blob: 99e51c57718788dee3a861caf89aca906ff639a5 [file] [log] [blame]
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#ifndef EIGEN_CXX11_TENSOR_TENSOR_UINT128_H
#define EIGEN_CXX11_TENSOR_TENSOR_UINT128_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
template <uint64_t n>
struct static_val {
static const uint64_t value = n;
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE operator uint64_t() const { return n; }
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE static_val() {}
template <typename T>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE static_val(const T& v) {
EIGEN_UNUSED_VARIABLE(v);
eigen_assert(v == n);
}
};
template <typename HIGH = uint64_t, typename LOW = uint64_t>
struct TensorUInt128 {
HIGH high;
LOW low;
template <typename OTHER_HIGH, typename OTHER_LOW>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE TensorUInt128(const TensorUInt128<OTHER_HIGH, OTHER_LOW>& other)
: high(other.high), low(other.low) {
EIGEN_STATIC_ASSERT(sizeof(OTHER_HIGH) <= sizeof(HIGH), YOU_MADE_A_PROGRAMMING_MISTAKE);
EIGEN_STATIC_ASSERT(sizeof(OTHER_LOW) <= sizeof(LOW), YOU_MADE_A_PROGRAMMING_MISTAKE);
}
template <typename OTHER_HIGH, typename OTHER_LOW>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE TensorUInt128& operator=(const TensorUInt128<OTHER_HIGH, OTHER_LOW>& other) {
EIGEN_STATIC_ASSERT(sizeof(OTHER_HIGH) <= sizeof(HIGH), YOU_MADE_A_PROGRAMMING_MISTAKE);
EIGEN_STATIC_ASSERT(sizeof(OTHER_LOW) <= sizeof(LOW), YOU_MADE_A_PROGRAMMING_MISTAKE);
high = other.high;
low = other.low;
return *this;
}
template <typename T>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE explicit TensorUInt128(const T& x) : high(0), low(x) {
eigen_assert(
(static_cast<std::conditional_t<sizeof(T) == 8, uint64_t, uint32_t>>(x) <= NumTraits<uint64_t>::highest()));
eigen_assert(x >= 0);
}
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE TensorUInt128(HIGH y, LOW x) : high(y), low(x) {}
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE operator LOW() const { return low; }
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE LOW lower() const { return low; }
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE HIGH upper() const { return high; }
};
template <typename HL, typename LL, typename HR, typename LR>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool operator==(const TensorUInt128<HL, LL>& lhs,
const TensorUInt128<HR, LR>& rhs) {
return (lhs.high == rhs.high) && (lhs.low == rhs.low);
}
template <typename HL, typename LL, typename HR, typename LR>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool operator!=(const TensorUInt128<HL, LL>& lhs,
const TensorUInt128<HR, LR>& rhs) {
return (lhs.high != rhs.high) || (lhs.low != rhs.low);
}
template <typename HL, typename LL, typename HR, typename LR>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool operator>=(const TensorUInt128<HL, LL>& lhs,
const TensorUInt128<HR, LR>& rhs) {
if (lhs.high != rhs.high) {
return lhs.high > rhs.high;
}
return lhs.low >= rhs.low;
}
template <typename HL, typename LL, typename HR, typename LR>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool operator<(const TensorUInt128<HL, LL>& lhs,
const TensorUInt128<HR, LR>& rhs) {
if (lhs.high != rhs.high) {
return lhs.high < rhs.high;
}
return lhs.low < rhs.low;
}
template <typename HL, typename LL, typename HR, typename LR>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE TensorUInt128<uint64_t, uint64_t> operator+(const TensorUInt128<HL, LL>& lhs,
const TensorUInt128<HR, LR>& rhs) {
TensorUInt128<uint64_t, uint64_t> result(lhs.high + rhs.high, lhs.low + rhs.low);
if (result.low < rhs.low) {
result.high += 1;
}
return result;
}
template <typename HL, typename LL, typename HR, typename LR>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE TensorUInt128<uint64_t, uint64_t> operator-(const TensorUInt128<HL, LL>& lhs,
const TensorUInt128<HR, LR>& rhs) {
TensorUInt128<uint64_t, uint64_t> result(lhs.high - rhs.high, lhs.low - rhs.low);
if (result.low > lhs.low) {
result.high -= 1;
}
return result;
}
template <typename HL, typename LL, typename HR, typename LR>
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorUInt128<uint64_t, uint64_t> operator*(
const TensorUInt128<HL, LL>& lhs, const TensorUInt128<HR, LR>& rhs) {
// Split each 128-bit integer into 4 32-bit integers, and then do the
// multiplications by hand as follow:
// lhs a b c d
// rhs e f g h
// -----------
// ah bh ch dh
// bg cg dg
// cf df
// de
// The result is stored in 2 64bit integers, high and low.
const uint64_t LOW = 0x00000000FFFFFFFFLL;
const uint64_t HIGH = 0xFFFFFFFF00000000LL;
uint64_t d = lhs.low & LOW;
uint64_t c = (lhs.low & HIGH) >> 32LL;
uint64_t b = lhs.high & LOW;
uint64_t a = (lhs.high & HIGH) >> 32LL;
uint64_t h = rhs.low & LOW;
uint64_t g = (rhs.low & HIGH) >> 32LL;
uint64_t f = rhs.high & LOW;
uint64_t e = (rhs.high & HIGH) >> 32LL;
// Compute the low 32 bits of low
uint64_t acc = d * h;
uint64_t low = acc & LOW;
// Compute the high 32 bits of low. Add a carry every time we wrap around
acc >>= 32LL;
uint64_t carry = 0;
uint64_t acc2 = acc + c * h;
if (acc2 < acc) {
carry++;
}
acc = acc2 + d * g;
if (acc < acc2) {
carry++;
}
low |= (acc << 32LL);
// Carry forward the high bits of acc to initiate the computation of the
// low 32 bits of high
acc2 = (acc >> 32LL) | (carry << 32LL);
carry = 0;
acc = acc2 + b * h;
if (acc < acc2) {
carry++;
}
acc2 = acc + c * g;
if (acc2 < acc) {
carry++;
}
acc = acc2 + d * f;
if (acc < acc2) {
carry++;
}
uint64_t high = acc & LOW;
// Start to compute the high 32 bits of high.
acc2 = (acc >> 32LL) | (carry << 32LL);
acc = acc2 + a * h;
acc2 = acc + b * g;
acc = acc2 + c * f;
acc2 = acc + d * e;
high |= (acc2 << 32LL);
return TensorUInt128<uint64_t, uint64_t>(high, low);
}
template <typename HL, typename LL, typename HR, typename LR>
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorUInt128<uint64_t, uint64_t> operator/(
const TensorUInt128<HL, LL>& lhs, const TensorUInt128<HR, LR>& rhs) {
if (rhs == TensorUInt128<static_val<0>, static_val<1>>(1)) {
return TensorUInt128<uint64_t, uint64_t>(lhs.high, lhs.low);
} else if (lhs < rhs) {
return TensorUInt128<uint64_t, uint64_t>(0);
} else {
// calculate the biggest power of 2 times rhs that's less than or equal to lhs
TensorUInt128<uint64_t, uint64_t> power2(1);
TensorUInt128<uint64_t, uint64_t> d(rhs);
TensorUInt128<uint64_t, uint64_t> tmp(lhs - d);
while (lhs >= d) {
tmp = tmp - d;
d = d + d;
power2 = power2 + power2;
}
tmp = TensorUInt128<uint64_t, uint64_t>(lhs.high, lhs.low);
TensorUInt128<uint64_t, uint64_t> result(0);
while (power2 != TensorUInt128<static_val<0>, static_val<0>>(0)) {
if (tmp >= d) {
tmp = tmp - d;
result = result + power2;
}
// Shift right
power2 = TensorUInt128<uint64_t, uint64_t>(power2.high >> 1, (power2.low >> 1) | (power2.high << 63));
d = TensorUInt128<uint64_t, uint64_t>(d.high >> 1, (d.low >> 1) | (d.high << 63));
}
return result;
}
}
} // namespace internal
} // namespace Eigen
#endif // EIGEN_CXX11_TENSOR_TENSOR_UINT128_H