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functional.h
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/***************************************************************************************************
* Copyright (c) 2017-2021, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without modification, are permitted
* provided that the following conditions are met:
* * Redistributions of source code must retain the above copyright notice, this list of
* conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright notice, this list of
* conditions and the following disclaimer in the documentation and/or other materials
* provided with the distribution.
* * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used
* to endorse or promote products derived from this software without specific prior written
* permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
* FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
* OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
* STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*
**************************************************************************************************/
/*! \file
\brief Define basic numeric operators with specializations for Array<T, N>. SIMD-ize where possible.
This is inspired by the Standard Library's <functional> header.
*/
#pragma once
#include "cutlass/cutlass.h"
#include "cutlass/numeric_types.h"
#include "cutlass/complex.h"
#include "cutlass/quaternion.h"
#include "cutlass/array.h"
#include "cutlass/half.h"
namespace cutlass {
/////////////////////////////////////////////////////////////////////////////////////////////////
template <typename T>
struct plus {
CUTLASS_HOST_DEVICE
T operator()(T lhs, T const &rhs) const {
lhs += rhs;
return lhs;
}
};
template <typename T>
struct minus {
CUTLASS_HOST_DEVICE
T operator()(T lhs, T const &rhs) const {
lhs -= rhs;
return lhs;
}
};
template <typename T>
struct multiplies {
CUTLASS_HOST_DEVICE
T operator()(T lhs, T const &rhs) const {
lhs *= rhs;
return lhs;
}
};
template <typename T>
struct multiplies<Quaternion<T>> {
CUTLASS_HOST_DEVICE
Quaternion<T> operator()(Quaternion<T> lhs, Quaternion<T> const &rhs) const {
lhs = lhs * rhs;
return lhs;
}
};
/// Squares with optional conversion
template <typename T, typename Output = T>
struct square {
CUTLASS_HOST_DEVICE
Output operator()(T lhs) const {
multiplies<Output> mul_op;
Output y = Output(lhs);
return mul_op(y, y);
}
};
/// Returns the magnitude squared of an element.
template <typename T, typename Output = T>
struct magnitude_squared {
CUTLASS_HOST_DEVICE
Output operator()(T lhs) const {
multiplies<Output> mul_op;
Output y = Output(lhs);
return mul_op(y, y);
}
};
/// Squares with optional conversion
template <typename T, typename Output>
struct magnitude_squared<complex<T>, Output> {
CUTLASS_HOST_DEVICE
Output operator()(complex<T> lhs) const {
multiplies<Output> mul_op;
Output y_r = Output(lhs.real());
Output y_i = Output(lhs.imag());
return mul_op(y_r, y_r) + mul_op(y_i, y_i);
}
};
/// Squares with optional conversion
template <typename T, typename Output>
struct magnitude_squared<Quaternion<T>, Output> {
CUTLASS_HOST_DEVICE
Output operator()(Quaternion<T> lhs) const {
multiplies<Output> mul_op;
Output y_w = Output(lhs.w());
Output y_x = Output(lhs.x());
Output y_y = Output(lhs.y());
Output y_z = Output(lhs.z());
return mul_op(y_w, y_w) + mul_op(y_x, y_x) + mul_op(y_y, y_y) + \
mul_op(y_z, y_z);
}
};
/// Computes the square of a difference with optional conversion
template <typename T, typename Output = T>
struct square_difference {
CUTLASS_HOST_DEVICE
Output operator()(T lhs, T rhs) const {
multiplies<Output> mul_op;
Output y = Output(lhs) - Output(rhs);
return mul_op(y, y);
}
};
/// Computes the square of a difference with optional conversion
template <typename T, typename Output = T>
struct magnitude_squared_difference {
CUTLASS_HOST_DEVICE
Output operator()(T lhs, T rhs) const {
multiplies<Output> mul_op;
Output y = Output(lhs) - Output(rhs);
return mul_op(y, y);
}
};
/// Computes the square of a difference with optional conversion
template <typename T, typename Output>
struct magnitude_squared_difference<complex<T>, Output> {
CUTLASS_HOST_DEVICE
Output operator()(complex<T> lhs, complex<T> rhs) const {
multiplies<Output> mul_op;
Output y_r = Output(lhs.real()) - Output(rhs.real());
Output y_i = Output(lhs.imag()) - Output(rhs.imag());
return mul_op(y_r, y_r) + mul_op(y_i, y_i);
}
};
template <typename T>
struct divides {
CUTLASS_HOST_DEVICE
T operator()(T lhs, T const &rhs) const {
lhs /= rhs;
return lhs;
}
};
template <typename T>
struct negate {
CUTLASS_HOST_DEVICE
T operator()(T lhs) const {
return -lhs;
}
};
/// Greater equal
template <typename T>
struct greater_equal {
CUTLASS_HOST_DEVICE
bool operator()(T const &lhs, T const &rhs) const {
return (lhs >= rhs);
}
};
/// Greater
template <typename T>
struct greater {
CUTLASS_HOST_DEVICE
bool operator()(T const &lhs, T const &rhs) const {
return (lhs > rhs);
}
};
/// Less equal
template <typename T>
struct less_equal {
CUTLASS_HOST_DEVICE
bool operator()(T const &lhs, T const &rhs) const {
return (lhs <= rhs);
}
};
/// Less
template <typename T>
struct less {
CUTLASS_HOST_DEVICE
bool operator()(T const &lhs, T const &rhs) const {
return (lhs < rhs);
}
};
/// Fused multiply-add
template <typename A, typename B = A, typename C = A>
struct multiply_add {
CUTLASS_HOST_DEVICE
C operator()(A const &a, B const &b, C const &c) const {
return C(a) * C(b) + c;
}
};
/// Fused multiply-add
template <typename T>
struct and_add {
CUTLASS_HOST_DEVICE
T operator()(T const &a, T const &b, T const &c) const {
return ((a & b) + c);
}
};
/// Fused multiply-add
template <typename T>
struct xor_add {
CUTLASS_HOST_DEVICE
T operator()(T const &a, T const &b, T const &c) const {
return ((a ^ b) + c);
}
};
template <typename T>
struct conjugate {
CUTLASS_HOST_DEVICE
T operator()(T const &a) const {
return a;
}
};
/////////////////////////////////////////////////////////////////////////////////////////////////
template <typename T>
struct logical_and {
CUTLASS_HOST_DEVICE
T operator()(T const &a, T const &b) const {
return ((a && b) ? T(1) : T());
}
};
template <typename T>
struct logical_or {
CUTLASS_HOST_DEVICE
T operator()(T const &a, T const &b) const {
return ((a || b) ? T(1) : T());
}
};
template <typename T>
struct logical_not {
CUTLASS_HOST_DEVICE
T operator()(T const &a) const {
return T(!(a));
}
};
/////////////////////////////////////////////////////////////////////////////////////////////////
template <typename T>
struct bit_and {
CUTLASS_HOST_DEVICE
T operator()(T const &a, T const &b) const {
return a & b;
}
};
template <typename T>
struct bit_or {
CUTLASS_HOST_DEVICE
T operator()(T const &a, T const &b) const {
return a | b;
}
};
template <typename T>
struct bit_not {
CUTLASS_HOST_DEVICE
T operator()(T const &a) const {
return ~a;
}
};
template <typename T>
struct bit_xor {
CUTLASS_HOST_DEVICE
T operator()(T const &a, T const &b) const {
return a ^ b;
}
};
/////////////////////////////////////////////////////////////////////////////////////////////////
// Partial specializations for Arrays
template <int N>
struct bit_and<Array<uint1b_t, N>> {
CUTLASS_HOST_DEVICE
Array<uint1b_t, N> operator()(Array<uint1b_t, N> const &a, Array<uint1b_t, N> const &b) const {
using ArrayType = Array<uint1b_t, N>;
using Storage = typename ArrayType::Storage;
ArrayType result;
Storage *result_data = result.raw_data();
Storage const *a_data = a.raw_data();
Storage const *b_data = b.raw_data();
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < ArrayType::kStorageElements; ++i) {
result_data[i] = (a_data[i] & b_data[i]);
}
return result;
}
};
// Partial specializations for Arrays
template <int N>
struct bit_or<Array<uint1b_t, N>> {
CUTLASS_HOST_DEVICE
Array<uint1b_t, N> operator()(Array<uint1b_t, N> const &a, Array<uint1b_t, N> const &b) const {
using ArrayType = Array<uint1b_t, N>;
using Storage = typename ArrayType::Storage;
ArrayType result;
Storage *result_data = result.raw_data();
Storage const *a_data = a.raw_data();
Storage const *b_data = b.raw_data();
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < ArrayType::kStorageElements; ++i) {
result_data[i] = (a_data[i] | b_data[i]);
}
return result;
}
};
// Partial specializations for Arrays
template <int N>
struct bit_not<Array<uint1b_t, N>> {
CUTLASS_HOST_DEVICE
Array<uint1b_t, N> operator()(Array<uint1b_t, N> const &a) const {
using ArrayType = Array<uint1b_t, N>;
using Storage = typename ArrayType::Storage;
ArrayType result;
Storage *result_data = result.raw_data();
Storage const *a_data = a.raw_data();
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < ArrayType::kStorageElements; ++i) {
result_data[i] = (~a_data[i]);
}
return result;
}
};
// Partial specializations for Arrays
template <int N>
struct bit_xor<Array<uint1b_t, N>> {
CUTLASS_HOST_DEVICE
Array<uint1b_t, N> operator()(Array<uint1b_t, N> const &a, Array<uint1b_t, N> const &b) const {
using ArrayType = Array<uint1b_t, N>;
using Storage = typename ArrayType::Storage;
ArrayType result;
Storage *result_data = result.raw_data();
Storage const *a_data = a.raw_data();
Storage const *b_data = b.raw_data();
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < ArrayType::kStorageElements; ++i) {
result_data[i] = (a_data[i] ^ b_data[i]);
}
return result;
}
};
/////////////////////////////////////////////////////////////////////////////////////////////////
template <typename T>
struct conjugate<complex<T>> {
CUTLASS_HOST_DEVICE
complex<T> operator()(complex<T> const &a) const {
return conj(a);
}
};
template <typename T, int N>
struct conjugate<Array<T, N> > {
CUTLASS_HOST_DEVICE
Array<T, N> operator()(Array<T, N> const &a) const {
conjugate<T> conj_op;
Array<T, N> ca;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
ca[i] = conj_op(a[i]);
}
return ca;
}
};
/////////////////////////////////////////////////////////////////////////////////////////////////
//
// Partial specialization for complex<T> to target four scalar fused multiply-adds.
//
/////////////////////////////////////////////////////////////////////////////////////////////////
/// Fused multiply-add
template <typename T>
struct multiply_add<complex<T>, complex<T>, complex<T>> {
CUTLASS_HOST_DEVICE
complex<T> operator()(
complex<T> const &a,
complex<T> const &b,
complex<T> const &c) const {
T real = c.real();
T imag = c.imag();
real += a.real() * b.real();
real += -a.imag() * b.imag();
imag += a.real() * b.imag();
imag += a.imag () * b.real();
return complex<T>{
real,
imag
};
}
};
/// Fused multiply-add
template <typename T>
struct multiply_add<complex<T>, T, complex<T>> {
CUTLASS_HOST_DEVICE
complex<T> operator()(
complex<T> const &a,
T const &b,
complex<T> const &c) const {
T real = c.real();
T imag = c.imag();
real += a.real() * b;
imag += a.imag () * b;
return complex<T>{
real,
imag
};
}
};
/// Fused multiply-add
template <typename T>
struct multiply_add<T, complex<T>, complex<T>> {
CUTLASS_HOST_DEVICE
complex<T> operator()(
T const &a,
complex<T> const &b,
complex<T> const &c) const {
T real = c.real();
T imag = c.imag();
real += a * b.real();
imag += a * b.imag();
return complex<T>{
real,
imag
};
}
};
/////////////////////////////////////////////////////////////////////////////////////////////////
//
// Partial specializations for Array<T, N>
//
/////////////////////////////////////////////////////////////////////////////////////////////////
template <typename T, int N>
struct plus<Array<T, N>> {
CUTLASS_HOST_DEVICE
Array<T, N> operator()(Array<T, N> const &lhs, Array<T, N> const &rhs) const {
Array<T, N> result;
plus<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(lhs[i], rhs[i]);
}
return result;
}
CUTLASS_HOST_DEVICE
Array<T, N> operator()(Array<T, N> const &lhs, T const &scalar) const {
Array<T, N> result;
plus<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(lhs[i], scalar);
}
return result;
}
CUTLASS_HOST_DEVICE
Array<T, N> operator()( T const &scalar, Array<T, N> const &rhs) const {
Array<T, N> result;
plus<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(scalar, rhs[i]);
}
return result;
}
};
template <typename T>
struct maximum {
CUTLASS_HOST_DEVICE
T operator()(T const &lhs, T const &rhs) const {
return (lhs < rhs ? rhs : lhs);
}
};
template <>
struct maximum<float> {
CUTLASS_HOST_DEVICE
float operator()(float const &lhs, float const &rhs) const {
return fmaxf(lhs, rhs);
}
};
template <typename T, int N>
struct maximum<Array<T, N>> {
CUTLASS_HOST_DEVICE
Array<T, N> operator()(Array<T, N> const &lhs, Array<T, N> const &rhs) const {
Array<T, N> result;
maximum<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(lhs[i], rhs[i]);
}
return result;
}
CUTLASS_HOST_DEVICE
Array<T, N> operator()(Array<T, N> const &lhs, T const &scalar) const {
Array<T, N> result;
maximum<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(lhs[i], scalar);
}
return result;
}
CUTLASS_HOST_DEVICE
Array<T, N> operator()( T const &scalar, Array<T, N> const &rhs) const {
Array<T, N> result;
maximum<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(scalar, rhs[i]);
}
return result;
}
};
template <typename T>
struct minimum {
CUTLASS_HOST_DEVICE
T operator()(T const &lhs, T const &rhs) const {
return (rhs < lhs ? rhs : lhs);
}
};
template <>
struct minimum<float> {
CUTLASS_HOST_DEVICE
float operator()(float const &lhs, float const &rhs) const {
return fminf(lhs, rhs);
}
};
template <typename T, int N>
struct minimum<Array<T, N>> {
CUTLASS_HOST_DEVICE
static T scalar_op(T const &lhs, T const &rhs) {
return (rhs < lhs ? rhs : lhs);
}
CUTLASS_HOST_DEVICE
Array<T, N> operator()(Array<T, N> const &lhs, Array<T, N> const &rhs) const {
Array<T, N> result;
minimum<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(lhs[i], rhs[i]);
}
return result;
}
CUTLASS_HOST_DEVICE
Array<T, N> operator()(Array<T, N> const &lhs, T const &scalar) const {
Array<T, N> result;
minimum<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(lhs[i], scalar);
}
return result;
}
CUTLASS_HOST_DEVICE
Array<T, N> operator()( T const &scalar, Array<T, N> const &rhs) const {
Array<T, N> result;
minimum<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(scalar, rhs[i]);
}
return result;
}
};
template <typename T, int N>
struct minus<Array<T, N>> {
CUTLASS_HOST_DEVICE
Array<T, N> operator()(Array<T, N> const &lhs, Array<T, N> const &rhs) const {
Array<T, N> result;
minus<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(lhs[i], rhs[i]);
}
return result;
}
CUTLASS_HOST_DEVICE
Array<T, N> operator()(Array<T, N> const &lhs, T const &scalar) const {
Array<T, N> result;
minus<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(lhs[i], scalar);
}
return result;
}
CUTLASS_HOST_DEVICE
Array<T, N> operator()( T const &scalar, Array<T, N> const &rhs) const {
Array<T, N> result;
minus<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(scalar, rhs[i]);
}
return result;
}
};
template <typename T, int N>
struct multiplies<Array<T, N>> {
CUTLASS_HOST_DEVICE
Array<T, N> operator()(Array<T, N> const &lhs, Array<T, N> const &rhs) const {
Array<T, N> result;
multiplies<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(lhs[i], rhs[i]);
}
return result;
}
CUTLASS_HOST_DEVICE
Array<T, N> operator()(Array<T, N> const &lhs, T const &scalar) const {
Array<T, N> result;
multiplies<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(lhs[i], scalar);
}
return result;
}
CUTLASS_HOST_DEVICE
Array<T, N> operator()( T const &scalar, Array<T, N> const &rhs) const {
Array<T, N> result;
multiplies<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(scalar, rhs[i]);
}
return result;
}
};
template <typename T, int N>
struct divides<Array<T, N>> {
CUTLASS_HOST_DEVICE
Array<T, N> operator()(Array<T, N> const &lhs, Array<T, N> const &rhs) const {
Array<T, N> result;
divides<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(lhs[i], rhs[i]);
}
return result;
}
CUTLASS_HOST_DEVICE
Array<T, N> operator()(Array<T, N> const &lhs, T const &scalar) const {
Array<T, N> result;
divides<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(lhs[i], scalar);
}
return result;
}
CUTLASS_HOST_DEVICE
Array<T, N> operator()( T const &scalar, Array<T, N> const &rhs) const {
Array<T, N> result;
divides<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(scalar, rhs[i]);
}
return result;
}
};
template <typename T, int N>
struct negate<Array<T, N>> {
CUTLASS_HOST_DEVICE
Array<T, N> operator()(Array<T, N> const &lhs) const {
Array<T, N> result;
negate<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(lhs[i]);
}
return result;
}
};
/// Fused multiply-add
template <typename T, int N>
struct multiply_add<Array<T, N>, Array<T, N>, Array<T, N>> {
CUTLASS_HOST_DEVICE
Array<T, N> operator()(Array<T, N> const &a, Array<T, N> const &b, Array<T, N> const &c) const {
Array<T, N> result;
multiply_add<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(a[i], b[i], c[i]);
}
return result;
}
CUTLASS_HOST_DEVICE
Array<T, N> operator()(Array<T, N> const &a, T const &scalar, Array<T, N> const &c) const {
Array<T, N> result;
multiply_add<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(a[i], scalar, c[i]);
}
return result;
}
CUTLASS_HOST_DEVICE
Array<T, N> operator()(T const &scalar, Array<T, N> const &b, Array<T, N> const &c) const {
Array<T, N> result;
multiply_add<T> scalar_op;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = scalar_op(scalar, b[i], c[i]);
}
return result;
}
};
/////////////////////////////////////////////////////////////////////////////////////////////////
//
// Partial specializations for Array<half_t, N> targeting SIMD instructions in device code.
//
/////////////////////////////////////////////////////////////////////////////////////////////////
template <int N>
struct plus<Array<half_t, N>> {
CUTLASS_HOST_DEVICE
Array<half_t, N> operator()(Array<half_t, N> const & lhs, Array<half_t, N> const &rhs) const {
Array<half_t, N> result;
#if defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 530)
__half2 *result_ptr = reinterpret_cast<__half2 *>(&result);
__half2 const *lhs_ptr = reinterpret_cast<__half2 const *>(&lhs);
__half2 const *rhs_ptr = reinterpret_cast<__half2 const *>(&rhs);
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N / 2; ++i) {
result_ptr[i] = __hadd2(lhs_ptr[i], rhs_ptr[i]);
}
if (N % 2) {
__half const *a_residual_ptr = reinterpret_cast<__half const *>(&lhs);
__half const *b_residual_ptr = reinterpret_cast<__half const *>(&rhs);
__half d_residual = __hadd(a_residual_ptr[N - 1], b_residual_ptr[N - 1]);
result[N - 1] = reinterpret_cast<half_t const &>(d_residual);
}
#else
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = lhs[i] + rhs[i];
}
#endif
return result;
}
CUTLASS_HOST_DEVICE
Array<half_t, N> operator()(half_t const & lhs, Array<half_t, N> const &rhs) const {
Array<half_t, N> result;
#if defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 530)
__half2 *result_ptr = reinterpret_cast<__half2 *>(&result);
__half2 lhs_pair = __half2half2(reinterpret_cast<__half const &>(lhs));
__half2 const *rhs_ptr = reinterpret_cast<__half2 const *>(&rhs);
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N / 2; ++i) {
result_ptr[i] = __hadd2(lhs_pair, rhs_ptr[i]);
}
if (N % 2) {
__half const *b_residual_ptr = reinterpret_cast<__half const *>(&rhs);
__half d_residual = __hadd(reinterpret_cast<__half const &>(lhs), b_residual_ptr[N - 1]);
result[N - 1] = reinterpret_cast<half_t const &>(d_residual);
}
#else
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = lhs + rhs[i];
}
#endif
return result;
}
CUTLASS_HOST_DEVICE
Array<half_t, N> operator()(Array<half_t, N> const & lhs, half_t const &rhs) const {
Array<half_t, N> result;
#if defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 530)
__half2 *result_ptr = reinterpret_cast<__half2 *>(&result);
__half2 const *lhs_ptr = reinterpret_cast<__half2 const *>(&lhs);
__half2 rhs_pair = __half2half2(reinterpret_cast<__half const &>(rhs));
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N / 2; ++i) {
result_ptr[i] = __hadd2(lhs_ptr[i], rhs_pair);
}
if (N % 2) {
__half const *a_residual_ptr = reinterpret_cast<__half const *>(&lhs);
__half d_residual = __hadd(a_residual_ptr[N - 1], reinterpret_cast<__half const &>(rhs));
result[N - 1] = reinterpret_cast<half_t const &>(d_residual);
}
#else
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
result[i] = lhs[i] + rhs;
}
#endif