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kernel/ksupport: add linalg functions

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abdul124 2024-08-01 17:51:05 +08:00
parent c04b0797e0
commit 4e37ac4690
2 changed files with 452 additions and 0 deletions
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12
artiq/firmware/ksupport/api.rs
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@ -117,6 +117,18 @@ static mut API: &'static [(&'static str, *const ())] = &[
api!(y1),
api!(yn),
// linalg
api!(np_linalg_cholesky = ::linalg::np_linalg_cholesky),
api!(np_linalg_qr = ::linalg::np_linalg_qr),
api!(np_linalg_svd = ::linalg::np_linalg_svd),
api!(np_linalg_inv = ::linalg::np_linalg_inv),
api!(np_linalg_pinv = ::linalg::np_linalg_pinv),
api!(np_linalg_matrix_power = ::linalg::np_linalg_matrix_power),
api!(np_linalg_det = ::linalg::np_linalg_det),
api!(sp_linalg_lu = ::linalg::sp_linalg_lu),
api!(sp_linalg_schur = ::linalg::sp_linalg_schur),
api!(sp_linalg_hessenberg = ::linalg::sp_linalg_hessenberg),
/* exceptions */
api!(_Unwind_Resume = ::unwind::_Unwind_Resume),
api!(__nac3_personality = ::eh_artiq::personality),

440
artiq/firmware/ksupport/linalg.rs Normal file
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@ -0,0 +1,440 @@
// Uses `nalgebra` crate to invoke `np_linalg` and `sp_linalg` functions
// When converting between `nalgebra::Matrix` and `NDArray` following considerations are necessary
//
// * Both `nalgebra::Matrix` and `NDArray` require their content to be stored in row-major order
// * `NDArray` data pointer can be directly read and converted to `nalgebra::Matrix` (row and column number must be known)
// * `nalgebra::Matrix::as_slice` returns the content of matrix in column-major order and initial data needs to be transposed before storing it in `NDArray` data pointer
use alloc::vec::Vec;
use core::slice;
use nalgebra::DMatrix;
use crate::artiq_raise;
pub struct InputMatrix {
pub ndims: usize,
pub dims: *const usize,
pub data: *mut f64,
}
impl InputMatrix {
fn get_dims(&mut self) -> Vec<usize> {
let dims = unsafe { slice::from_raw_parts(self.dims, self.ndims) };
dims.to_vec()
}
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_cholesky(mat1: *mut InputMatrix, out: *mut InputMatrix) {
let mat1 = mat1.as_mut().unwrap();
let out = out.as_mut().unwrap();
if mat1.ndims != 2 {
artiq_raise!(
"ValueError",
"expected 2D Vector Input, but received {1}D input)",
0,
mat1.ndims as i64,
0
);
}
let dim1 = (*mat1).get_dims();
if dim1[0] != dim1[1] {
artiq_raise!(
"ValueError",
"last 2 dimensions of the array must be square: {1} != {2}",
0,
dim1[0] as i64,
dim1[1] as i64
);
}
let outdim = out.get_dims();
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let result = matrix1.cholesky();
match result {
Some(res) => {
out_slice.copy_from_slice(res.unpack().transpose().as_slice());
}
None => {
artiq_raise!("LinAlgError", "Matrix is not positive definite");
}
};
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_qr(mat1: *mut InputMatrix, out_q: *mut InputMatrix, out_r: *mut InputMatrix) {
let mat1 = mat1.as_mut().unwrap();
let out_q = out_q.as_mut().unwrap();
let out_r = out_r.as_mut().unwrap();
if mat1.ndims != 2 {
artiq_raise!(
"ValueError",
"expected 2D Vector Input, but received {1}D input)",
0,
mat1.ndims as i64,
0
);
}
let dim1 = (*mat1).get_dims();
let outq_dim = (*out_q).get_dims();
let outr_dim = (*out_r).get_dims();
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let out_q_slice = unsafe { slice::from_raw_parts_mut(out_q.data, outq_dim[0] * outq_dim[1]) };
let out_r_slice = unsafe { slice::from_raw_parts_mut(out_r.data, outr_dim[0] * outr_dim[1]) };
// Refer to https://github.com/dimforge/nalgebra/issues/735
let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let res = matrix1.qr();
let (q, r) = res.unpack();
// Uses different algo need to match numpy
out_q_slice.copy_from_slice(q.transpose().as_slice());
out_r_slice.copy_from_slice(r.transpose().as_slice());
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_svd(
mat1: *mut InputMatrix,
outu: *mut InputMatrix,
outs: *mut InputMatrix,
outvh: *mut InputMatrix,
) {
let mat1 = mat1.as_mut().unwrap();
let outu = outu.as_mut().unwrap();
let outs = outs.as_mut().unwrap();
let outvh = outvh.as_mut().unwrap();
if mat1.ndims != 2 {
artiq_raise!(
"ValueError",
"expected 2D Vector Input, but received {1}D input)",
0,
mat1.ndims as i64,
0
);
}
let dim1 = (*mat1).get_dims();
let outu_dim = (*outu).get_dims();
let outs_dim = (*outs).get_dims();
let outvh_dim = (*outvh).get_dims();
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let out_u_slice = unsafe { slice::from_raw_parts_mut(outu.data, outu_dim[0] * outu_dim[1]) };
let out_s_slice = unsafe { slice::from_raw_parts_mut(outs.data, outs_dim[0]) };
let out_vh_slice = unsafe { slice::from_raw_parts_mut(outvh.data, outvh_dim[0] * outvh_dim[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let result = matrix.svd(true, true);
out_u_slice.copy_from_slice(result.u.unwrap().transpose().as_slice());
out_s_slice.copy_from_slice(result.singular_values.as_slice());
out_vh_slice.copy_from_slice(result.v_t.unwrap().transpose().as_slice());
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_inv(mat1: *mut InputMatrix, out: *mut InputMatrix) {
let mat1 = mat1.as_mut().unwrap();
let out = out.as_mut().unwrap();
if mat1.ndims != 2 {
artiq_raise!(
"ValueError",
"expected 2D Vector Input, but received {1}D input)",
0,
mat1.ndims as i64,
0
);
}
let dim1 = (*mat1).get_dims();
if dim1[0] != dim1[1] {
artiq_raise!(
"ValueError",
"last 2 dimensions of the array must be square: {1} != {2}",
0,
dim1[0] as i64,
dim1[1] as i64
);
}
let outdim = out.get_dims();
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
if !matrix.is_invertible() {
artiq_raise!("LinAlgError", "no inverse for Singular Matrix");
}
let inv = matrix.try_inverse().unwrap();
out_slice.copy_from_slice(inv.transpose().as_slice());
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_pinv(mat1: *mut InputMatrix, out: *mut InputMatrix) {
let mat1 = mat1.as_mut().unwrap();
let out = out.as_mut().unwrap();
if mat1.ndims != 2 {
artiq_raise!(
"ValueError",
"expected 2D Vector Input, but received {1}D input)",
0,
mat1.ndims as i64,
0
);
}
let dim1 = (*mat1).get_dims();
let outdim = out.get_dims();
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let svd = matrix.svd(true, true);
let inv = svd.pseudo_inverse(1e-15);
match inv {
Ok(m) => {
out_slice.copy_from_slice(m.transpose().as_slice());
}
Err(_) => {
artiq_raise!("LinAlgError", "SVD computation does not converge");
}
}
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_matrix_power(mat1: *mut InputMatrix, mat2: *mut InputMatrix, out: *mut InputMatrix) {
let mat1 = mat1.as_mut().unwrap();
let mat2 = mat2.as_mut().unwrap();
let out = out.as_mut().unwrap();
if mat1.ndims != 2 {
artiq_raise!(
"ValueError",
"expected 2D Vector Input, but received {1}D input)",
0,
mat1.ndims as i64,
0
);
}
let dim1 = (*mat1).get_dims();
let power = unsafe { slice::from_raw_parts_mut(mat2.data, 1) };
let power = power[0];
let outdim = out.get_dims();
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let mut abs_power = power;
if abs_power < 0.0 {
abs_power = abs_power * -1.0;
}
let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
if !matrix1.is_square() {
artiq_raise!(
"ValueError",
"last 2 dimensions of the array must be square: {1} != {2}",
0,
dim1[0] as i64,
dim1[1] as i64
);
}
let mut result = matrix1.pow(abs_power as u32);
if power < 0.0 {
if !matrix1.is_invertible() {
artiq_raise!("LinAlgError", "no inverse for Singular Matrix");
}
result = result.try_inverse().unwrap();
}
out_slice.copy_from_slice(result.transpose().as_slice());
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_det(mat1: *mut InputMatrix, out: *mut InputMatrix) {
let mat1 = mat1.as_mut().unwrap();
let out = out.as_mut().unwrap();
if mat1.ndims != 2 {
artiq_raise!(
"ValueError",
"expected 2D Vector Input, but received {1}D input)",
0,
mat1.ndims as i64,
0
);
}
let dim1 = (*mat1).get_dims();
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, 1) };
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
if !matrix.is_square() {
artiq_raise!(
"ValueError",
"last 2 dimensions of the array must be square: {1} != {2}",
0,
dim1[0] as i64,
dim1[1] as i64
);
}
out_slice[0] = matrix.determinant();
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn sp_linalg_lu(mat1: *mut InputMatrix, out_l: *mut InputMatrix, out_u: *mut InputMatrix) {
let mat1 = mat1.as_mut().unwrap();
let out_l = out_l.as_mut().unwrap();
let out_u = out_u.as_mut().unwrap();
if mat1.ndims != 2 {
artiq_raise!(
"ValueError",
"expected 2D Vector Input, but received {1}D input)",
0,
mat1.ndims as i64,
0
);
}
let dim1 = (*mat1).get_dims();
let outl_dim = (*out_l).get_dims();
let outu_dim = (*out_u).get_dims();
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let out_l_slice = unsafe { slice::from_raw_parts_mut(out_l.data, outl_dim[0] * outl_dim[1]) };
let out_u_slice = unsafe { slice::from_raw_parts_mut(out_u.data, outu_dim[0] * outu_dim[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let (_, l, u) = matrix.lu().unpack();
out_l_slice.copy_from_slice(l.transpose().as_slice());
out_u_slice.copy_from_slice(u.transpose().as_slice());
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn sp_linalg_schur(mat1: *mut InputMatrix, out_t: *mut InputMatrix, out_z: *mut InputMatrix) {
let mat1 = mat1.as_mut().unwrap();
let out_t = out_t.as_mut().unwrap();
let out_z = out_z.as_mut().unwrap();
if mat1.ndims != 2 {
artiq_raise!(
"ValueError",
"expected 2D Vector Input, but received {1}D input)",
0,
mat1.ndims as i64,
0
);
}
let dim1 = (*mat1).get_dims();
if dim1[0] != dim1[1] {
artiq_raise!(
"ValueError",
"last 2 dimensions of the array must be square: {1} != {2}",
0,
dim1[0] as i64,
dim1[1] as i64
);
}
let out_t_dim = (*out_t).get_dims();
let out_z_dim = (*out_z).get_dims();
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let out_t_slice = unsafe { slice::from_raw_parts_mut(out_t.data, out_t_dim[0] * out_t_dim[1]) };
let out_z_slice = unsafe { slice::from_raw_parts_mut(out_z.data, out_z_dim[0] * out_z_dim[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let (z, t) = matrix.schur().unpack();
out_t_slice.copy_from_slice(t.transpose().as_slice());
out_z_slice.copy_from_slice(z.transpose().as_slice());
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn sp_linalg_hessenberg(
mat1: *mut InputMatrix,
out_h: *mut InputMatrix,
out_q: *mut InputMatrix,
) {
let mat1 = mat1.as_mut().unwrap();
let out_h = out_h.as_mut().unwrap();
let out_q = out_q.as_mut().unwrap();
if mat1.ndims != 2 {
artiq_raise!(
"ValueError",
"expected 2D Vector Input, but received {1}D input)",
0,
mat1.ndims as i64,
0
);
}
let dim1 = (*mat1).get_dims();
if dim1[0] != dim1[1] {
artiq_raise!(
"ValueError",
"last 2 dimensions of the array must be square: {1} != {2}",
0,
dim1[0] as i64,
dim1[1] as i64
);
}
let out_h_dim = (*out_h).get_dims();
let out_q_dim = (*out_q).get_dims();
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let out_h_slice = unsafe { slice::from_raw_parts_mut(out_h.data, out_h_dim[0] * out_h_dim[1]) };
let out_q_slice = unsafe { slice::from_raw_parts_mut(out_q.data, out_q_dim[0] * out_q_dim[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let (q, h) = matrix.hessenberg().unpack();
out_h_slice.copy_from_slice(h.transpose().as_slice());
out_q_slice.copy_from_slice(q.transpose().as_slice());
}