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Add SIMD support for determinant and inverse

Browse source 
Also:
- Change the travis script: no use `cargo bench`ing in beta or stable.
- Add bench test for Matrix4's determinant().
- clean code a bit
This commit is contained in:
Luxko 2017-02-25 20:31:38 +08:00
parent d45536f1bd
commit 68d1d27222
4 changed files with 61 additions and 110 deletions
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4
.travis.yml
View file

@ -6,4 +6,6 @@ rust:
- stable
script:
- cargo build && cargo test && cargo bench
- cargo build && cargo test
- if [[ "$TRAVIS_RUST_VERSION" == "nightly" ]]; then cargo bench;
- if [[ "$TRAVIS_RUST_VERSION" == "nightly" ]]; then cargo build --features "use_simd" && cargo test --features "use_simd" && cargo bench --features "use_simd"

2
benches/mat.rs
View file

@ -59,3 +59,5 @@ bench_unop!(_bench_matrix4_invert, Matrix4<f32>, invert);
bench_unop!(_bench_matrix2_transpose, Matrix2<f32>, transpose);
bench_unop!(_bench_matrix3_transpose, Matrix3<f32>, transpose);
bench_unop!(_bench_matrix4_transpose, Matrix4<f32>, transpose);
bench_unop!(_bench_matrix4_determinant, Matrix4<f32>, determinant);

59
src/macros.rs
View file

@ -381,21 +381,11 @@ macro_rules! impl_operator_simd {
let $x: $Simd = self.into(); $body
}
}
// #[cfg(feature = "simd")]
// impl<'a> $Op for &'a $Lhs {
// type Output = $Output;
// #[inline]
// fn $op(self) -> $Output {
// let $x: $Simd = (*self).into(); $body
// }
// }
};
// When the right operand is a scalar
(@rs [$Simd:ident]; $Op:ident<$Rhs:ty> for $Lhs:ty {
fn $op:ident($lhs:ident, $rhs:ident) -> $Output:ty { $body:expr }
}) => {
impl $Op<$Rhs> for $Lhs {
#[inline]
fn $op(self, other: $Rhs) -> $Output {
@ -411,6 +401,7 @@ macro_rules! impl_operator_simd {
}
}
};
// When the right operand is a compound type
([$Simd:ident]; $Op:ident<$Rhs:ty> for $Lhs:ty {
fn $op:ident($lhs:ident, $rhs:ident) -> $Output:ty { $body:expr }
@ -430,7 +421,6 @@ macro_rules! impl_operator_simd {
let ($lhs, $rhs): ($Simd, $Simd) = (self.into(), (*other).into()); $body
}
}
impl<'a> $Op<$Rhs> for &'a $Lhs {
#[inline]
@ -439,7 +429,6 @@ macro_rules! impl_operator_simd {
}
}
impl<'a, 'b> $Op<&'a $Rhs> for &'b $Lhs {
#[inline]
fn $op(self, other: &'a $Rhs) -> $Output {
@ -447,18 +436,17 @@ macro_rules! impl_operator_simd {
}
}
};
// When the left operand is a scalar
(@ls [$Simd:ident]; $Op:ident<$Rhs:ty> for $Lhs:ident {
fn $op:ident($lhs:ident, $rhs:ident) -> $Output:ty { $body:expr }
}) => {
impl $Op<$Rhs> for $Lhs {
#[inline]
fn $op(self, other: $Rhs) -> $Output {
let ($lhs, $rhs): ($Simd, $Simd) = ($Simd::splat(self), other.into()); $body
}
}
impl<'a> $Op<&'a $Rhs> for $Lhs {
#[inline]
@ -467,47 +455,4 @@ macro_rules! impl_operator_simd {
}
}
};
// // When left is row-vec, right is colume-matrix
// (@vm [$Simd: ident]; $Op:ident<$Rhs:ty> for $Lhs:ty {
// fn $op:ident($lhs:ident, $rhs:ident) -> $Output:ty {
// }
// })
// When matrix with matrix
(@mm $Op:ident<$Rhs:ty> for $Lhs:ty {
fn $op:ident($lhs:ident, $rhs:ident) -> $Output:ty { $body: expr }
}) => {
impl $Op<$Rhs> for $Lhs {
#[inline]
fn $op(self, other: $Rhs) -> $Output {
let ($lhs, $rhs) = (self, other); $body
}
}
impl<'a> $Op<&'a $Rhs> for $Lhs {
#[inline]
fn $op(self, other: &'a $Rhs) -> $Output {
let ($lhs, $rhs) = (self, other); $body
}
}
impl<'a> $Op<$Rhs> for &'a $Lhs {
#[inline]
fn $op(self, other: $Rhs) -> $Output {
let ($lhs, $rhs) = (self, other); $body
}
}
impl<'a, 'b> $Op<&'a $Rhs> for &'b $Lhs {
#[inline]
fn $op(self, other: &'a $Rhs) -> $Output {
let ($lhs, $rhs) = (self, other); $body
}
}
}
}

106
src/matrix.rs
View file

@ -645,23 +645,10 @@ impl<S: BaseFloat> SquareMatrix for Matrix4<S> {
}
fn determinant(&self) -> S {
let m0 = Matrix3::new(self[1][1], self[2][1], self[3][1],
self[1][2], self[2][2], self[3][2],
self[1][3], self[2][3], self[3][3]);
let m1 = Matrix3::new(self[0][1], self[2][1], self[3][1],
self[0][2], self[2][2], self[3][2],
self[0][3], self[2][3], self[3][3]);
let m2 = Matrix3::new(self[0][1], self[1][1], self[3][1],
self[0][2], self[1][2], self[3][2],
self[0][3], self[1][3], self[3][3]);
let m3 = Matrix3::new(self[0][1], self[1][1], self[2][1],
self[0][2], self[1][2], self[2][2],
self[0][3], self[1][3], self[2][3]);
self[0][0] * m0.determinant() -
self[1][0] * m1.determinant() +
self[2][0] * m2.determinant() -
self[3][0] * m3.determinant()
let tmp = unsafe {
det_sub_proc_unsafe(self, 1, 2, 3)
};
tmp.dot(Vector4::new(self[0][0], self[1][0], self[2][0], self[3][0]))
}
#[inline]
@ -672,6 +659,12 @@ impl<S: BaseFloat> SquareMatrix for Matrix4<S> {
self[3][3])
}
// The new implementation results in negative optimization when used
// without SIMD. so we opt them in with configuration.
// A better option would be using specialization. But currently somewhat
// specialization is too buggy, and it won't apply here. I'm getting
// weird error msgs. Help wanted.
#[cfg(not(feature = "use_simd"))]
fn invert(&self) -> Option<Matrix4<S>> {
let det = self.determinant();
if ulps_eq!(det, &S::zero()) { None } else {
@ -695,6 +688,27 @@ impl<S: BaseFloat> SquareMatrix for Matrix4<S> {
cf(3, 0), cf(3, 1), cf(3, 2), cf(3, 3)))
}
}
#[cfg(feature = "use_simd")]
fn invert(&self) -> Option<Matrix4<S>> {
let tmp0 = unsafe {
det_sub_proc_unsafe(self, 1, 2, 3)
};
let det = tmp0.dot(Vector4::new(self[0][0], self[1][0], self[2][0], self[3][0]));
if ulps_eq!(det, &S::zero()) { None } else {
let inv_det = S::one() / det;
let tmp0 = tmp0 * inv_det;
let tmp1 = unsafe {
det_sub_proc_unsafe(self, 0, 3, 2) * inv_det
};
let tmp2 = unsafe {
det_sub_proc_unsafe(self, 0, 1, 3) * inv_det
};
let tmp3 = unsafe {
det_sub_proc_unsafe(self, 0, 2, 1) * inv_det
};
Some(Matrix4::from_cols(tmp0, tmp1, tmp2, tmp3))
}
}
fn is_diagonal(&self) -> bool {
ulps_eq!(self[0][1], &S::zero()) &&
@ -1036,6 +1050,7 @@ impl_operator!(<S: BaseFloat> Mul<Matrix3<S> > for Matrix3<S> {
// causes the LLVM to miss identical loads and multiplies. This optimization
// causes the code to be auto vectorized properly increasing the performance
// around ~4 times.
// Update: this should now be a bit more efficient
impl_operator!(<S: BaseFloat> Mul<Matrix4<S> > for Matrix4<S> {
fn mul(lhs, rhs) -> Matrix4<S> {
@ -1335,39 +1350,26 @@ impl<S: BaseFloat + Rand> Rand for Matrix4<S> {
}
}
// Specialization strangely won't work for this.
// TODO: find another way
// #[cfg(feature = "use_simd")]
// impl SquareMatrix for Matrix4<f32> {
// fn determinant(&self) -> f32 {
// let a = Simdf32x4::new(self.z[1], self.x[1], self.w[1], self.y[1]);
// let b = Simdf32x4::new(self.y[2], self.y[2], self.z[2], self.z[2]);
// let c = Simdf32x4::new(self.x[3], self.z[3], self.x[3], self.z[3]);
// let mut tmp = a * (b * c);
// let d = Simdf32x4::new(self.y[1], self.y[1], self.z[1], self.z[1]);
// let e = Simdf32x4::new(self.x[2], self.z[2], self.x[2], self.z[2]);
// let f = Simdf32x4::new(self.z[3], self.x[3], self.w[3], self.y[3]);
// let tmp1 = d * (e * f);
// tmp = tmp + tmp1;
// let g = Simdf32x4::new(self.x[1], self.z[1], self.x[1], self.z[1]);
// let h = Simdf32x4::new(self.z[2], self.x[2], self.w[2], self.y[2]);
// let i = Simdf32x4::new(self.y[3], self.y[3], self.z[3], self.z[3]);
// let tmp1 = g * (h * i);
// tmp = tmp + tmp1;
// let tmp1 = g * (b * f);
// tmp = tmp - tmp1;
// let tmp1 = d * (h * c);
// tmp = tmp - tmp1;
// let tmp1 = a * (e * i);
// tmp = tmp - tmp1;
// let tmp: Vector4<f32> = (tmp * Simdf32x4::new(self.x[0], self.y[0], self.z[0], self.w[0])).into();
// tmp.sum()
// }
// }
// Sub procedure for SIMD when dealing with determinant and inversion
#[inline]
unsafe fn det_sub_proc_unsafe<S: BaseFloat>(m: &Matrix4<S>, x: usize, y: usize, z: usize) -> Vector4<S> {
let s: &[S; 16] = m.as_ref();
let a = Vector4::new(*s.get_unchecked(4 + x), *s.get_unchecked(12 + x), *s.get_unchecked(x), *s.get_unchecked(8 + x));
let b = Vector4::new(*s.get_unchecked(8 + y), *s.get_unchecked(8 + y), *s.get_unchecked(4 + y), *s.get_unchecked(4 + y));
let c = Vector4::new(*s.get_unchecked(12 + z), *s.get_unchecked(z), *s.get_unchecked(12 + z), *s.get_unchecked(z));
// #[cfg(feature = "use_simd")]
// impl_operator_simd!(@mm Mul<Vector4<f32>> for Matrix4<f32> {
// fn mul(matrix, vector) -> Vector4<f32> {
// matrix[0] * vector[0] + matrix[1] * vector[1] + matrix[2] * vector[2] + matrix[3] * vector[3]
// }
// });
let d = Vector4::new(*s.get_unchecked(8 + x), *s.get_unchecked(8 + x), *s.get_unchecked(4 + x), *s.get_unchecked(4 + x));
let e = Vector4::new(*s.get_unchecked(12 + y), *s.get_unchecked(y), *s.get_unchecked(12 + y), *s.get_unchecked(y));
let f = Vector4::new(*s.get_unchecked(4 + z), *s.get_unchecked(12 + z), *s.get_unchecked(z), *s.get_unchecked(8 + z));
let g = Vector4::new(*s.get_unchecked(12 + x), *s.get_unchecked(x), *s.get_unchecked(12 + x), *s.get_unchecked(x));
let h = Vector4::new(*s.get_unchecked(4 + y), *s.get_unchecked(12 + y), *s.get_unchecked(y), *s.get_unchecked(8 + y));
let i = Vector4::new(*s.get_unchecked(8 + z), *s.get_unchecked(8 + z), *s.get_unchecked(4 + z), *s.get_unchecked(4 + z));
let mut tmp = a.mul_element_wise(b.mul_element_wise(c));
tmp += d.mul_element_wise(e.mul_element_wise(f));
tmp += g.mul_element_wise(h.mul_element_wise(i));
tmp -= a.mul_element_wise(e.mul_element_wise(i));
tmp -= d.mul_element_wise(h.mul_element_wise(c));
tmp -= g.mul_element_wise(b.mul_element_wise(f));
tmp
}