- Feature Name: simd_basics, cfg_target_feature
- Start Date: 2015-06-02
- RFC PR: (leave this empty)
- Rust Issue: (leave this empty)
Summary
Lay the ground work for building powerful SIMD functionality.
Motivation
SIMD (Single-Instruction Multiple-Data) is an important part of performant modern applications. Most CPUs used for that sort of task provide dedicated hardware and instructions for operating on multiple values in a single instruction, and exposing this is an important part of being a low-level language.
This RFC lays the ground-work for building nice SIMD functionality, but doesn’t fill everything out. The goal here is to provide the raw types and access to the raw instructions on each platform.
Where does this code go? Aka. why not in std
?
This RFC is focused on building stable, powerful SIMD functionality in
external crates, not std
.
This makes it much easier to support functionality only "occasionally"
available with Rust’s preexisting cfg
system. There’s no way for
std
to conditionally provide an API based on the target features
used for the final artifact. Building std
in every configuration is
certainly untenable. Hence, if it were to be in std
, there would
need to be some highly delayed cfg
system to support that sort of
conditional API exposure.
With an external crate, we can leverage cargo
's existing build
infrastructure: compiling with some target features will rebuild with
those features enabled.
Detailed design
The design comes in three parts, all on the path to stabilisation:
- types (
feature(simd_basics)
) - operations (
feature(simd_basics)
) - platform detection (
feature(cfg_target_feature)
)
The general idea is to avoid bad performance cliffs, so that an intrinsic call in Rust maps to preferably one CPU instruction, or, if not, the “optimal” sequence required to do the given operation anyway. This means exposing a lot of platform specific details, since platforms behave very differently: both across architecture families (x86, x86-64, ARM, MIPS, …), and even within a family (x86-64’s Skylake, Haswell, Nehalem, …).
There is definitely a common core of SIMD functionality shared across many platforms, but this RFC doesn’t try to extract that, it is just building tools that can be wrapped into a more uniform API later.
Types & traits
There are two new attributes: repr(simd)
and simd_primitive_trait
#[repr(simd)]
struct f32x4(f32, f32, f23, f23);
#[repr(simd)]
struct Simd2<T>(T, T);
#[simd_primitive_trait]
trait SimdPrim {}
repr(simd)
The simd
repr
can be attached to a struct and will cause such a
struct to be compiled to a SIMD vector. It can be generic, but it is
required that any fully monomorphised instance of the type consist of
only a single “primitive” type, repeated some number of times. The
restrictions on the element type are exactly the same restrictions as
#[simd_primitive_trait]
traits impose on their implementing types.
The repr(simd)
may not enforce that the trait bound exists/does the
right thing at the type checking level for generic repr(simd)
types. As such, it will be possible to get the code-generator to error
out (ala the old transmute
size errosr), however, this shouldn’t
cause problems in practice: libraries wrapping this functionality
would layer type-safety on top (i.e. generic repr(simd)
types would
use the SimdPrim
trait as a bound).
It is illegal to take an internal reference to the fields of a
repr(simd)
type, because the representation of booleans may require
to change, so that booleans are bit-packed. The official external
library providing SIMD support will have private fields so this will
not be generally observable.
simd_primitive_trait
Traits marked with the simd_primitive_trait
attribute are special:
types implementing it are those that can be stored in SIMD
vectors. Initially, only primitives and single-field structs that
store SimdPrim
types will be allowed to implement it.
This is explicitly not a lang item: it is legal to have multiple distinct traits in a compilation. The attribute just adds the restriction and possibly tweaks type’s internal representation (as such, it’s legal for a single type to implement multiple traits with the attribute, if a bit pointless).
This trait exists to allow new-type wrappers around primitives to also be usable in a SIMD context. However, this only works in limited scenarios (i.e. when the type wraps a single primitive) and so needs to be an explicit part of every type’s API: type authors opt-in to being designed-for-SIMD. If it was implicit, changes to private fields may break downstream code.
Operations
CPU vendors usually offer “standard” C headers for their CPU specific
operations, such as arm_neon.h
and the ...mmintrin.h
headers for
x86(-64).
All of these would be exposed as compiler intrinsics with names very
similar to those that the vendor suggests (only difference would be
some form of manual namespacing, e.g. prefixing with the CPU target),
loadable via an extern
block with an appropriate ABI. This subset of
intrinsics would be on the path to stabilisation (that is, one can
"import" them with extern
in stable code), and would not be exported
by std
.
extern "rust-intrinsic" {
fn x86_mm_abs_epi16(a: Simd8<i16>) -> Simd8<i16>;
// ...
}
These all use entirely concrete types, and this is the core interface
to these intrinsics: essentially it is just allowing code to exactly
specify a CPU instruction to use. These intrinsics only actually work
on a subset of the CPUs that Rust targets, and are only be available
for extern
ing on those targets. The signatures are typechecked, but
in a “duck-typed” manner: it will just ensure that the types are SIMD
vectors with the appropriate length and element type, it will not
enforce a specific nominal type.
There would additionally be a small set of cross-platform operations that are either generally efficiently supported everywhere or are extremely useful. These won’t necessarily map to a single instruction, but will be shimmed as efficiently as possible.
- shuffles and extracting/inserting elements
- comparisons
Lastly, arithmetic and conversions are supported via built-in operators.
Shuffles & element operations
One of the most powerful features of SIMD is the ability to rearrange data within vectors, giving super-linear speed-ups sometimes. As such, shuffles are exposed generally: intrinsics that represent arbitrary shuffles.
This may violate the “one instruction per instrinsic” principal depending on the shuffle, but rearranging SIMD vectors is extremely useful, and providing a direct intrinsic lets the compiler (a) do the programmers work in synthesising the optimal (short) sequence of instructions to get a given shuffle and (b) track data through shuffles without having to understand all the details of every platform specific intrinsic for shuffling.
extern "rust-intrinsic" {
fn simd_shuffle2<T, Elem>(v: T, w: T, i0: u32, i1: u32) -> Simd2<Elem>;
fn simd_shuffle4<T, Elem>(v: T, w: T, i0: u32, i1: u32, i2: u32, i3: u32) -> Sidm4<Elem>;
fn simd_shuffle8<T, Elem>(v: T, w: T,
i0: u32, i1: u32, i2: u32, i3: u32,
i4: u32, i5: u32, i6: u32, i7: u32) -> Simd8<Elem>;
fn simd_shuffle16<T, Elem>(v: T, w: T,
i0: u32, i1: u32, i2: u32, i3: u32,
i4: u32, i5: u32, i6: u32, i7: u32
i8: u32, i9: u32, i10: u32, i11: u32,
i12: u32, i13: u32, i14: u32, i15: u32) -> Simd16<Elem>;
}
The raw definitions are only checked for validity at monomorphisation
time, ensure that T
is a SIMD vector, U
is the element type of T
etc. Libraries can use traits to ensure that these will be enforced by
the type checker too.
This approach has some downsides: simd_shuffle32
(e.g. Simd32<u8>
on AVX, and Simd32<u16>
on AVX-512) and especially simd_shuffle64
(e.g. Simd64<u8>
on AVX-512) are unwieldy. These have similar type
"safety"/code-generation errors to the vectors themselves.
These operations are semantically:
// vector of double length
let z = concat(v, w);
return [z[i0], z[i1], z[i2], ...]
The indices iN
have to be compile time constants. Out of bounds
indices yield unspecified results.
Similarly, intrinsics for inserting/extracting elements into/out of vectors are provided, to allow modelling the SIMD vectors as actual CPU registers as much as possible:
extern "rust-intrinsic" {
fn simd_insert<T, Elem>(v: T, i0: u32, elem: Elem) -> T;
fn simd_extract<T, Elem>(v: T, i0: u32) -> Elem;
}
The i0
indices do not have to be constant. These are equivalent to
v[i0] = elem
and v[i0]
respectively. They are type checked
similarly to the shuffles.
Comparisons
Comparisons are implemented via intrinsics, because the current comparison operator infrastructure doesn’t easily lend itself to return vectors, as required.
The raw signatures would look like:
extern "rust-intrinsic" {
fn simd_eq<T, U>(v: T, w: T) -> U;
fn simd_ne<T, U>(v: T, w: T) -> U;
fn simd_lt<T, U>(v: T, w: T) -> U;
fn simd_le<T, U>(v: T, w: T) -> U;
fn simd_gt<T, U>(v: T, w: T) -> U;
fn simd_ge<T, U>(v: T, w: T) -> U;
}
These are type checked during code-generation similarly to the
shuffles. Ensuring that T
and U
has the same length, and that U
is appropriately “boolean”-y. Libraries can use traits to ensure that
these will be enforced by the type checker too.
Built-in functionality
Any type marked repr(simd)
automatically has the +
, -
and *
operators work. The /
operator works for floating point, and the
<<
and >>
ones work for integers.
SIMD vectors can be converted with as
. As with intrinsics, this is
"duck-typed" it is possible to cast a vector type V
to a type W
if
their lengths match and their elements are castable (i.e. are
primitives), there’s no enforcement of nominal types.
All of these are never checked: explicit SIMD is essentially only required for speed, and checking inflates one instruction to 5 or more.
Platform Detection
The availability of efficient SIMD functionality is very fine-grained,
and our current cfg(target_arch = "...")
is not precise enough. This
RFC proposes a target_feature
cfg
, that would be set to the
features of the architecture that are known to be supported by the
exact target e.g.
- a default x86-64 compilation would essentially only set
target_feature = "sse"
andtarget_feature = "sse2"
- compiling with
-C target-feature="+sse4.2"
would settarget_feature = "sse4.2"
,target_feature = "sse.4.1"
, …,target_feature = "sse"
. - compiling with
-C target-cpu=native
on a modern CPU might settarget_feature = "avx2"
,target_feature = "avx"
, …
The possible values of target_feature
will be a selected whitelist,
not necessarily just everything LLVM understands. There are other
non-SIMD features that might have target_feature
s set too, such as
popcnt
and rdrnd
on x86/x86-64.)
With a cfg_if_else!
macro that expands to the first cfg
that is
satisfied (ala @alexcrichton’s cascade), code might look
like:
cfg_if_else! {
if #[cfg(target_feature = "avx")] {
fn foo() { /* use AVX things */ }
} else if #[cfg(target_feature = "sse4.1")] {
fn foo() { /* use SSE4.1 things */ }
} else if #[cfg(target_feature = "sse2")] {
fn foo() { /* use SSE2 things */ }
} else if #[cfg(target_feature = "neon")] {
fn foo() { /* use NEON things */ }
} else {
fn foo() { /* universal fallback */ }
}
}
Extensions
- scatter/gather operations allow (partially) operating on a SIMD
vector of pointers. This would require extending
SimdPrim
to also allow pointer types. - allow (and ignore for everything but type checking) zero-sized types
in
repr(simd)
structs, to allow tagging them with markers
Alternatives
-
The SIMD on-route-to-stable intrinsics could have their own ABI
-
Intrinsics could instead by namespaced by ABI,
extern "x86-intrinsic"
,extern "arm-intrinsic"
. -
There could be more syntactic support for shuffles, either with true syntax, or with a syntax extension. The latter might look like:
shuffle![x, y, i0, i1, i2, i3, i4, ...]
. However, this requires that shuffles are restricted to a single type only (i.e.Simd4<T>
can be shuffled toSimd4<T>
but nothing else), or some sort of type synthesis. The compiler has to somehow work out the return value:let x: Simd4<u32> = ...; let y: Simd4<u32> = ...; // reverse all the elements. let z = shuffle![x, y, 7, 6, 5, 4, 3, 2, 1, 0];
Presumably
z
should beSimd8<u32>
, but it’s not obvious how the compiler can know this. Therepr(simd)
approach means there may be more than one SIMD-vector type with theSimd8<u32>
shape (or, in fact, there may be zero). -
Instead of platform detection, there could be feature detection (e.g. "platform supports something equivalent to x86’s
DPPS
"), but there probably aren’t enough cross-platform commonalities for this to be worth it. (Each “feature” would essentially be a platform specificcfg
anyway.) -
Check vector operators in debug mode just like the scalar versions.
Unresolved questions
- Should integer vectors get
/
and%
automatically? Most CPUs don’t support them for vectors. - How should out-of-bounds shuffle and insert/extract indices be handled?