From 8dd16259287f58f9273002717ec4d27e97127719 Mon Sep 17 00:00:00 2001 From: Daniel Baumann Date: Wed, 12 Jun 2024 07:43:14 +0200 Subject: Merging upstream version 127.0. Signed-off-by: Daniel Baumann --- third_party/rust/packed_simd/src/lib.rs | 348 -------------------------------- 1 file changed, 348 deletions(-) delete mode 100644 third_party/rust/packed_simd/src/lib.rs (limited to 'third_party/rust/packed_simd/src/lib.rs') diff --git a/third_party/rust/packed_simd/src/lib.rs b/third_party/rust/packed_simd/src/lib.rs deleted file mode 100644 index 867cc10e9e..0000000000 --- a/third_party/rust/packed_simd/src/lib.rs +++ /dev/null @@ -1,348 +0,0 @@ -//! # Portable packed SIMD vectors -//! -//! This crate is proposed for stabilization as `std::packed_simd` in [RFC2366: -//! `std::simd`](https://github.com/rust-lang/rfcs/pull/2366) . -//! -//! The examples available in the -//! [`examples/`](https://github.com/rust-lang-nursery/packed_simd/tree/master/examples) -//! sub-directory of the crate showcase how to use the library in practice. -//! -//! ## Table of contents -//! -//! - [Introduction](#introduction) -//! - [Vector types](#vector-types) -//! - [Conditional operations](#conditional-operations) -//! - [Conversions](#conversions) -//! - [Hardware Features](#hardware-features) -//! - [Performance guide](https://rust-lang-nursery.github.io/packed_simd/perf-guide/) -//! -//! ## Introduction -//! -//! This crate exports [`Simd<[T; N]>`][`Simd`]: a packed vector of `N` -//! elements of type `T` as well as many type aliases for this type: for -//! example, [`f32x4`], which is just an alias for `Simd<[f32; 4]>`. -//! -//! The operations on packed vectors are, by default, "vertical", that is, they -//! are applied to each vector lane in isolation of the others: -//! -//! ``` -//! # use packed_simd::*; -//! let a = i32x4::new(1, 2, 3, 4); -//! let b = i32x4::new(5, 6, 7, 8); -//! assert_eq!(a + b, i32x4::new(6, 8, 10, 12)); -//! ``` -//! -//! Many "horizontal" operations are also provided: -//! -//! ``` -//! # use packed_simd::*; -//! # let a = i32x4::new(1, 2, 3, 4); -//! assert_eq!(a.wrapping_sum(), 10); -//! ``` -//! -//! In virtually all architectures vertical operations are fast, while -//! horizontal operations are, by comparison, much slower. That is, the -//! most portably-efficient way of performing a reduction over a slice -//! is to collect the results into a vector using vertical operations, -//! and performing a single horizontal operation at the end: -//! -//! ``` -//! # use packed_simd::*; -//! fn reduce(x: &[i32]) -> i32 { -//! assert_eq!(x.len() % 4, 0); -//! let mut sum = i32x4::splat(0); // [0, 0, 0, 0] -//! for i in (0..x.len()).step_by(4) { -//! sum += i32x4::from_slice_unaligned(&x[i..]); -//! } -//! sum.wrapping_sum() -//! } -//! -//! let x = [0, 1, 2, 3, 4, 5, 6, 7]; -//! assert_eq!(reduce(&x), 28); -//! ``` -//! -//! ## Vector types -//! -//! The vector type aliases are named according to the following scheme: -//! -//! > `{element_type}x{number_of_lanes} == Simd<[element_type; -//! number_of_lanes]>` -//! -//! where the following element types are supported: -//! -//! * `i{element_width}`: signed integer -//! * `u{element_width}`: unsigned integer -//! * `f{element_width}`: float -//! * `m{element_width}`: mask (see below) -//! * `*{const,mut} T`: `const` and `mut` pointers -//! -//! ## Basic operations -//! -//! ``` -//! # use packed_simd::*; -//! // Sets all elements to `0`: -//! let a = i32x4::splat(0); -//! -//! // Reads a vector from a slice: -//! let mut arr = [0, 0, 0, 1, 2, 3, 4, 5]; -//! let b = i32x4::from_slice_unaligned(&arr); -//! -//! // Reads the 4-th element of a vector: -//! assert_eq!(b.extract(3), 1); -//! -//! // Returns a new vector where the 4-th element is replaced with `1`: -//! let a = a.replace(3, 1); -//! assert_eq!(a, b); -//! -//! // Writes a vector to a slice: -//! let a = a.replace(2, 1); -//! a.write_to_slice_unaligned(&mut arr[4..]); -//! assert_eq!(arr, [0, 0, 0, 1, 0, 0, 1, 1]); -//! ``` -//! -//! ## Conditional operations -//! -//! One often needs to perform an operation on some lanes of the vector. Vector -//! masks, like `m32x4`, allow selecting on which vector lanes an operation is -//! to be performed: -//! -//! ``` -//! # use packed_simd::*; -//! let a = i32x4::new(1, 1, 2, 2); -//! -//! // Add `1` to the first two lanes of the vector. -//! let m = m16x4::new(true, true, false, false); -//! let a = m.select(a + 1, a); -//! assert_eq!(a, i32x4::splat(2)); -//! ``` -//! -//! The elements of a vector mask are either `true` or `false`. Here `true` -//! means that a lane is "selected", while `false` means that a lane is not -//! selected. -//! -//! All vector masks implement a `mask.select(a: T, b: T) -> T` method that -//! works on all vectors that have the same number of lanes as the mask. The -//! resulting vector contains the elements of `a` for those lanes for which the -//! mask is `true`, and the elements of `b` otherwise. -//! -//! The example constructs a mask with the first two lanes set to `true` and -//! the last two lanes set to `false`. This selects the first two lanes of `a + -//! 1` and the last two lanes of `a`, producing a vector where the first two -//! lanes have been incremented by `1`. -//! -//! > note: mask `select` can be used on vector types that have the same number -//! > of lanes as the mask. The example shows this by using [`m16x4`] instead -//! > of [`m32x4`]. It is _typically_ more performant to use a mask element -//! > width equal to the element width of the vectors being operated upon. -//! > This is, however, not true for 512-bit wide vectors when targeting -//! > AVX-512, where the most efficient masks use only 1-bit per element. -//! -//! All vertical comparison operations returns masks: -//! -//! ``` -//! # use packed_simd::*; -//! let a = i32x4::new(1, 1, 3, 3); -//! let b = i32x4::new(2, 2, 0, 0); -//! -//! // ge: >= (Greater Eequal; see also lt, le, gt, eq, ne). -//! let m = a.ge(i32x4::splat(2)); -//! -//! if m.any() { -//! // all / any / none allow coherent control flow -//! let d = m.select(a, b); -//! assert_eq!(d, i32x4::new(2, 2, 3, 3)); -//! } -//! ``` -//! -//! ## Conversions -//! -//! * **lossless widening conversions**: [`From`]/[`Into`] are implemented for -//! vectors with the same number of lanes when the conversion is value -//! preserving (same as in `std`). -//! -//! * **safe bitwise conversions**: The cargo feature `into_bits` provides the -//! `IntoBits/FromBits` traits (`x.into_bits()`). These perform safe bitwise -//! `transmute`s when all bit patterns of the source type are valid bit -//! patterns of the target type and are also implemented for the -//! architecture-specific vector types of `std::arch`. For example, `let x: -//! u8x8 = m8x8::splat(true).into_bits();` is provided because all `m8x8` bit -//! patterns are valid `u8x8` bit patterns. However, the opposite is not -//! true, not all `u8x8` bit patterns are valid `m8x8` bit-patterns, so this -//! operation cannot be performed safely using `x.into_bits()`; one needs to -//! use `unsafe { crate::mem::transmute(x) }` for that, making sure that the -//! value in the `u8x8` is a valid bit-pattern of `m8x8`. -//! -//! * **numeric casts** (`as`): are performed using [`FromCast`]/[`Cast`] -//! (`x.cast()`), just like `as`: -//! -//! * casting integer vectors whose lane types have the same size (e.g. -//! `i32xN` -> `u32xN`) is a **no-op**, -//! -//! * casting from a larger integer to a smaller integer (e.g. `u32xN` -> -//! `u8xN`) will **truncate**, -//! -//! * casting from a smaller integer to a larger integer (e.g. `u8xN` -> -//! `u32xN`) will: -//! * **zero-extend** if the source is unsigned, or -//! * **sign-extend** if the source is signed, -//! -//! * casting from a float to an integer will **round the float towards -//! zero**, -//! -//! * casting from an integer to float will produce the floating point -//! representation of the integer, **rounding to nearest, ties to even**, -//! -//! * casting from an `f32` to an `f64` is perfect and lossless, -//! -//! * casting from an `f64` to an `f32` **rounds to nearest, ties to even**. -//! -//! Numeric casts are not very "precise": sometimes lossy, sometimes value -//! preserving, etc. -//! -//! ## Hardware Features -//! -//! This crate can use different hardware features based on your configured -//! `RUSTFLAGS`. For example, with no configured `RUSTFLAGS`, `u64x8` on -//! x86_64 will use SSE2 operations like `PCMPEQD`. If you configure -//! `RUSTFLAGS='-C target-feature=+avx2,+avx'` on supported x86_64 hardware -//! the same `u64x8` may use wider AVX2 operations like `VPCMPEQQ`. It is -//! important for performance and for hardware support requirements that -//! you choose an appropriate set of `target-feature` and `target-cpu` -//! options during builds. For more information, see the [Performance -//! guide](https://rust-lang-nursery.github.io/packed_simd/perf-guide/) - -#![feature( - adt_const_params, - repr_simd, - rustc_attrs, - platform_intrinsics, - stdsimd, - arm_target_feature, - link_llvm_intrinsics, - core_intrinsics, - stmt_expr_attributes, - custom_inner_attributes, -)] -#![allow(non_camel_case_types, non_snake_case, - // FIXME: these types are unsound in C FFI already - // See https://github.com/rust-lang/rust/issues/53346 - improper_ctypes_definitions, - incomplete_features, - clippy::cast_possible_truncation, - clippy::cast_lossless, - clippy::cast_possible_wrap, - clippy::cast_precision_loss, - // TODO: manually add the `#[must_use]` attribute where appropriate - clippy::must_use_candidate, - // This lint is currently broken for generic code - // See https://github.com/rust-lang/rust-clippy/issues/3410 - clippy::use_self, - clippy::wrong_self_convention, - clippy::from_over_into, -)] -#![cfg_attr(test, feature(hashmap_internals))] -#![cfg_attr(doc_cfg, feature(doc_cfg))] -#![deny(rust_2018_idioms, clippy::missing_inline_in_public_items)] -#![no_std] - -use cfg_if::cfg_if; - -cfg_if! { - if #[cfg(feature = "core_arch")] { - #[allow(unused_imports)] - use core_arch as arch; - } else { - #[allow(unused_imports)] - use core::arch; - } -} - -#[cfg(all(target_arch = "wasm32", test))] -use wasm_bindgen_test::*; - -#[allow(unused_imports)] -use core::{ - /* arch (handled above), */ cmp, f32, f64, fmt, hash, hint, i128, i16, i32, i64, i8, intrinsics, - isize, iter, marker, mem, ops, ptr, slice, u128, u16, u32, u64, u8, usize, -}; - -#[macro_use] -mod testing; -#[macro_use] -mod api; -mod codegen; -mod sealed; - -pub use crate::sealed::{Mask, Shuffle, Simd as SimdVector, SimdArray}; - -/// Packed SIMD vector type. -/// -/// # Examples -/// -/// ``` -/// # use packed_simd::Simd; -/// let v = Simd::<[i32; 4]>::new(0, 1, 2, 3); -/// assert_eq!(v.extract(2), 2); -/// ``` -#[repr(transparent)] -#[derive(Copy, Clone)] -pub struct Simd( - // FIXME: this type should be private, - // but it currently must be public for the - // `shuffle!` macro to work: it needs to - // access the internal `repr(simd)` type - // to call the shuffle intrinsics. - #[doc(hidden)] pub ::Tuple, -); - -impl sealed::Seal for Simd {} - -/// Wrapper over `T` implementing a lexicoraphical order via the `PartialOrd` -/// and/or `Ord` traits. -#[repr(transparent)] -#[derive(Copy, Clone, Debug)] -#[allow(clippy::missing_inline_in_public_items)] -pub struct LexicographicallyOrdered(T); - -mod masks; -pub use self::masks::*; - -mod v16; -pub use self::v16::*; - -mod v32; -pub use self::v32::*; - -mod v64; -pub use self::v64::*; - -mod v128; -pub use self::v128::*; - -mod v256; -pub use self::v256::*; - -mod v512; -pub use self::v512::*; - -mod vSize; -pub use self::vSize::*; - -mod vPtr; -pub use self::vPtr::*; - -pub use self::api::cast::*; - -#[cfg(feature = "into_bits")] -pub use self::api::into_bits::*; - -// Re-export the shuffle intrinsics required by the `shuffle!` macro. -#[doc(hidden)] -pub use self::codegen::llvm::{ - __shuffle_vector16, __shuffle_vector2, __shuffle_vector32, __shuffle_vector4, __shuffle_vector64, - __shuffle_vector8, -}; - -pub(crate) mod llvm { - pub(crate) use crate::codegen::llvm::*; -} -- cgit v1.2.3