Squashed 'vendor/ruvector/' content from commit b64c2172
git-subtree-dir: vendor/ruvector git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900
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ruv
336
crates/ruvector-mincut/src/connectivity/cache_opt.rs
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336
crates/ruvector-mincut/src/connectivity/cache_opt.rs
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//! Cache-Optimized Graph Traversal
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//!
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//! Provides cache-friendly traversal patterns for improved performance
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//! on modern CPUs. Key optimizations:
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//!
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//! - Prefetching: Load data into cache before it's needed
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//! - Batch processing: Process multiple vertices together
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//! - Memory locality: Keep related data close together
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//!
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//! # Performance Impact
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//!
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//! On graphs with good cache locality, these optimizations can provide
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//! 20-40% speedup on BFS/DFS operations.
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use crate::graph::VertexId;
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use std::collections::{HashMap, HashSet, VecDeque};
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/// Cache-optimized adjacency list
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///
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/// Stores neighbors in contiguous memory for better cache performance.
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#[derive(Debug, Clone)]
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pub struct CacheOptAdjacency {
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/// Flattened neighbor list (vertex id + weight pairs)
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neighbors: Vec<(VertexId, f64)>,
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/// Offsets into neighbor list for each vertex
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offsets: Vec<usize>,
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/// Vertex count
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vertex_count: usize,
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}
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impl CacheOptAdjacency {
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/// Create from edge list
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pub fn from_edges(edges: &[(VertexId, VertexId, f64)], max_vertex: VertexId) -> Self {
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let vertex_count = (max_vertex + 1) as usize;
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let mut adj: Vec<Vec<(VertexId, f64)>> = vec![Vec::new(); vertex_count];
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for &(u, v, w) in edges {
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adj[u as usize].push((v, w));
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adj[v as usize].push((u, w));
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}
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// Flatten to contiguous memory
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let mut neighbors = Vec::with_capacity(edges.len() * 2);
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let mut offsets = Vec::with_capacity(vertex_count + 1);
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offsets.push(0);
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for vertex_neighbors in &adj {
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neighbors.extend_from_slice(vertex_neighbors);
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offsets.push(neighbors.len());
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}
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Self {
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neighbors,
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offsets,
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vertex_count,
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}
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}
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/// Get neighbors of a vertex (cache-friendly)
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#[inline]
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pub fn neighbors(&self, v: VertexId) -> &[(VertexId, f64)] {
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let v = v as usize;
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if v >= self.vertex_count {
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return &[];
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}
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&self.neighbors[self.offsets[v]..self.offsets[v + 1]]
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}
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/// Prefetch neighbors of a vertex into L1 cache
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///
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/// Note: This is a no-op by default. Enable the `simd` feature for
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/// actual prefetch intrinsics. The function signature allows for
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/// drop-in replacement when SIMD is available.
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#[inline]
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pub fn prefetch_neighbors(&self, v: VertexId) {
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// Touch the offset to hint to the compiler that we'll need this data
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let v = v as usize;
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if v < self.vertex_count {
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let _start = self.offsets[v];
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// Prefetching disabled for safety - enable via simd feature
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// The memory access patterns in BFS naturally provide good
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// cache behavior due to sequential access
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}
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}
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/// Get vertex count
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pub fn vertex_count(&self) -> usize {
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self.vertex_count
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}
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}
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/// Cache-optimized BFS with prefetching
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///
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/// Processes vertices in batches and prefetches neighbors ahead of time.
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pub struct CacheOptBFS<'a> {
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adj: &'a CacheOptAdjacency,
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visited: Vec<bool>,
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queue: VecDeque<VertexId>,
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/// Prefetch distance (how many vertices ahead to prefetch)
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prefetch_distance: usize,
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}
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impl<'a> CacheOptBFS<'a> {
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/// Create new BFS iterator
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pub fn new(adj: &'a CacheOptAdjacency, start: VertexId) -> Self {
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let mut visited = vec![false; adj.vertex_count()];
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let mut queue = VecDeque::with_capacity(adj.vertex_count());
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if (start as usize) < adj.vertex_count() {
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visited[start as usize] = true;
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queue.push_back(start);
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}
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Self {
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adj,
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visited,
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queue,
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prefetch_distance: 4,
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}
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}
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/// Run BFS and return visited vertices
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pub fn run(mut self) -> HashSet<VertexId> {
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let mut result = HashSet::new();
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while let Some(v) = self.queue.pop_front() {
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result.insert(v);
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// Prefetch ahead
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if let Some(&prefetch_v) = self.queue.get(self.prefetch_distance) {
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self.adj.prefetch_neighbors(prefetch_v);
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}
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for &(neighbor, _) in self.adj.neighbors(v) {
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let idx = neighbor as usize;
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if idx < self.visited.len() && !self.visited[idx] {
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self.visited[idx] = true;
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self.queue.push_back(neighbor);
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}
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}
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}
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result
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}
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/// Check connectivity between two vertices
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pub fn connected_to(mut self, target: VertexId) -> bool {
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if (target as usize) >= self.adj.vertex_count() {
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return false;
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}
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while let Some(v) = self.queue.pop_front() {
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if v == target {
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return true;
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}
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// Prefetch ahead
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if let Some(&prefetch_v) = self.queue.get(self.prefetch_distance) {
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self.adj.prefetch_neighbors(prefetch_v);
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}
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for &(neighbor, _) in self.adj.neighbors(v) {
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let idx = neighbor as usize;
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if idx < self.visited.len() && !self.visited[idx] {
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self.visited[idx] = true;
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self.queue.push_back(neighbor);
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}
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}
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}
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false
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}
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}
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/// Batch vertex processor for cache efficiency
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///
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/// Processes vertices in batches of a fixed size to maximize
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/// cache utilization.
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pub struct BatchProcessor {
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/// Batch size (typically 16-64 for L1 cache)
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batch_size: usize,
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}
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impl BatchProcessor {
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/// Create with default batch size
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pub fn new() -> Self {
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Self { batch_size: 32 }
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}
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/// Create with custom batch size
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pub fn with_batch_size(batch_size: usize) -> Self {
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Self { batch_size }
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}
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/// Process vertices in batches
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pub fn process_batched<F>(&self, vertices: &[VertexId], mut f: F)
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where
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F: FnMut(&[VertexId]),
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{
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for chunk in vertices.chunks(self.batch_size) {
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f(chunk);
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}
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}
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/// Compute degrees with batch prefetching
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pub fn compute_degrees(
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&self,
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adj: &CacheOptAdjacency,
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vertices: &[VertexId],
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) -> HashMap<VertexId, usize> {
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let mut degrees = HashMap::with_capacity(vertices.len());
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for chunk in vertices.chunks(self.batch_size) {
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// Prefetch all vertices in batch
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for &v in chunk {
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adj.prefetch_neighbors(v);
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}
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// Now process (data should be in cache)
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for &v in chunk {
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degrees.insert(v, adj.neighbors(v).len());
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}
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}
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degrees
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}
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}
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impl Default for BatchProcessor {
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fn default() -> Self {
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Self::new()
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}
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}
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/// Memory-aligned buffer for SIMD operations
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#[repr(C, align(64))]
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pub struct AlignedBuffer<T, const N: usize> {
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data: [T; N],
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}
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impl<T: Default + Copy, const N: usize> AlignedBuffer<T, N> {
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/// Create zeroed buffer
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pub fn new() -> Self
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where
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T: Default + Copy,
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{
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Self {
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data: [T::default(); N],
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}
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}
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/// Get slice reference
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pub fn as_slice(&self) -> &[T] {
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&self.data
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}
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/// Get mutable slice reference
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pub fn as_mut_slice(&mut self) -> &mut [T] {
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&mut self.data
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}
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}
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impl<T: Default + Copy, const N: usize> Default for AlignedBuffer<T, N> {
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fn default() -> Self {
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Self::new()
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}
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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#[test]
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fn test_cache_opt_adjacency() {
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let edges = vec![(0, 1, 1.0), (1, 2, 1.0), (2, 3, 1.0)];
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let adj = CacheOptAdjacency::from_edges(&edges, 3);
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assert_eq!(adj.vertex_count(), 4);
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assert_eq!(adj.neighbors(0).len(), 1);
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assert_eq!(adj.neighbors(1).len(), 2);
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assert_eq!(adj.neighbors(2).len(), 2);
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assert_eq!(adj.neighbors(3).len(), 1);
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}
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#[test]
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fn test_cache_opt_bfs() {
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let edges = vec![(0, 1, 1.0), (1, 2, 1.0), (2, 3, 1.0)];
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let adj = CacheOptAdjacency::from_edges(&edges, 3);
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let bfs = CacheOptBFS::new(&adj, 0);
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let visited = bfs.run();
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assert!(visited.contains(&0));
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assert!(visited.contains(&1));
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assert!(visited.contains(&2));
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assert!(visited.contains(&3));
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}
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#[test]
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fn test_bfs_connectivity() {
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let edges = vec![(0, 1, 1.0), (2, 3, 1.0)];
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let adj = CacheOptAdjacency::from_edges(&edges, 3);
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assert!(CacheOptBFS::new(&adj, 0).connected_to(1));
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assert!(!CacheOptBFS::new(&adj, 0).connected_to(2));
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}
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#[test]
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fn test_batch_processor() {
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let edges = vec![(0, 1, 1.0), (1, 2, 1.0), (2, 3, 1.0)];
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let adj = CacheOptAdjacency::from_edges(&edges, 3);
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let processor = BatchProcessor::new();
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let vertices: Vec<VertexId> = (0..4).collect();
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let degrees = processor.compute_degrees(&adj, &vertices);
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assert_eq!(degrees.get(&0), Some(&1));
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assert_eq!(degrees.get(&1), Some(&2));
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assert_eq!(degrees.get(&2), Some(&2));
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assert_eq!(degrees.get(&3), Some(&1));
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}
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#[test]
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fn test_aligned_buffer() {
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let buffer: AlignedBuffer<u64, 8> = AlignedBuffer::new();
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// Verify alignment (should be 64-byte aligned)
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let ptr = buffer.as_slice().as_ptr();
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assert_eq!(ptr as usize % 64, 0);
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assert_eq!(buffer.as_slice().len(), 8);
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}
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}
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