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kernel: add linalg functions #309

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sb10q merged 1 commits from abdul124/artiq-zynq:add_linalg_functions into master 2024-08-01 18:20:33 +08:00
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4 changed files with 531 additions and 167 deletions
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219
src/Cargo.lock generated
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@ -2,6 +2,15 @@
# It is not intended for manual editing.
version = 3
[[package]]
name = "approx"
version = "0.5.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "cab112f0a86d568ea0e627cc1d6be74a1e9cd55214684db5561995f6dad897c6"
dependencies = [
"num-traits",
]
[[package]]
name = "arrayvec"
version = "0.7.4"
@ -246,10 +255,10 @@ dependencies = [
"libsupport_zynq",
"log",
"log_buffer",
"nalgebra",
"nb 0.1.3",
"unwind",
"vcell",
"nalgebra",
"void",
]
@ -383,6 +392,19 @@ version = "0.7.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "c75de51135344a4f8ed3cfe2720dc27736f7711989703a0b43aadf3753c55577"
[[package]]
name = "nalgebra"
version = "0.32.6"
source = "git+https://git.m-labs.hk/M-labs/nalgebra?rev=dd00f9b#dd00f9b46046e0b931d1b470166db02fd29591be"
dependencies = [
"approx",
"num-complex",
"num-rational",
"num-traits",
"simba",
"typenum",
]
[[package]]
name = "nb"
version = "0.1.3"
@ -398,6 +420,15 @@ version = "1.0.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "546c37ac5d9e56f55e73b677106873d9d9f5190605e41a856503623648488cae"
[[package]]
name = "num-complex"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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dependencies = [
"num-traits",
]
[[package]]
name = "num-derive"
version = "0.3.3"
@ -409,6 +440,26 @@ dependencies = [
"syn",
]
[[package]]
name = "num-integer"
version = "0.1.46"
source = "registry+https://github.com/rust-lang/crates.io-index"
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dependencies = [
"num-traits",
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[[package]]
name = "num-rational"
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dependencies = [
"autocfg",
"num-integer",
"num-traits",
]
[[package]]
name = "num-traits"
version = "0.2.15"
@ -416,8 +467,15 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "578ede34cf02f8924ab9447f50c28075b4d3e5b269972345e7e0372b38c6cdcd"
dependencies = [
"autocfg",
"libm",
]
[[package]]
name = "paste"
version = "1.0.15"
source = "registry+https://github.com/rust-lang/crates.io-index"
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[[package]]
name = "pin-project-lite"
version = "0.2.9"
@ -524,6 +582,18 @@ version = "0.1.20"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "d4f410fedcf71af0345d7607d246e7ad15faaadd49d240ee3b24e5dc21a820ac"
[[package]]
name = "simba"
version = "0.8.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "50582927ed6f77e4ac020c057f37a268fc6aebc29225050365aacbb9deeeddc4"
dependencies = [
"approx",
"num-complex",
"num-traits",
"paste",
]
[[package]]
name = "smoltcp"
version = "0.7.5"
@ -556,6 +626,12 @@ dependencies = [
"log",
]
[[package]]
name = "typenum"
version = "1.17.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "42ff0bf0c66b8238c6f3b578df37d0b7848e55df8577b3f74f92a69acceeb825"
[[package]]
name = "unicode-ident"
version = "1.0.5"
@ -572,147 +648,6 @@ dependencies = [
"libc",
]
[[package]]
name = "nalgebra"
version = "0.32.6"
source = "git+https://git.m-labs.hk/M-labs/nalgebra?rev=dd00f9b#dd00f9b46046e0b931d1b470166db02fd29591be"
dependencies = [
"approx",
"matrixmultiply",
"nalgebra-macros",
"num-complex",
"num-rational",
"num-traits",
"simba",
"typenum",
]
[[package]]
name = "approx"
version = "0.5.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
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dependencies = [
"num-traits",
]
[[package]]
name = "matrixmultiply"
version = "0.3.8"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "7574c1cf36da4798ab73da5b215bbf444f50718207754cb522201d78d1cd0ff2"
dependencies = [
"autocfg",
"rawpointer",
]
[[package]]
name = "nalgebra-macros"
version = "0.2.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
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dependencies = [
"proc-macro2",
"quote",
"syn",
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dependencies = [
"num-bigint",
"num-integer",
"num-traits",
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"num-traits",
"paste",
"wide",
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dependencies = [
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"num-traits",
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name = "num-integer"
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dependencies = [
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features = ["no_std"]
dependencies = [
"bytemuck",
"safe_arch",
]
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name = "vcell"
version = "0.1.3"

38
src/libksupport/src/kernel/api.rs
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@ -1,16 +1,15 @@
use alloc::vec;
use core::{ffi::VaList, ptr, slice, str};
use core::{ffi::VaList, ptr, str};
use libc::{c_char, c_int, size_t};
use libm;
use log::{info, warn};
use nalgebra::{linalg, DMatrix};
#[cfg(has_drtio)]
use super::subkernel;
use super::{cache,
core1::rtio_get_destination_status,
dma,
dma, linalg,
rpc::{rpc_recv, rpc_send, rpc_send_async}};
use crate::{eh_artiq, i2c, rtio};
@ -39,26 +38,6 @@ unsafe extern "C" fn rtio_log(fmt: *const c_char, mut args: ...) {
rtio::write_log(buf.as_slice());
}
unsafe extern "C" fn linalg_try_invert_to(dim0: usize, dim1: usize, data: *mut f64) -> i8 {
let data_slice = unsafe { slice::from_raw_parts_mut(data, dim0 * dim1) };
let matrix = DMatrix::from_row_slice(dim0, dim1, data_slice);
let mut inverted_matrix = DMatrix::<f64>::zeros(dim0, dim1);
if linalg::try_invert_to(matrix, &mut inverted_matrix) {
data_slice.copy_from_slice(inverted_matrix.transpose().as_slice());
1
} else {
0
}
}
unsafe extern "C" fn linalg_wilkinson_shift(dim0: usize, dim1: usize, data: *mut f64) -> f64 {
let data_slice = slice::from_raw_parts_mut(data, dim0 * dim1);
let matrix = DMatrix::from_row_slice(dim0, dim1, data_slice);
linalg::wilkinson_shift(matrix[(0, 0)], matrix[(1, 1)], matrix[(0, 1)])
}
macro_rules! api {
($i:ident) => ({
extern { static $i: u8; }
@ -342,8 +321,17 @@ pub fn resolve(required: &[u8]) -> Option<u32> {
},
// linalg
api!(linalg_try_invert_to = linalg_try_invert_to),
api!(linalg_wilkinson_shift = linalg_wilkinson_shift),
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),
];
api.iter()
.find(|&&(exported, _)| exported.as_bytes() == required)

440
src/libksupport/src/kernel/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());
}

1
src/libksupport/src/kernel/mod.rs
View File

@ -13,6 +13,7 @@ mod dma;
mod rpc;
pub use dma::DmaRecorder;
mod cache;
mod linalg;
#[cfg(has_drtio)]
mod subkernel;