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switch to std::simd, expand SIMD & docs #1239

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merged 5 commits into from
Aug 10, 2022
Merged

switch to std::simd, expand SIMD & docs #1239

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599d7f8
switch to std::simd, expand SIMD stuff & docs
TheIronBorn Jul 7, 2022
d4b8748
fix simd ints, clarify mask behavior
TheIronBorn Jul 11, 2022
f89f15f
fix doc link
TheIronBorn Aug 4, 2022
2fab15d
fix stdsimd, add mask opt notes
TheIronBorn Aug 8, 2022
949d70f
fix doc test
TheIronBorn Aug 8, 2022
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11 changes: 2 additions & 9 deletions Cargo.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -41,8 +41,8 @@ alloc = ["rand_core/alloc"]
# Option: use getrandom package for seeding
getrandom = ["rand_core/getrandom"]

# Option (requires nightly): experimental SIMD support
simd_support = ["packed_simd"]
# Option (requires nightly Rust): experimental SIMD support
simd_support = []

# Option (enabled by default): enable StdRng
std_rng = ["rand_chacha"]
Expand All @@ -68,13 +68,6 @@ log = { version = "0.4.4", optional = true }
serde = { version = "1.0.103", features = ["derive"], optional = true }
rand_chacha = { path = "rand_chacha", version = "0.3.0", default-features = false, optional = true }

[dependencies.packed_simd]
# NOTE: so far no version works reliably due to dependence on unstable features
package = "packed_simd_2"
version = "0.3.7"
optional = true
features = ["into_bits"]

[target.'cfg(unix)'.dependencies]
# Used for fork protection (reseeding.rs)
libc = { version = "0.2.22", optional = true, default-features = false }
Expand Down
5 changes: 3 additions & 2 deletions src/distributions/bernoulli.rs
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Expand Up @@ -14,6 +14,7 @@ use core::{fmt, u64};

#[cfg(feature = "serde1")]
use serde::{Serialize, Deserialize};

/// The Bernoulli distribution.
///
/// This is a special case of the Binomial distribution where `n = 1`.
Expand Down Expand Up @@ -147,10 +148,10 @@ mod test {
use crate::Rng;

#[test]
#[cfg(feature="serde1")]
#[cfg(feature = "serde1")]
fn test_serializing_deserializing_bernoulli() {
let coin_flip = Bernoulli::new(0.5).unwrap();
let de_coin_flip : Bernoulli = bincode::deserialize(&bincode::serialize(&coin_flip).unwrap()).unwrap();
let de_coin_flip: Bernoulli = bincode::deserialize(&bincode::serialize(&coin_flip).unwrap()).unwrap();

assert_eq!(coin_flip.p_int, de_coin_flip.p_int);
}
Expand Down
74 changes: 39 additions & 35 deletions src/distributions/float.rs
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Expand Up @@ -8,11 +8,11 @@

//! Basic floating-point number distributions

use crate::distributions::utils::FloatSIMDUtils;
use crate::distributions::utils::{IntAsSIMD, FloatAsSIMD, FloatSIMDUtils};
use crate::distributions::{Distribution, Standard};
use crate::Rng;
use core::mem;
#[cfg(feature = "simd_support")] use packed_simd::*;
#[cfg(feature = "simd_support")] use core::simd::*;

#[cfg(feature = "serde1")]
use serde::{Serialize, Deserialize};
Expand Down Expand Up @@ -99,7 +99,7 @@ macro_rules! float_impls {
// The exponent is encoded using an offset-binary representation
let exponent_bits: $u_scalar =
(($exponent_bias + exponent) as $u_scalar) << $fraction_bits;
$ty::from_bits(self | exponent_bits)
$ty::from_bits(self | $uty::splat(exponent_bits))
}
}

Expand All @@ -108,13 +108,13 @@ macro_rules! float_impls {
// Multiply-based method; 24/53 random bits; [0, 1) interval.
// We use the most significant bits because for simple RNGs
// those are usually more random.
let float_size = mem::size_of::<$f_scalar>() as u32 * 8;
let float_size = mem::size_of::<$f_scalar>() as $u_scalar * 8;
let precision = $fraction_bits + 1;
let scale = 1.0 / ((1 as $u_scalar << precision) as $f_scalar);

let value: $uty = rng.gen();
let value = value >> (float_size - precision);
scale * $ty::cast_from_int(value)
let value = value >> $uty::splat(float_size - precision);
$ty::splat(scale) * $ty::cast_from_int(value)
}
}

Expand All @@ -123,14 +123,14 @@ macro_rules! float_impls {
// Multiply-based method; 24/53 random bits; (0, 1] interval.
// We use the most significant bits because for simple RNGs
// those are usually more random.
let float_size = mem::size_of::<$f_scalar>() as u32 * 8;
let float_size = mem::size_of::<$f_scalar>() as $u_scalar * 8;
let precision = $fraction_bits + 1;
let scale = 1.0 / ((1 as $u_scalar << precision) as $f_scalar);

let value: $uty = rng.gen();
let value = value >> (float_size - precision);
let value = value >> $uty::splat(float_size - precision);
// Add 1 to shift up; will not overflow because of right-shift:
scale * $ty::cast_from_int(value + 1)
$ty::splat(scale) * $ty::cast_from_int(value + $uty::splat(1))
}
}

Expand All @@ -140,11 +140,11 @@ macro_rules! float_impls {
// We use the most significant bits because for simple RNGs
// those are usually more random.
use core::$f_scalar::EPSILON;
let float_size = mem::size_of::<$f_scalar>() as u32 * 8;
let float_size = mem::size_of::<$f_scalar>() as $u_scalar * 8;

let value: $uty = rng.gen();
let fraction = value >> (float_size - $fraction_bits);
fraction.into_float_with_exponent(0) - (1.0 - EPSILON / 2.0)
let fraction = value >> $uty::splat(float_size - $fraction_bits);
fraction.into_float_with_exponent(0) - $ty::splat(1.0 - EPSILON / 2.0)
}
}
}
Expand All @@ -169,10 +169,10 @@ float_impls! { f64x4, u64x4, f64, u64, 52, 1023 }
#[cfg(feature = "simd_support")]
float_impls! { f64x8, u64x8, f64, u64, 52, 1023 }


#[cfg(test)]
mod tests {
use super::*;
use crate::distributions::utils::FloatAsSIMD;
use crate::rngs::mock::StepRng;

const EPSILON32: f32 = ::core::f32::EPSILON;
Expand All @@ -182,29 +182,31 @@ mod tests {
($fnn:ident, $ty:ident, $ZERO:expr, $EPSILON:expr) => {
#[test]
fn $fnn() {
let two = $ty::splat(2.0);

// Standard
let mut zeros = StepRng::new(0, 0);
assert_eq!(zeros.gen::<$ty>(), $ZERO);
let mut one = StepRng::new(1 << 8 | 1 << (8 + 32), 0);
assert_eq!(one.gen::<$ty>(), $EPSILON / 2.0);
assert_eq!(one.gen::<$ty>(), $EPSILON / two);
let mut max = StepRng::new(!0, 0);
assert_eq!(max.gen::<$ty>(), 1.0 - $EPSILON / 2.0);
assert_eq!(max.gen::<$ty>(), $ty::splat(1.0) - $EPSILON / two);

// OpenClosed01
let mut zeros = StepRng::new(0, 0);
assert_eq!(zeros.sample::<$ty, _>(OpenClosed01), 0.0 + $EPSILON / 2.0);
assert_eq!(zeros.sample::<$ty, _>(OpenClosed01), $ZERO + $EPSILON / two);
let mut one = StepRng::new(1 << 8 | 1 << (8 + 32), 0);
assert_eq!(one.sample::<$ty, _>(OpenClosed01), $EPSILON);
let mut max = StepRng::new(!0, 0);
assert_eq!(max.sample::<$ty, _>(OpenClosed01), $ZERO + 1.0);
assert_eq!(max.sample::<$ty, _>(OpenClosed01), $ZERO + $ty::splat(1.0));

// Open01
let mut zeros = StepRng::new(0, 0);
assert_eq!(zeros.sample::<$ty, _>(Open01), 0.0 + $EPSILON / 2.0);
assert_eq!(zeros.sample::<$ty, _>(Open01), $ZERO + $EPSILON / two);
let mut one = StepRng::new(1 << 9 | 1 << (9 + 32), 0);
assert_eq!(one.sample::<$ty, _>(Open01), $EPSILON / 2.0 * 3.0);
assert_eq!(one.sample::<$ty, _>(Open01), $EPSILON / two * $ty::splat(3.0));
let mut max = StepRng::new(!0, 0);
assert_eq!(max.sample::<$ty, _>(Open01), 1.0 - $EPSILON / 2.0);
assert_eq!(max.sample::<$ty, _>(Open01), $ty::splat(1.0) - $EPSILON / two);
}
};
}
Expand All @@ -222,29 +224,31 @@ mod tests {
($fnn:ident, $ty:ident, $ZERO:expr, $EPSILON:expr) => {
#[test]
fn $fnn() {
let two = $ty::splat(2.0);

// Standard
let mut zeros = StepRng::new(0, 0);
assert_eq!(zeros.gen::<$ty>(), $ZERO);
let mut one = StepRng::new(1 << 11, 0);
assert_eq!(one.gen::<$ty>(), $EPSILON / 2.0);
assert_eq!(one.gen::<$ty>(), $EPSILON / two);
let mut max = StepRng::new(!0, 0);
assert_eq!(max.gen::<$ty>(), 1.0 - $EPSILON / 2.0);
assert_eq!(max.gen::<$ty>(), $ty::splat(1.0) - $EPSILON / two);

// OpenClosed01
let mut zeros = StepRng::new(0, 0);
assert_eq!(zeros.sample::<$ty, _>(OpenClosed01), 0.0 + $EPSILON / 2.0);
assert_eq!(zeros.sample::<$ty, _>(OpenClosed01), $ZERO + $EPSILON / two);
let mut one = StepRng::new(1 << 11, 0);
assert_eq!(one.sample::<$ty, _>(OpenClosed01), $EPSILON);
let mut max = StepRng::new(!0, 0);
assert_eq!(max.sample::<$ty, _>(OpenClosed01), $ZERO + 1.0);
assert_eq!(max.sample::<$ty, _>(OpenClosed01), $ZERO + $ty::splat(1.0));

// Open01
let mut zeros = StepRng::new(0, 0);
assert_eq!(zeros.sample::<$ty, _>(Open01), 0.0 + $EPSILON / 2.0);
assert_eq!(zeros.sample::<$ty, _>(Open01), $ZERO + $EPSILON / two);
let mut one = StepRng::new(1 << 12, 0);
assert_eq!(one.sample::<$ty, _>(Open01), $EPSILON / 2.0 * 3.0);
assert_eq!(one.sample::<$ty, _>(Open01), $EPSILON / two * $ty::splat(3.0));
let mut max = StepRng::new(!0, 0);
assert_eq!(max.sample::<$ty, _>(Open01), 1.0 - $EPSILON / 2.0);
assert_eq!(max.sample::<$ty, _>(Open01), $ty::splat(1.0) - $EPSILON / two);
}
};
}
Expand Down Expand Up @@ -296,16 +300,16 @@ mod tests {
// non-SIMD types; we assume this pattern continues across all
// SIMD types.

test_samples(&Standard, f32x2::new(0.0, 0.0), &[
f32x2::new(0.0035963655, 0.7346052),
f32x2::new(0.09778172, 0.20298547),
f32x2::new(0.34296435, 0.81664366),
test_samples(&Standard, f32x2::from([0.0, 0.0]), &[
f32x2::from([0.0035963655, 0.7346052]),
f32x2::from([0.09778172, 0.20298547]),
f32x2::from([0.34296435, 0.81664366]),
]);

test_samples(&Standard, f64x2::new(0.0, 0.0), &[
f64x2::new(0.7346051961657583, 0.20298547462974248),
f64x2::new(0.8166436635290655, 0.7423708925400552),
f64x2::new(0.16387782224016323, 0.9087068770169618),
test_samples(&Standard, f64x2::from([0.0, 0.0]), &[
f64x2::from([0.7346051961657583, 0.20298547462974248]),
f64x2::from([0.8166436635290655, 0.7423708925400552]),
f64x2::from([0.16387782224016323, 0.9087068770169618]),
]);
}
}
Expand Down
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