use super::*; #[inline(always)] pub(crate) fn diff_op_1d( block: &[&[Float]], diag: &[Float], symmetry: Symmetry, optype: OperatorType, prev: ArrayView1, mut fut: ArrayViewMut1, ) { assert_eq!(prev.shape(), fut.shape()); let nx = prev.shape()[0]; assert!(nx >= 2 * block.len()); let dx = if optype == OperatorType::H2 { 1.0 / (nx - 2) as Float } else { 1.0 / (nx - 1) as Float }; let idx = 1.0 / dx; for (bl, f) in block.iter().zip(&mut fut) { let diff = bl .iter() .zip(prev.iter()) .map(|(x, y)| x * y) .sum::(); *f = diff * idx; } // The window needs to be aligned to the diagonal elements, // based on the block size let window_elems_to_skip = block.len() - ((diag.len() - 1) / 2); for (window, f) in prev .windows(diag.len()) .into_iter() .skip(window_elems_to_skip) .zip(fut.iter_mut().skip(block.len())) .take(nx - 2 * block.len()) { let diff = diag.iter().zip(&window).map(|(x, y)| x * y).sum::(); *f = diff * idx; } for (bl, f) in block.iter().zip(fut.iter_mut().rev()) { let diff = bl .iter() .zip(prev.iter().rev()) .map(|(x, y)| x * y) .sum::(); *f = idx * if symmetry == Symmetry::Symmetric { diff } else { -diff }; } } #[derive(PartialEq, Copy, Clone)] pub(crate) enum Symmetry { Symmetric, AntiSymmetric, } #[derive(PartialEq, Copy, Clone)] pub(crate) enum OperatorType { Normal, H2, } #[inline(always)] #[allow(unused)] pub(crate) fn diff_op_col_naive( block: &'static [&'static [Float]], diag: &'static [Float], symmetry: Symmetry, optype: OperatorType, ) -> impl Fn(ArrayView2, ArrayViewMut2) { #[inline(always)] move |prev: ArrayView2, mut fut: ArrayViewMut2| { assert_eq!(prev.shape(), fut.shape()); let nx = prev.shape()[1]; assert!(nx >= 2 * block.len()); assert_eq!(prev.strides()[0], 1); assert_eq!(fut.strides()[0], 1); let dx = if optype == OperatorType::H2 { 1.0 / (nx - 2) as Float } else { 1.0 / (nx - 1) as Float }; let idx = 1.0 / dx; fut.fill(0.0); // First block for (bl, mut fut) in block.iter().zip(fut.axis_iter_mut(ndarray::Axis(1))) { debug_assert_eq!(fut.len(), prev.shape()[0]); for (&bl, prev) in bl.iter().zip(prev.axis_iter(ndarray::Axis(1))) { debug_assert_eq!(prev.len(), fut.len()); fut.scaled_add(idx * bl, &prev); } } let half_diag_width = (diag.len() - 1) / 2; assert!(half_diag_width <= block.len()); // Diagonal entries for (ifut, mut fut) in fut .axis_iter_mut(ndarray::Axis(1)) .enumerate() .skip(block.len()) .take(nx - 2 * block.len()) { for (id, &d) in diag.iter().enumerate() { let offset = ifut - half_diag_width + id; fut.scaled_add(idx * d, &prev.slice(ndarray::s![.., offset])) } } // End block for (bl, mut fut) in block.iter().zip(fut.axis_iter_mut(ndarray::Axis(1)).rev()) { fut.fill(0.0); for (&bl, prev) in bl.iter().zip(prev.axis_iter(ndarray::Axis(1)).rev()) { if symmetry == Symmetry::Symmetric { fut.scaled_add(idx * bl, &prev); } else { fut.scaled_add(-idx * bl, &prev); } } } } } #[inline(always)] pub(crate) fn diff_op_col( block: &'static [&'static [Float]], diag: &'static [Float], symmetry: Symmetry, optype: OperatorType, ) -> impl Fn(ArrayView2, ArrayViewMut2) { diff_op_col_simd(block, diag, symmetry, optype) } #[inline(always)] pub(crate) fn diff_op_col_simd( block: &'static [&'static [Float]], diag: &'static [Float], symmetry: Symmetry, optype: OperatorType, ) -> impl Fn(ArrayView2, ArrayViewMut2) { #[inline(always)] move |prev: ArrayView2, mut fut: ArrayViewMut2| { assert_eq!(prev.shape(), fut.shape()); let nx = prev.shape()[1]; assert!(nx >= 2 * block.len()); assert_eq!(prev.strides()[0], 1); assert_eq!(fut.strides()[0], 1); let dx = if optype == OperatorType::H2 { 1.0 / (nx - 2) as Float } else { 1.0 / (nx - 1) as Float }; let idx = 1.0 / dx; #[cfg(not(feature = "f32"))] type SimdT = packed_simd::f64x8; #[cfg(feature = "f32")] type SimdT = packed_simd::f32x16; let ny = prev.shape()[0]; // How many elements that can be simdified let simdified = SimdT::lanes() * (ny / SimdT::lanes()); let half_diag_width = (diag.len() - 1) / 2; assert!(half_diag_width <= block.len()); let fut_base_ptr = fut.as_mut_ptr(); let fut_stride = fut.strides()[1]; let fut_ptr = |j, i| { debug_assert!(j < ny && i < nx); unsafe { fut_base_ptr.offset(fut_stride * i as isize + j as isize) } }; let prev_base_ptr = prev.as_ptr(); let prev_stride = prev.strides()[1]; let prev_ptr = |j, i| { debug_assert!(j < ny && i < nx); unsafe { prev_base_ptr.offset(prev_stride * i as isize + j as isize) } }; // Not algo necessary, but gives performance increase assert_eq!(fut_stride, prev_stride); // First block { for (ifut, &bl) in block.iter().enumerate() { for j in (0..simdified).step_by(SimdT::lanes()) { let index_to_simd = |i| unsafe { // j never moves past end of slice due to step_by and // rounding down SimdT::from_slice_unaligned(std::slice::from_raw_parts( prev_ptr(j, i), SimdT::lanes(), )) }; let mut f = SimdT::splat(0.0); for (iprev, &bl) in bl.iter().enumerate() { f = index_to_simd(iprev).mul_adde(SimdT::splat(bl), f); } f *= idx; unsafe { f.write_to_slice_unaligned(std::slice::from_raw_parts_mut( fut_ptr(j, ifut), SimdT::lanes(), )); } } for j in simdified..ny { unsafe { let mut f = 0.0; for (iprev, bl) in bl.iter().enumerate() { f += bl * *prev_ptr(j, iprev); } *fut_ptr(j, ifut) = f * idx; } } } } // Diagonal elements { for ifut in block.len()..nx - block.len() { for j in (0..simdified).step_by(SimdT::lanes()) { let index_to_simd = |i| unsafe { // j never moves past end of slice due to step_by and // rounding down SimdT::from_slice_unaligned(std::slice::from_raw_parts( prev_ptr(j, i), SimdT::lanes(), )) }; let mut f = SimdT::splat(0.0); for (id, &d) in diag.iter().enumerate() { let offset = ifut - half_diag_width + id; f = index_to_simd(offset).mul_adde(SimdT::splat(d), f); } f *= idx; unsafe { // puts simd along stride 1, j never goes past end of slice f.write_to_slice_unaligned(std::slice::from_raw_parts_mut( fut_ptr(j, ifut), SimdT::lanes(), )); } } for j in simdified..ny { let mut f = 0.0; for (id, &d) in diag.iter().enumerate() { let offset = ifut - half_diag_width + id; unsafe { f += d * *prev_ptr(j, offset); } } unsafe { *fut_ptr(j, ifut) = idx * f; } } } } // End block { // Get blocks and corresponding offsets // (rev to iterate in ifut increasing order) for (bl, ifut) in block.iter().zip((0..nx).rev()) { for j in (0..simdified).step_by(SimdT::lanes()) { let index_to_simd = |i| unsafe { // j never moves past end of slice due to step_by and // rounding down SimdT::from_slice_unaligned(std::slice::from_raw_parts( prev_ptr(j, i), SimdT::lanes(), )) }; let mut f = SimdT::splat(0.0); for (&bl, iprev) in bl.iter().zip((0..nx).rev()) { f = index_to_simd(iprev).mul_adde(SimdT::splat(bl), f); } f = if symmetry == Symmetry::Symmetric { f * idx } else { -f * idx }; unsafe { f.write_to_slice_unaligned(std::slice::from_raw_parts_mut( fut_ptr(j, ifut), SimdT::lanes(), )); } } for j in simdified..ny { unsafe { let mut f = 0.0; for (&bl, iprev) in bl.iter().zip((0..nx).rev()).rev() { f += bl * *prev_ptr(j, iprev); } *fut_ptr(j, ifut) = if symmetry == Symmetry::Symmetric { f * idx } else { -f * idx }; } } } } } } #[inline(always)] fn product_fast<'a>( u: impl Iterator, v: impl Iterator, ) -> Float { use std::intrinsics::{fadd_fast, fmul_fast}; u.zip(v).fold(0.0, |acc, (&u, &v)| unsafe { // We do not care about the order of multiplication nor addition fadd_fast(acc, fmul_fast(u, v)) }) } #[inline(always)] pub(crate) fn diff_op_row( block: &'static [&'static [Float]], diag: &'static [Float], symmetry: Symmetry, optype: OperatorType, ) -> impl Fn(ArrayView2, ArrayViewMut2) { #[inline(always)] move |prev: ArrayView2, mut fut: ArrayViewMut2| { assert_eq!(prev.shape(), fut.shape()); let nx = prev.shape()[1]; assert!(nx >= 2 * block.len()); assert_eq!(prev.strides()[1], 1); assert_eq!(fut.strides()[1], 1); let dx = if optype == OperatorType::H2 { 1.0 / (nx - 2) as Float } else { 1.0 / (nx - 1) as Float }; let idx = 1.0 / dx; for (prev, mut fut) in prev .axis_iter(ndarray::Axis(0)) .zip(fut.axis_iter_mut(ndarray::Axis(0))) { let prev = prev.as_slice().unwrap(); let fut = fut.as_slice_mut().unwrap(); assert_eq!(prev.len(), fut.len()); assert!(prev.len() >= 2 * block.len()); for (bl, f) in block.iter().zip(fut.iter_mut()) { let diff = product_fast(bl.iter(), prev[..bl.len()].iter()); *f = diff * idx; } // The window needs to be aligned to the diagonal elements, // based on the block size let window_elems_to_skip = block.len() - ((diag.len() - 1) / 2); for (window, f) in prev .windows(diag.len()) .skip(window_elems_to_skip) .zip(fut.iter_mut().skip(block.len())) .take(nx - 2 * block.len()) { let diff = product_fast(diag.iter(), window.iter()); *f = diff * idx; } for (bl, f) in block.iter().zip(fut.iter_mut().rev()) { let diff = product_fast(bl.iter(), prev.iter().rev()); *f = idx * if symmetry == Symmetry::Symmetric { diff } else { -diff }; } } } } #[cfg(feature = "sparse")] pub(crate) fn sparse_from_block( block: &[&[Float]], diag: &[Float], symmetry: Symmetry, optype: OperatorType, n: usize, ) -> sprs::CsMat { assert!(n >= 2 * block.len()); let nnz = { let block_elems = block.iter().fold(0, |acc, x| { acc + x .iter() .fold(0, |acc, &x| if x != 0.0 { acc + 1 } else { acc }) }); let diag_elems = diag .iter() .fold(0, |acc, &x| if x != 0.0 { acc + 1 } else { acc }); 2 * block_elems + (n - 2 * block.len()) * diag_elems }; let mut mat = sprs::TriMat::with_capacity((n, n), nnz); let dx = if optype == OperatorType::H2 { 1.0 / (n - 2) as Float } else { 1.0 / (n - 1) as Float }; let idx = 1.0 / dx; for (j, bl) in block.iter().enumerate() { for (i, &b) in bl.iter().enumerate() { if b == 0.0 { continue; } mat.add_triplet(j, i, b * idx); } } for j in block.len()..n - block.len() { let half_diag_len = diag.len() / 2; for (&d, i) in diag.iter().zip(j - half_diag_len..) { if d == 0.0 { continue; } mat.add_triplet(j, i, d * idx); } } for (bl, j) in block.iter().zip((0..n).rev()).rev() { for (&b, i) in bl.iter().zip((0..n).rev()).rev() { if b == 0.0 { continue; } if symmetry == Symmetry::AntiSymmetric { mat.add_triplet(j, i, -b * idx); } else { mat.add_triplet(j, i, b * idx); } } } mat.to_csr() } #[cfg(feature = "sparse")] pub(crate) fn h_matrix(diag: &[Float], n: usize, is_h2: bool) -> sprs::CsMat { let h = if is_h2 { 1.0 / (n - 2) as Float } else { 1.0 / (n - 1) as Float }; let nmiddle = n - 2 * diag.len(); let iter = diag .iter() .chain(std::iter::repeat(&1.0).take(nmiddle)) .chain(diag.iter().rev()) .map(|&x| h * x); let mut mat = sprs::TriMat::with_capacity((n, n), n); for (i, d) in iter.enumerate() { mat.add_triplet(i, i, d); } mat.to_csr() }