::Vec<N,T>& d) { \ |
| auto mat = VLD(v); \ |
| a = skvx::bit_pun<skvx::Vec<N,T>>(mat.val[0]); \ |
| b = skvx::bit_pun<skvx::Vec<N,T>>(mat.val[1]); \ |
| c = skvx::bit_pun<skvx::Vec<N,T>>(mat.val[2]); \ |
| d = skvx::bit_pun<skvx::Vec<N,T>>(mat.val[3]); \ |
| } |
| IMPL_LOAD4_TRANSPOSED(2, uint32_t, vld4_u32); |
| IMPL_LOAD4_TRANSPOSED(4, uint16_t, vld4_u16); |
| IMPL_LOAD4_TRANSPOSED(8, uint8_t, vld4_u8); |
| IMPL_LOAD4_TRANSPOSED(2, int32_t, vld4_s32); |
| IMPL_LOAD4_TRANSPOSED(4, int16_t, vld4_s16); |
| IMPL_LOAD4_TRANSPOSED(8, int8_t, vld4_s8); |
| IMPL_LOAD4_TRANSPOSED(2, float, vld4_f32); |
| IMPL_LOAD4_TRANSPOSED(4, uint32_t, vld4q_u32); |
| IMPL_LOAD4_TRANSPOSED(8, uint16_t, vld4q_u16); |
| IMPL_LOAD4_TRANSPOSED(16, uint8_t, vld4q_u8); |
| IMPL_LOAD4_TRANSPOSED(4, int32_t, vld4q_s32); |
| IMPL_LOAD4_TRANSPOSED(8, int16_t, vld4q_s16); |
| IMPL_LOAD4_TRANSPOSED(16, int8_t, vld4q_s8); |
| IMPL_LOAD4_TRANSPOSED(4, float, vld4q_f32); |
| #undef IMPL_LOAD4_TRANSPOSED |
| #elif defined(__SSE__) |
| SI void strided_load4(const float* v, |
| Vec<4,float>& a, |
| Vec<4,float>& b, |
| Vec<4,float>& c, |
| Vec<4,float>& d) { |
| using skvx::bit_pun; |
| __m128 a_ = _mm_loadu_ps(v); |
| __m128 b_ = _mm_loadu_ps(v+4); |
| __m128 c_ = _mm_loadu_ps(v+8); |
| __m128 d_ = _mm_loadu_ps(v+12); |
| _MM_TRANSPOSE4_PS(a_, b_, c_, d_); |
| a = bit_pun<Vec<4,float>>(a_); |
| b = bit_pun<Vec<4,float>>(b_); |
| c = bit_pun<Vec<4,float>>(c_); |
| d = bit_pun<Vec<4,float>>(d_); |
| } |
| #endif |
| #endif |
| |
| // De-interleaving load of 2 vectors. |
| // |
| // WARNING: These are really only supported well on NEON. Consider restructuring your data before |
| // resorting to these methods. |
| SIT void strided_load2(const T* v, skvx::Vec<1,T>& a, skvx::Vec<1,T>& b) { |
| a.val = v[0]; |
| b.val = v[1]; |
| } |
| SINT void strided_load2(const T* v, skvx::Vec<N,T>& a, skvx::Vec<N,T>& b) { |
| strided_load2(v, a.lo, b.lo); |
| strided_load2(v + 2*(N/2), a.hi, b.hi); |
| } |
| #if !defined(SKNX_NO_SIMD) |
| #if defined(__ARM_NEON) |
| #define IMPL_LOAD2_TRANSPOSED(N, T, VLD) \ |
| SI void strided_load2(const T* v, skvx::Vec<N,T>& a, skvx::Vec<N,T>& b) { \ |
| auto mat = VLD(v); \ |
| a = skvx::bit_pun<skvx::Vec<N,T>>(mat.val[0]); \ |
| b = skvx::bit_pun<skvx::Vec<N,T>>(mat.val[1]); \ |
| } |
| IMPL_LOAD2_TRANSPOSED(2, uint32_t, vld2_u32); |
| IMPL_LOAD2_TRANSPOSED(4, uint16_t, vld2_u16); |
| IMPL_LOAD2_TRANSPOSED(8, uint8_t, vld2_u8); |
| IMPL_LOAD2_TRANSPOSED(2, int32_t, vld2_s32); |
| IMPL_LOAD2_TRANSPOSED(4, int16_t, vld2_s16); |
| IMPL_LOAD2_TRANSPOSED(8, int8_t, vld2_s8); |
| IMPL_LOAD2_TRANSPOSED(2, float, vld2_f32); |
| IMPL_LOAD2_TRANSPOSED(4, uint32_t, vld2q_u32); |
| IMPL_LOAD2_TRANSPOSED(8, uint16_t, vld2q_u16); |
| IMPL_LOAD2_TRANSPOSED(16, uint8_t, vld2q_u8); |
| IMPL_LOAD2_TRANSPOSED(4, int32_t, vld2q_s32); |
| IMPL_LOAD2_TRANSPOSED(8, int16_t, vld2q_s16); |
| IMPL_LOAD2_TRANSPOSED(16, int8_t, vld2q_s8); |
| IMPL_LOAD2_TRANSPOSED(4, float, vld2q_f32); |
| #undef IMPL_LOAD2_TRANSPOSED |
| #endif |
| #endif |
| |
| } // namespace skvx |
| |
| #undef SINTU |
| #undef SINT |
| #undef SIN |
| #undef SIT |
| #undef SI |
| #undef SKVX_ALWAYS_INLINE |
| |
| #endif//SKVX_DEFINED |