Auto merge of #93146 - workingjubilee:use-std-simd, r=Mark-Simulacrum

pub use std::simd::StdFloat;

Syncs portable-simd up to commit rust-lang/portable-simd@03f6fbb21e,
Diff: 533f0fc81a...03f6fbb21e

This sync requires a little bit more legwork because it also introduces a trait into `std::simd`, so that it is no longer simply a reexport of `core::simd`. Out of simple-minded consistency and to allow more options, I replicated the pattern for the way `core::simd` is integrated in the first place, however this is not necessary if it doesn't acquire any interdependencies inside `std`: it could be a simple crate reexport. I just don't know yet if that will happen or not.

To summarize other misc changes:
- Shifts no longer panic, now wrap on too-large shifts (like `Simd` integers usually do!)
- mask16x32 will now be many i16s, not many i32s... 🙃
- `#[must_use]` is spread around generously
- Adjusts division, float min/max, and `Mask::{from,to}_array` internally to be faster
- Adds the much-requested `Simd::cast::<U>` function (equivalent to `simd.to_array().map(|lane| lane as U)`)
This commit is contained in:
bors 2022-02-03 09:15:16 +00:00
commit 796bf14f2e
18 changed files with 543 additions and 341 deletions

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@ -2,5 +2,6 @@
members = [
"crates/core_simd",
"crates/std_float",
"crates/test_helpers",
]

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@ -26,3 +26,6 @@ features = ["alloc"]
[dev-dependencies.test_helpers]
path = "../test_helpers"
[dev-dependencies]
std_float = { path = "../std_float/", features = ["as_crate"] }

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@ -1,11 +1,13 @@
#![cfg_attr(feature = "std", feature(portable_simd))]
#![feature(portable_simd)]
extern crate std_float;
/// Benchmarks game nbody code
/// Taken from the `packed_simd` crate
/// Run this benchmark with `cargo test --example nbody`
#[cfg(feature = "std")]
mod nbody {
use core_simd::*;
use core_simd::simd::*;
#[allow(unused)] // False positive?
use std_float::StdFloat;
use std::f64::consts::PI;
const SOLAR_MASS: f64 = 4.0 * PI * PI;
@ -167,7 +169,6 @@ mod nbody {
}
}
#[cfg(feature = "std")]
#[cfg(test)]
mod tests {
// Good enough for demonstration purposes, not going for strictness here.
@ -184,7 +185,6 @@ mod tests {
}
fn main() {
#[cfg(feature = "std")]
{
let (energy_before, energy_after) = nbody::run(1000);
println!("Energy before: {}", energy_before);

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@ -39,6 +39,10 @@ extern "platform-intrinsic" {
/// fptoui/fptosi/uitofp/sitofp
pub(crate) fn simd_cast<T, U>(x: T) -> U;
/// follows Rust's `T as U` semantics, including saturating float casts
/// which amounts to the same as `simd_cast` for many cases
#[cfg(not(bootstrap))]
pub(crate) fn simd_as<T, U>(x: T) -> U;
/// neg/fneg
pub(crate) fn simd_neg<T>(x: T) -> T;
@ -46,6 +50,10 @@ extern "platform-intrinsic" {
/// fabs
pub(crate) fn simd_fabs<T>(x: T) -> T;
// minnum/maxnum
pub(crate) fn simd_fmin<T>(x: T, y: T) -> T;
pub(crate) fn simd_fmax<T>(x: T, y: T) -> T;
pub(crate) fn simd_eq<T, U>(x: T, y: T) -> U;
pub(crate) fn simd_ne<T, U>(x: T, y: T) -> U;
pub(crate) fn simd_lt<T, U>(x: T, y: T) -> U;
@ -87,29 +95,3 @@ extern "platform-intrinsic" {
#[allow(unused)]
pub(crate) fn simd_select_bitmask<M, T>(m: M, a: T, b: T) -> T;
}
#[cfg(feature = "std")]
mod std {
extern "platform-intrinsic" {
// ceil
pub(crate) fn simd_ceil<T>(x: T) -> T;
// floor
pub(crate) fn simd_floor<T>(x: T) -> T;
// round
pub(crate) fn simd_round<T>(x: T) -> T;
// trunc
pub(crate) fn simd_trunc<T>(x: T) -> T;
// fsqrt
pub(crate) fn simd_fsqrt<T>(x: T) -> T;
// fma
pub(crate) fn simd_fma<T>(x: T, y: T, z: T) -> T;
}
}
#[cfg(feature = "std")]
pub(crate) use crate::simd::intrinsics::std::*;

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@ -12,9 +12,10 @@
)]
mod mask_impl;
use crate::simd::intrinsics;
use crate::simd::{LaneCount, Simd, SimdElement, SupportedLaneCount};
use core::cmp::Ordering;
use core::fmt;
use core::{fmt, mem};
mod sealed {
use super::*;
@ -105,22 +106,39 @@ where
Self(mask_impl::Mask::splat(value))
}
/// Converts an array to a SIMD vector.
/// Converts an array of bools to a SIMD mask.
pub fn from_array(array: [bool; LANES]) -> Self {
let mut vector = Self::splat(false);
for (i, v) in array.iter().enumerate() {
vector.set(i, *v);
// SAFETY: Rust's bool has a layout of 1 byte (u8) with a value of
// true: 0b_0000_0001
// false: 0b_0000_0000
// Thus, an array of bools is also a valid array of bytes: [u8; N]
// This would be hypothetically valid as an "in-place" transmute,
// but these are "dependently-sized" types, so copy elision it is!
unsafe {
let bytes: [u8; LANES] = mem::transmute_copy(&array);
let bools: Simd<i8, LANES> =
intrinsics::simd_ne(Simd::from_array(bytes), Simd::splat(0u8));
Mask::from_int_unchecked(intrinsics::simd_cast(bools))
}
vector
}
/// Converts a SIMD vector to an array.
/// Converts a SIMD mask to an array of bools.
pub fn to_array(self) -> [bool; LANES] {
let mut array = [false; LANES];
for (i, v) in array.iter_mut().enumerate() {
*v = self.test(i);
// This follows mostly the same logic as from_array.
// SAFETY: Rust's bool has a layout of 1 byte (u8) with a value of
// true: 0b_0000_0001
// false: 0b_0000_0000
// Thus, an array of bools is also a valid array of bytes: [u8; N]
// Since our masks are equal to integers where all bits are set,
// we can simply convert them to i8s, and then bitand them by the
// bitpattern for Rust's "true" bool.
// This would be hypothetically valid as an "in-place" transmute,
// but these are "dependently-sized" types, so copy elision it is!
unsafe {
let mut bytes: Simd<i8, LANES> = intrinsics::simd_cast(self.to_int());
bytes &= Simd::splat(1i8);
mem::transmute_copy(&bytes)
}
array
}
/// Converts a vector of integers to a mask, where 0 represents `false` and -1
@ -516,7 +534,7 @@ pub type mask16x8 = Mask<i16, 8>;
pub type mask16x16 = Mask<i16, 16>;
/// Vector of 32 16-bit masks
pub type mask16x32 = Mask<i32, 32>;
pub type mask16x32 = Mask<i16, 32>;
/// Vector of two 32-bit masks
pub type mask32x2 = Mask<i32, 2>;

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@ -1,4 +1,3 @@
use crate::simd::intrinsics;
use crate::simd::{LaneCount, Simd, SimdElement, SupportedLaneCount};
use core::ops::{Add, Mul};
use core::ops::{BitAnd, BitOr, BitXor};
@ -32,232 +31,211 @@ where
}
}
/// Checks if the right-hand side argument of a left- or right-shift would cause overflow.
fn invalid_shift_rhs<T>(rhs: T) -> bool
where
T: Default + PartialOrd + core::convert::TryFrom<usize>,
<T as core::convert::TryFrom<usize>>::Error: core::fmt::Debug,
{
let bits_in_type = T::try_from(8 * core::mem::size_of::<T>()).unwrap();
rhs < T::default() || rhs >= bits_in_type
macro_rules! unsafe_base {
($lhs:ident, $rhs:ident, {$simd_call:ident}, $($_:tt)*) => {
unsafe { $crate::simd::intrinsics::$simd_call($lhs, $rhs) }
};
}
/// Automatically implements operators over references in addition to the provided operator.
macro_rules! impl_ref_ops {
// binary op
{
impl<const $lanes:ident: usize> core::ops::$trait:ident<$rhs:ty> for $type:ty
where
LaneCount<$lanes2:ident>: SupportedLaneCount,
/// SAFETY: This macro should not be used for anything except Shl or Shr, and passed the appropriate shift intrinsic.
/// It handles performing a bitand in addition to calling the shift operator, so that the result
/// is well-defined: LLVM can return a poison value if you shl, lshr, or ashr if rhs >= <Int>::BITS
/// At worst, this will maybe add another instruction and cycle,
/// at best, it may open up more optimization opportunities,
/// or simply be elided entirely, especially for SIMD ISAs which default to this.
///
// FIXME: Consider implementing this in cg_llvm instead?
// cg_clif defaults to this, and scalar MIR shifts also default to wrapping
macro_rules! wrap_bitshift {
($lhs:ident, $rhs:ident, {$simd_call:ident}, $int:ident) => {
unsafe {
$crate::simd::intrinsics::$simd_call(
$lhs,
$rhs.bitand(Simd::splat(<$int>::BITS as $int - 1)),
)
}
};
}
// Division by zero is poison, according to LLVM.
// So is dividing the MIN value of a signed integer by -1,
// since that would return MAX + 1.
// FIXME: Rust allows <SInt>::MIN / -1,
// so we should probably figure out how to make that safe.
macro_rules! int_divrem_guard {
( $lhs:ident,
$rhs:ident,
{ const PANIC_ZERO: &'static str = $zero:literal;
const PANIC_OVERFLOW: &'static str = $overflow:literal;
$simd_call:ident
},
$int:ident ) => {
if $rhs.lanes_eq(Simd::splat(0)).any() {
panic!($zero);
} else if <$int>::MIN != 0
&& ($lhs.lanes_eq(Simd::splat(<$int>::MIN))
// type inference can break here, so cut an SInt to size
& $rhs.lanes_eq(Simd::splat(-1i64 as _))).any()
{
type Output = $output:ty;
$(#[$attrs:meta])*
fn $fn:ident($self_tok:ident, $rhs_arg:ident: $rhs_arg_ty:ty) -> Self::Output $body:tt
}
} => {
impl<const $lanes: usize> core::ops::$trait<$rhs> for $type
where
LaneCount<$lanes2>: SupportedLaneCount,
{
type Output = $output;
$(#[$attrs])*
fn $fn($self_tok, $rhs_arg: $rhs_arg_ty) -> Self::Output $body
panic!($overflow);
} else {
unsafe { $crate::simd::intrinsics::$simd_call($lhs, $rhs) }
}
};
}
/// Automatically implements operators over vectors and scalars for a particular vector.
macro_rules! impl_op {
{ impl Add for $scalar:ty } => {
impl_op! { @binary $scalar, Add::add, simd_add }
};
{ impl Sub for $scalar:ty } => {
impl_op! { @binary $scalar, Sub::sub, simd_sub }
};
{ impl Mul for $scalar:ty } => {
impl_op! { @binary $scalar, Mul::mul, simd_mul }
};
{ impl Div for $scalar:ty } => {
impl_op! { @binary $scalar, Div::div, simd_div }
};
{ impl Rem for $scalar:ty } => {
impl_op! { @binary $scalar, Rem::rem, simd_rem }
};
{ impl Shl for $scalar:ty } => {
impl_op! { @binary $scalar, Shl::shl, simd_shl }
};
{ impl Shr for $scalar:ty } => {
impl_op! { @binary $scalar, Shr::shr, simd_shr }
};
{ impl BitAnd for $scalar:ty } => {
impl_op! { @binary $scalar, BitAnd::bitand, simd_and }
};
{ impl BitOr for $scalar:ty } => {
impl_op! { @binary $scalar, BitOr::bitor, simd_or }
};
{ impl BitXor for $scalar:ty } => {
impl_op! { @binary $scalar, BitXor::bitxor, simd_xor }
};
macro_rules! for_base_types {
( T = ($($scalar:ident),*);
type Lhs = Simd<T, N>;
type Rhs = Simd<T, N>;
type Output = $out:ty;
// generic binary op with assignment when output is `Self`
{ @binary $scalar:ty, $trait:ident :: $trait_fn:ident, $intrinsic:ident } => {
impl_ref_ops! {
impl<const LANES: usize> core::ops::$trait<Self> for Simd<$scalar, LANES>
where
LaneCount<LANES>: SupportedLaneCount,
{
type Output = Self;
impl $op:ident::$call:ident {
$macro_impl:ident $inner:tt
}) => {
$(
impl<const N: usize> $op<Self> for Simd<$scalar, N>
where
$scalar: SimdElement,
LaneCount<N>: SupportedLaneCount,
{
type Output = $out;
#[inline]
fn $trait_fn(self, rhs: Self) -> Self::Output {
unsafe {
intrinsics::$intrinsic(self, rhs)
#[inline]
#[must_use = "operator returns a new vector without mutating the inputs"]
fn $call(self, rhs: Self) -> Self::Output {
$macro_impl!(self, rhs, $inner, $scalar)
}
}
}
})*
}
}
// A "TokenTree muncher": takes a set of scalar types `T = {};`
// type parameters for the ops it implements, `Op::fn` names,
// and a macro that expands into an expr, substituting in an intrinsic.
// It passes that to for_base_types, which expands an impl for the types,
// using the expanded expr in the function, and recurses with itself.
//
// tl;dr impls a set of ops::{Traits} for a set of types
macro_rules! for_base_ops {
(
T = $types:tt;
type Lhs = Simd<T, N>;
type Rhs = Simd<T, N>;
type Output = $out:ident;
impl $op:ident::$call:ident
$inner:tt
$($rest:tt)*
) => {
for_base_types! {
T = $types;
type Lhs = Simd<T, N>;
type Rhs = Simd<T, N>;
type Output = $out;
impl $op::$call
$inner
}
for_base_ops! {
T = $types;
type Lhs = Simd<T, N>;
type Rhs = Simd<T, N>;
type Output = $out;
$($rest)*
}
};
($($done:tt)*) => {
// Done.
}
}
/// Implements floating-point operators for the provided types.
macro_rules! impl_float_ops {
{ $($scalar:ty),* } => {
$(
impl_op! { impl Add for $scalar }
impl_op! { impl Sub for $scalar }
impl_op! { impl Mul for $scalar }
impl_op! { impl Div for $scalar }
impl_op! { impl Rem for $scalar }
)*
};
// Integers can always accept add, mul, sub, bitand, bitor, and bitxor.
// For all of these operations, simd_* intrinsics apply wrapping logic.
for_base_ops! {
T = (i8, i16, i32, i64, isize, u8, u16, u32, u64, usize);
type Lhs = Simd<T, N>;
type Rhs = Simd<T, N>;
type Output = Self;
impl Add::add {
unsafe_base { simd_add }
}
impl Mul::mul {
unsafe_base { simd_mul }
}
impl Sub::sub {
unsafe_base { simd_sub }
}
impl BitAnd::bitand {
unsafe_base { simd_and }
}
impl BitOr::bitor {
unsafe_base { simd_or }
}
impl BitXor::bitxor {
unsafe_base { simd_xor }
}
impl Div::div {
int_divrem_guard {
const PANIC_ZERO: &'static str = "attempt to divide by zero";
const PANIC_OVERFLOW: &'static str = "attempt to divide with overflow";
simd_div
}
}
impl Rem::rem {
int_divrem_guard {
const PANIC_ZERO: &'static str = "attempt to calculate the remainder with a divisor of zero";
const PANIC_OVERFLOW: &'static str = "attempt to calculate the remainder with overflow";
simd_rem
}
}
// The only question is how to handle shifts >= <Int>::BITS?
// Our current solution uses wrapping logic.
impl Shl::shl {
wrap_bitshift { simd_shl }
}
impl Shr::shr {
wrap_bitshift {
// This automatically monomorphizes to lshr or ashr, depending,
// so it's fine to use it for both UInts and SInts.
simd_shr
}
}
}
/// Implements unsigned integer operators for the provided types.
macro_rules! impl_unsigned_int_ops {
{ $($scalar:ty),* } => {
$(
impl_op! { impl Add for $scalar }
impl_op! { impl Sub for $scalar }
impl_op! { impl Mul for $scalar }
impl_op! { impl BitAnd for $scalar }
impl_op! { impl BitOr for $scalar }
impl_op! { impl BitXor for $scalar }
// We don't need any special precautions here:
// Floats always accept arithmetic ops, but may become NaN.
for_base_ops! {
T = (f32, f64);
type Lhs = Simd<T, N>;
type Rhs = Simd<T, N>;
type Output = Self;
// Integers panic on divide by 0
impl_ref_ops! {
impl<const LANES: usize> core::ops::Div<Self> for Simd<$scalar, LANES>
where
LaneCount<LANES>: SupportedLaneCount,
{
type Output = Self;
impl Add::add {
unsafe_base { simd_add }
}
#[inline]
fn div(self, rhs: Self) -> Self::Output {
if rhs.as_array()
.iter()
.any(|x| *x == 0)
{
panic!("attempt to divide by zero");
}
impl Mul::mul {
unsafe_base { simd_mul }
}
// Guards for div(MIN, -1),
// this check only applies to signed ints
if <$scalar>::MIN != 0 && self.as_array().iter()
.zip(rhs.as_array().iter())
.any(|(x,y)| *x == <$scalar>::MIN && *y == -1 as _) {
panic!("attempt to divide with overflow");
}
unsafe { intrinsics::simd_div(self, rhs) }
}
}
}
impl Sub::sub {
unsafe_base { simd_sub }
}
// remainder panics on zero divisor
impl_ref_ops! {
impl<const LANES: usize> core::ops::Rem<Self> for Simd<$scalar, LANES>
where
LaneCount<LANES>: SupportedLaneCount,
{
type Output = Self;
impl Div::div {
unsafe_base { simd_div }
}
#[inline]
fn rem(self, rhs: Self) -> Self::Output {
if rhs.as_array()
.iter()
.any(|x| *x == 0)
{
panic!("attempt to calculate the remainder with a divisor of zero");
}
// Guards for rem(MIN, -1)
// this branch applies the check only to signed ints
if <$scalar>::MIN != 0 && self.as_array().iter()
.zip(rhs.as_array().iter())
.any(|(x,y)| *x == <$scalar>::MIN && *y == -1 as _) {
panic!("attempt to calculate the remainder with overflow");
}
unsafe { intrinsics::simd_rem(self, rhs) }
}
}
}
// shifts panic on overflow
impl_ref_ops! {
impl<const LANES: usize> core::ops::Shl<Self> for Simd<$scalar, LANES>
where
LaneCount<LANES>: SupportedLaneCount,
{
type Output = Self;
#[inline]
fn shl(self, rhs: Self) -> Self::Output {
// TODO there is probably a better way of doing this
if rhs.as_array()
.iter()
.copied()
.any(invalid_shift_rhs)
{
panic!("attempt to shift left with overflow");
}
unsafe { intrinsics::simd_shl(self, rhs) }
}
}
}
impl_ref_ops! {
impl<const LANES: usize> core::ops::Shr<Self> for Simd<$scalar, LANES>
where
LaneCount<LANES>: SupportedLaneCount,
{
type Output = Self;
#[inline]
fn shr(self, rhs: Self) -> Self::Output {
// TODO there is probably a better way of doing this
if rhs.as_array()
.iter()
.copied()
.any(invalid_shift_rhs)
{
panic!("attempt to shift with overflow");
}
unsafe { intrinsics::simd_shr(self, rhs) }
}
}
}
)*
};
impl Rem::rem {
unsafe_base { simd_rem }
}
}
/// Implements unsigned integer operators for the provided types.
macro_rules! impl_signed_int_ops {
{ $($scalar:ty),* } => {
impl_unsigned_int_ops! { $($scalar),* }
};
}
impl_unsigned_int_ops! { u8, u16, u32, u64, usize }
impl_signed_int_ops! { i8, i16, i32, i64, isize }
impl_float_ops! { f32, f64 }

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@ -5,47 +5,6 @@ macro_rules! implement {
{
$type:ty, $int_type:ty
} => {
#[cfg(feature = "std")]
impl<const LANES: usize> Simd<$type, LANES>
where
LaneCount<LANES>: SupportedLaneCount,
{
/// Returns the smallest integer greater than or equal to each lane.
#[must_use = "method returns a new vector and does not mutate the original value"]
#[inline]
pub fn ceil(self) -> Self {
unsafe { intrinsics::simd_ceil(self) }
}
/// Returns the largest integer value less than or equal to each lane.
#[must_use = "method returns a new vector and does not mutate the original value"]
#[inline]
pub fn floor(self) -> Self {
unsafe { intrinsics::simd_floor(self) }
}
/// Rounds to the nearest integer value. Ties round toward zero.
#[must_use = "method returns a new vector and does not mutate the original value"]
#[inline]
pub fn round(self) -> Self {
unsafe { intrinsics::simd_round(self) }
}
/// Returns the floating point's integer value, with its fractional part removed.
#[must_use = "method returns a new vector and does not mutate the original value"]
#[inline]
pub fn trunc(self) -> Self {
unsafe { intrinsics::simd_trunc(self) }
}
/// Returns the floating point's fractional value, with its integer part removed.
#[must_use = "method returns a new vector and does not mutate the original value"]
#[inline]
pub fn fract(self) -> Self {
self - self.trunc()
}
}
impl<const LANES: usize> Simd<$type, LANES>
where
LaneCount<LANES>: SupportedLaneCount,

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@ -75,6 +75,36 @@ where
Self(array)
}
/// Performs lanewise conversion of a SIMD vector's elements to another SIMD-valid type.
/// This follows the semantics of Rust's `as` conversion for casting
/// integers to unsigned integers (interpreting as the other type, so `-1` to `MAX`),
/// and from floats to integers (truncating, or saturating at the limits) for each lane,
/// or vice versa.
///
/// # Examples
/// ```
/// # #![feature(portable_simd)]
/// # #[cfg(feature = "std")] use core_simd::Simd;
/// # #[cfg(not(feature = "std"))] use core::simd::Simd;
/// let floats: Simd<f32, 4> = Simd::from_array([1.9, -4.5, f32::INFINITY, f32::NAN]);
/// let ints = floats.cast::<i32>();
/// assert_eq!(ints, Simd::from_array([1, -4, i32::MAX, 0]));
///
/// // Formally equivalent, but `Simd::cast` can optimize better.
/// assert_eq!(ints, Simd::from_array(floats.to_array().map(|x| x as i32)));
///
/// // The float conversion does not round-trip.
/// let floats_again = ints.cast();
/// assert_ne!(floats, floats_again);
/// assert_eq!(floats_again, Simd::from_array([1.0, -4.0, 2147483647.0, 0.0]));
/// ```
#[must_use]
#[inline]
#[cfg(not(bootstrap))]
pub fn cast<U: SimdElement>(self) -> Simd<U, LANES> {
unsafe { intrinsics::simd_as(self) }
}
/// Reads from potentially discontiguous indices in `slice` to construct a SIMD vector.
/// If an index is out-of-bounds, the lane is instead selected from the `or` vector.
///

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@ -38,29 +38,6 @@ macro_rules! impl_float_vector {
unsafe { intrinsics::simd_fabs(self) }
}
/// Fused multiply-add. Computes `(self * a) + b` with only one rounding error,
/// yielding a more accurate result than an unfused multiply-add.
///
/// Using `mul_add` *may* be more performant than an unfused multiply-add if the target
/// architecture has a dedicated `fma` CPU instruction. However, this is not always
/// true, and will be heavily dependent on designing algorithms with specific target
/// hardware in mind.
#[cfg(feature = "std")]
#[inline]
#[must_use = "method returns a new vector and does not mutate the original value"]
pub fn mul_add(self, a: Self, b: Self) -> Self {
unsafe { intrinsics::simd_fma(self, a, b) }
}
/// Produces a vector where every lane has the square root value
/// of the equivalently-indexed lane in `self`
#[inline]
#[must_use = "method returns a new vector and does not mutate the original value"]
#[cfg(feature = "std")]
pub fn sqrt(self) -> Self {
unsafe { intrinsics::simd_fsqrt(self) }
}
/// Takes the reciprocal (inverse) of each lane, `1/x`.
#[inline]
#[must_use = "method returns a new vector and does not mutate the original value"]
@ -128,8 +105,8 @@ macro_rules! impl_float_vector {
self.abs().lanes_ne(Self::splat(0.0)) & (self.to_bits() & Self::splat(<$type>::INFINITY).to_bits()).lanes_eq(Simd::splat(0))
}
/// Returns true for each lane if its value is neither neither zero, infinite,
/// subnormal, or `NaN`.
/// Returns true for each lane if its value is neither zero, infinite,
/// subnormal, nor `NaN`.
#[inline]
#[must_use = "method returns a new mask and does not mutate the original value"]
pub fn is_normal(self) -> Mask<$mask_ty, LANES> {
@ -164,11 +141,7 @@ macro_rules! impl_float_vector {
#[inline]
#[must_use = "method returns a new vector and does not mutate the original value"]
pub fn min(self, other: Self) -> Self {
// TODO consider using an intrinsic
self.is_nan().select(
other,
self.lanes_ge(other).select(other, self)
)
unsafe { intrinsics::simd_fmin(self, other) }
}
/// Returns the maximum of each lane.
@ -177,11 +150,7 @@ macro_rules! impl_float_vector {
#[inline]
#[must_use = "method returns a new vector and does not mutate the original value"]
pub fn max(self, other: Self) -> Self {
// TODO consider using an intrinsic
self.is_nan().select(
other,
self.lanes_le(other).select(other, self)
)
unsafe { intrinsics::simd_fmax(self, other) }
}
/// Restrict each lane to a certain interval unless it is NaN.

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@ -0,0 +1,37 @@
#![feature(portable_simd)]
macro_rules! cast_types {
($start:ident, $($target:ident),*) => {
mod $start {
use core_simd::simd::Simd;
type Vector<const N: usize> = Simd<$start, N>;
$(
mod $target {
use super::*;
test_helpers::test_lanes! {
fn cast_as<const N: usize>() {
test_helpers::test_unary_elementwise(
&Vector::<N>::cast::<$target>,
&|x| x as $target,
&|_| true,
)
}
}
}
)*
}
};
}
// The hypothesis is that widening conversions aren't terribly interesting.
cast_types!(f32, f64, i8, u8, usize, isize);
cast_types!(f64, f32, i8, u8, usize, isize);
cast_types!(i8, u8, f32);
cast_types!(u8, i8, f32);
cast_types!(i16, u16, i8, u8, f32);
cast_types!(u16, i16, i8, u8, f32);
cast_types!(i32, u32, i8, u8, f32, f64);
cast_types!(u32, i32, i8, u8, f32, f64);
cast_types!(i64, u64, i8, u8, isize, usize, f32, f64);
cast_types!(u64, i64, i8, u8, isize, usize, f32, f64);
cast_types!(isize, usize, i8, u8, f32, f64);
cast_types!(usize, isize, i8, u8, f32, f64);

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@ -546,6 +546,8 @@ macro_rules! impl_float_tests {
#[cfg(feature = "std")]
mod std {
use std_float::StdFloat;
use super::*;
test_helpers::test_lanes! {
fn sqrt<const LANES: usize>() {

View File

@ -3,6 +3,8 @@
macro_rules! float_rounding_test {
{ $scalar:tt, $int_scalar:tt } => {
mod $scalar {
use std_float::StdFloat;
type Vector<const LANES: usize> = core_simd::Simd<$scalar, LANES>;
type Scalar = $scalar;
type IntScalar = $int_scalar;

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@ -0,0 +1,13 @@
[package]
name = "std_float"
version = "0.1.0"
edition = "2021"
# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
[dependencies]
core_simd = { path = "../core_simd" }
[features]
default = ["as_crate"]
as_crate = []

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@ -0,0 +1,165 @@
#![cfg_attr(feature = "as_crate", no_std)] // We are std!
#![cfg_attr(
feature = "as_crate",
feature(platform_intrinsics),
feature(portable_simd)
)]
#[cfg(not(feature = "as_crate"))]
use core::simd;
#[cfg(feature = "as_crate")]
use core_simd::simd;
use simd::{LaneCount, Simd, SupportedLaneCount};
#[cfg(feature = "as_crate")]
mod experimental {
pub trait Sealed {}
}
#[cfg(feature = "as_crate")]
use experimental as sealed;
use crate::sealed::Sealed;
// "platform intrinsics" are essentially "codegen intrinsics"
// each of these may be scalarized and lowered to a libm call
extern "platform-intrinsic" {
// ceil
fn simd_ceil<T>(x: T) -> T;
// floor
fn simd_floor<T>(x: T) -> T;
// round
fn simd_round<T>(x: T) -> T;
// trunc
fn simd_trunc<T>(x: T) -> T;
// fsqrt
fn simd_fsqrt<T>(x: T) -> T;
// fma
fn simd_fma<T>(x: T, y: T, z: T) -> T;
}
/// This trait provides a possibly-temporary implementation of float functions
/// that may, in the absence of hardware support, canonicalize to calling an
/// operating system's `math.h` dynamically-loaded library (also known as a
/// shared object). As these conditionally require runtime support, they
/// should only appear in binaries built assuming OS support: `std`.
///
/// However, there is no reason SIMD types, in general, need OS support,
/// as for many architectures an embedded binary may simply configure that
/// support itself. This means these types must be visible in `core`
/// but have these functions available in `std`.
///
/// [`f32`] and [`f64`] achieve a similar trick by using "lang items", but
/// due to compiler limitations, it is harder to implement this approach for
/// abstract data types like [`Simd`]. From that need, this trait is born.
///
/// It is possible this trait will be replaced in some manner in the future,
/// when either the compiler or its supporting runtime functions are improved.
/// For now this trait is available to permit experimentation with SIMD float
/// operations that may lack hardware support, such as `mul_add`.
pub trait StdFloat: Sealed + Sized {
/// Fused multiply-add. Computes `(self * a) + b` with only one rounding error,
/// yielding a more accurate result than an unfused multiply-add.
///
/// Using `mul_add` *may* be more performant than an unfused multiply-add if the target
/// architecture has a dedicated `fma` CPU instruction. However, this is not always
/// true, and will be heavily dependent on designing algorithms with specific target
/// hardware in mind.
#[inline]
#[must_use = "method returns a new vector and does not mutate the original value"]
fn mul_add(self, a: Self, b: Self) -> Self {
unsafe { simd_fma(self, a, b) }
}
/// Produces a vector where every lane has the square root value
/// of the equivalently-indexed lane in `self`
#[inline]
#[must_use = "method returns a new vector and does not mutate the original value"]
fn sqrt(self) -> Self {
unsafe { simd_fsqrt(self) }
}
/// Returns the smallest integer greater than or equal to each lane.
#[must_use = "method returns a new vector and does not mutate the original value"]
#[inline]
fn ceil(self) -> Self {
unsafe { simd_ceil(self) }
}
/// Returns the largest integer value less than or equal to each lane.
#[must_use = "method returns a new vector and does not mutate the original value"]
#[inline]
fn floor(self) -> Self {
unsafe { simd_floor(self) }
}
/// Rounds to the nearest integer value. Ties round toward zero.
#[must_use = "method returns a new vector and does not mutate the original value"]
#[inline]
fn round(self) -> Self {
unsafe { simd_round(self) }
}
/// Returns the floating point's integer value, with its fractional part removed.
#[must_use = "method returns a new vector and does not mutate the original value"]
#[inline]
fn trunc(self) -> Self {
unsafe { simd_trunc(self) }
}
/// Returns the floating point's fractional value, with its integer part removed.
#[must_use = "method returns a new vector and does not mutate the original value"]
fn fract(self) -> Self;
}
impl<const N: usize> Sealed for Simd<f32, N> where LaneCount<N>: SupportedLaneCount {}
impl<const N: usize> Sealed for Simd<f64, N> where LaneCount<N>: SupportedLaneCount {}
// We can safely just use all the defaults.
impl<const N: usize> StdFloat for Simd<f32, N>
where
LaneCount<N>: SupportedLaneCount,
{
/// Returns the floating point's fractional value, with its integer part removed.
#[must_use = "method returns a new vector and does not mutate the original value"]
#[inline]
fn fract(self) -> Self {
self - self.trunc()
}
}
impl<const N: usize> StdFloat for Simd<f64, N>
where
LaneCount<N>: SupportedLaneCount,
{
/// Returns the floating point's fractional value, with its integer part removed.
#[must_use = "method returns a new vector and does not mutate the original value"]
#[inline]
fn fract(self) -> Self {
self - self.trunc()
}
}
#[cfg(test)]
mod tests {
use super::*;
use simd::*;
#[test]
fn everything_works() {
let x = f32x4::from_array([0.1, 0.5, 0.6, -1.5]);
let x2 = x + x;
let _xc = x.ceil();
let _xf = x.floor();
let _xr = x.round();
let _xt = x.trunc();
let _xfma = x.mul_add(x, x);
let _xsqrt = x.sqrt();
let _ = x2.abs() * x2;
}
}

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@ -311,6 +311,7 @@
#![feature(panic_can_unwind)]
#![feature(panic_unwind)]
#![feature(pin_static_ref)]
#![feature(platform_intrinsics)]
#![feature(portable_simd)]
#![feature(prelude_import)]
#![feature(ptr_as_uninit)]
@ -456,8 +457,6 @@ pub use core::pin;
pub use core::ptr;
#[stable(feature = "rust1", since = "1.0.0")]
pub use core::result;
#[unstable(feature = "portable_simd", issue = "86656")]
pub use core::simd;
#[unstable(feature = "async_stream", issue = "79024")]
pub use core::stream;
#[stable(feature = "i128", since = "1.26.0")]
@ -504,6 +503,25 @@ pub mod time;
#[unstable(feature = "once_cell", issue = "74465")]
pub mod lazy;
// Pull in `std_float` crate into libstd. The contents of
// `std_float` are in a different repository: rust-lang/portable-simd.
#[path = "../../portable-simd/crates/std_float/src/lib.rs"]
#[allow(missing_debug_implementations, dead_code, unsafe_op_in_unsafe_fn, unused_unsafe)]
#[allow(rustdoc::bare_urls)]
#[unstable(feature = "portable_simd", issue = "86656")]
#[cfg(not(all(miri, doctest)))] // Miri does not support all SIMD intrinsics
mod std_float;
#[cfg(not(all(miri, doctest)))] // Miri does not support all SIMD intrinsics
#[doc = include_str!("../../portable-simd/crates/core_simd/src/core_simd_docs.md")]
#[unstable(feature = "portable_simd", issue = "86656")]
pub mod simd {
#[doc(inline)]
pub use crate::std_float::StdFloat;
#[doc(inline)]
pub use core::simd::*;
}
#[stable(feature = "futures_api", since = "1.36.0")]
pub mod task {
//! Types and Traits for working with asynchronous tasks.

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@ -0,0 +1,23 @@
// run-pass
// This is the converse of the other libm test.
#![feature(portable_simd)]
use std::simd::f32x4;
use std::simd::StdFloat;
// For SIMD float ops, the LLIR version which is used to implement the portable
// forms of them may become calls to math.h AKA libm. So, we can't guarantee
// we can compile them for #![no_std] crates.
//
// However, we can expose some of these ops via an extension trait.
fn main() {
let x = f32x4::from_array([0.1, 0.5, 0.6, -1.5]);
let x2 = x + x;
let _xc = x.ceil();
let _xf = x.floor();
let _xr = x.round();
let _xt = x.trunc();
let _xfma = x.mul_add(x, x);
let _xsqrt = x.sqrt();
let _ = x2.abs() * x2;
}

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@ -1,7 +1,8 @@
// May not matter, since people can use them with a nightly feature.
// However this tests to guarantee they don't leak out via portable_simd,
// and thus don't accidentally get stabilized.
use std::simd::intrinsics; //~ERROR E0603
use core::simd::intrinsics; //~ERROR E0433
use std::simd::intrinsics; //~ERROR E0432
fn main() {
()

View File

@ -1,15 +1,16 @@
error[E0603]: module `intrinsics` is private
--> $DIR/portable-intrinsics-arent-exposed.rs:4:16
error[E0433]: failed to resolve: maybe a missing crate `core`?
--> $DIR/portable-intrinsics-arent-exposed.rs:4:5
|
LL | use core::simd::intrinsics;
| ^^^^ maybe a missing crate `core`?
error[E0432]: unresolved import `std::simd::intrinsics`
--> $DIR/portable-intrinsics-arent-exposed.rs:5:5
|
LL | use std::simd::intrinsics;
| ^^^^^^^^^^ private module
|
note: the module `intrinsics` is defined here
--> $SRC_DIR/core/src/lib.rs:LL:COL
|
LL | pub use crate::core_simd::simd::*;
| ^^^^^^^^^^^^^^^^^^^^^^^^^
| ^^^^^^^^^^^^^^^^^^^^^ no `intrinsics` in `simd`
error: aborting due to previous error
error: aborting due to 2 previous errors
For more information about this error, try `rustc --explain E0603`.
Some errors have detailed explanations: E0432, E0433.
For more information about an error, try `rustc --explain E0432`.