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#ifndef NETGEN_CORE_SIMD_HPP
#define NETGEN_CORE_SIMD_HPP
/**************************************************************************/
/* File: simd.hpp */
/* Author: Joachim Schoeberl, Matthias Hochsteger */
/* Date: 25. Mar. 16 */
/**************************************************************************/
#include <array>
#include <tuple>
#include "ngcore_api.hpp"
#include "simd_generic.hpp"
#ifndef __CUDA_ARCH__
#ifdef NETGEN_ARCH_AMD64
#ifndef __SSE__
#define __SSE__
#endif
#include "simd_sse.hpp"
#endif
#ifdef __AVX__
#include "simd_avx.hpp"
#endif
#ifdef __AVX512F__
#include "simd_avx512.hpp"
#endif
#ifdef __aarch64__
#include "simd_arm64.hpp"
#endif
#endif // __CUDA_ARCH__
namespace ngcore
{
#ifndef __CUDA_ARCH__
#ifdef NETGEN_ARCH_AMD64
/*
NETGEN_INLINE auto HSum (SIMD<double,2> v1, SIMD<double,2> v2, SIMD<double,2> v3, SIMD<double,2> v4)
{
SIMD<double,2> hsum1 = my_mm_hadd_pd (v1.Data(), v2.Data());
SIMD<double,2> hsum2 = my_mm_hadd_pd (v3.Data(), v4.Data());
return SIMD<double,4> (hsum1, hsum2);
}
*/
NETGEN_INLINE auto GetMaskFromBits( unsigned int i )
{
return SIMD<mask64>::GetMaskFromBits(i);
}
#endif
#endif // __CUDA_ARCH__
NETGEN_INLINE void SIMDTranspose (SIMD<double,4> a1, SIMD<double,4> a2, SIMD <double,4> a3, SIMD<double,4> a4,
SIMD<double,4> & b1, SIMD<double,4> & b2, SIMD<double,4> & b3, SIMD<double,4> & b4)
{
if constexpr (sizeof(a1.Lo()) == 16)
{
auto [h1,h2] = Unpack(a1,a2);
auto [h3,h4] = Unpack(a3,a4);
b1 = SIMD<double,4> (h1.Lo(), h3.Lo());
b2 = SIMD<double,4> (h2.Lo(), h4.Lo());
b3 = SIMD<double,4> (h1.Hi(), h3.Hi());
b4 = SIMD<double,4> (h2.Hi(), h4.Hi());
}
else
{
b1 = SIMD<double,4> (a1[0], a2[0], a3[0], a4[0]);
b2 = SIMD<double,4> (a1[1], a2[1], a3[1], a4[1]);
b3 = SIMD<double,4> (a1[2], a2[2], a3[2], a4[2]);
b4 = SIMD<double,4> (a1[3], a2[3], a3[3], a4[3]);
}
}
template<int N>
NETGEN_INLINE auto HSum (SIMD<double,N> s1, SIMD<double,N> s2)
{
return SIMD<double,2>(HSum(s1), HSum(s2));
}
template<int N>
NETGEN_INLINE auto HSum (SIMD<double,N> s1, SIMD<double,N> s2, SIMD<double,N> s3, SIMD<double,N> s4 )
{
// return SIMD<double,4>(HSum(s1), HSum(s2), HSum(s3), HSum(s4));
return SIMD<double,4>(HSum(s1, s2), HSum(s3,s4));
}
template <typename T, size_t S> class MakeSimdCl;
template <typename T, size_t S>
auto MakeSimd (std::array<T,S> aa) { return MakeSimdCl(aa).Get(); }
template <typename T, size_t S>
class MakeSimdCl
{
std::array<T,S> a;
public:
MakeSimdCl (std::array<T,S> aa) : a(aa) { ; }
auto Get() const
{
SIMD<T,S> sa( [this] (auto i) { return (this->a)[i]; });
return sa;
}
};
template <typename Tfirst, size_t S, typename ...Trest>
class MakeSimdCl<std::tuple<Tfirst,Trest...>,S>
{
std::array<std::tuple<Tfirst,Trest...>,S> a;
public:
MakeSimdCl (std::array<std::tuple<Tfirst,Trest...>,S> aa) : a(aa) { ; }
auto Get() const
{
std::array<Tfirst,S> a0;
for (int i = 0; i < S; i++)
a0[i] = std::get<0> (a[i]);
if constexpr (std::tuple_size<std::tuple<Tfirst,Trest...>>::value == 1)
{
return std::tuple(MakeSimd(a0));
}
else
{
std::array<std::tuple<Trest...>,S> arest;
for (int i = 0; i < S; i++)
arest[i] = skip_first(a[i]);
return std::tuple_cat ( std::tuple (MakeSimd(a0)), MakeSimd(arest) );
}
}
template <typename... Ts>
static auto skip_first(const std::tuple<Ts...>& t) {
return std::apply([](auto first, auto... rest) {
return std::make_tuple(rest...);
}, t);
}
};
}
#include "simd_math.hpp"
#endif // NETGEN_CORE_SIMD_HPP
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