Deterministic CPU multithreading: supernodal Cholesky, parallel elements, LBM blocks (#50)

* parallel: deterministic thread pool helpers for the solvers (fixed partitions, ordered results)

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NmAttHhUZTokgPeEJia8sm

* solver: supernodal left-looking Cholesky, multithreaded with a fixed operation order

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NmAttHhUZTokgPeEJia8sm

* solver: parallel element matrices, stresses, Lanczos block solves and products (sums in the sequential order)

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NmAttHhUZTokgPeEJia8sm

* explicit: element updates in parallel, nodal forces added in element order (bit-identical to the sequential loop)

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NmAttHhUZTokgPeEJia8sm

* lbm: collision and streaming by fixed cell blocks in parallel, wall forces in link order (bit-identical)

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NmAttHhUZTokgPeEJia8sm

* engine: threads setting for the solve commands (session default from MODELCRAFT_THREADS or the cores); bit-identity test on 1, 2 and 7 threads

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NmAttHhUZTokgPeEJia8sm

* docs: rayon threads in ADR 0001, the parallel crate, supernodal Cholesky

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NmAttHhUZTokgPeEJia8sm

---------

Co-authored-by: jyviko <2501648+jyviko@users.noreply.github.com>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>

crates/solver/src/sparse.rs

@@ -11,6 +11,9 @@ use modelcraft_fem::{DofLayout, DofSet};
 
 use crate::{Error, Result};
 
+/// Rows per parallel block of a product.
+const ROWS: usize = 4096;
+
 /// A square sparse matrix in compressed rows with sorted column indices.
 #[derive(Debug, Clone, PartialEq)]
 pub struct Csr {
@@ -28,11 +31,15 @@ impl Csr {
     }
 
     /// y = A x.
+    /// Rows are computed in parallel blocks; each row's sum runs in column order.
     pub fn mul(&self, x: &[f64], y: &mut [f64]) {
-        for (r, yr) in y.iter_mut().enumerate().take(self.n) {
-            let (cols, vals) = self.row(r);
-            *yr = cols.iter().zip(vals).map(|(c, v)| v * x.get(*c).copied().unwrap_or(0.0)).sum();
-        }
+        let n = self.n.min(y.len());
+        modelcraft_parallel::chunks_mut(y.get_mut(..n).unwrap_or_default(), ROWS, |b, block| {
+            for (i, yr) in block.iter_mut().enumerate() {
+                let (cols, vals) = self.row(b * ROWS + i);
+                *yr = cols.iter().zip(vals).map(|(c, v)| v * x.get(*c).copied().unwrap_or(0.0)).sum();
+            }
+        });
     }
 
     pub fn diagonal(&self) -> Vec<f64> {