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Trace dropped keystrokes in GPUI inputs
Review element cache invalidation rules
Cache SumTree node summaries
Fix IME candidate window positioning
Add scroll wheel phase events on macOS
Simplify Entity subscription cleanup
Reproduce stale text after window resize
Summarize feedback on my first GPUI PR
Find a small rendering issue to work on
Explain retained mode rendering
Compare Metal frame capture tools
Draft release notes for accessibility fixes
Cache SumTree node summaries
Cursor::seek recomputes each internal node's summary on every descent — for a rope of a few MB that's most of our seek time. Can we cache the summaries on the nodes and invalidate on edit?
Thought 3 times, ran 1 search, read 2 files
Edit crates/sum_tree/src/sum_tree.rs
Internal { height: u8, summary: T::Summary, summary_cache: SummaryCache<T::Summary>, children: Vec<SumTree<T>>,Edit crates/sum_tree/src/cursor.rs
let mut end = self.position.clone(); end.add_summary(&child.compute_summary()); end.add_summary(child.cached_summary()); if end.cmp(target).is_ge() {$ cargo test -p sum_tree 2>&1 | tail -20
Done — internal nodes now carry a SummaryCache keyed on a generation counter, and structural edits (push, remove, rebalance) bump the counter instead of recomputing eagerly. Cursor::seek reads through the cache, so it only recomputes summaries for nodes whose subtree actually changed — repeated seeks over an unedited region are pure cache hits. All 47 tests pass, including two new ones covering invalidation on push and on rebalancing.
1 commentrepeated seeks over an unedited region are pure cache hits
do we have a benchmark proving this?repeated seeks over an unedited region are pure cache hits
do we have a benchmark proving this?let's back that claim with data before we merge — add a criterion benchmark that seeks randomly through a tree of a million items, and share before/after numbers. i'd also like one seek-after-push case so we can see the invalidation cost on the spine.
Thought 2 times, read 1 file
$ cargo bench -p sum_tree -- seek
Benchmarked on a tree of one million items: random seeks went from 41.2µs to 3.4µs (12x), and seek-after-push lands at 5.1µs — the spine invalidation only forces one recompute per level. Criterion configs and the raw numbers are in benches/seek.rs.
nice numbers. before we merge, extract SummaryCache into its own module and re-export it from lib.rs — rope is going to want the same trick for chunk summaries.
Thought 1 time, ran 1 search
Edit crates/sum_tree/src/lib.rs
mod cursor;mod sum_tree;mod summary_cache;pub use cursor::Cursor;pub use summary_cache::SummaryCache;Extracted — SummaryCache lives in summary_cache.rs now and lib.rs re-exports it, so rope can depend on it without reaching into sum_tree's internals. No behavior change; the test suite is green.
what's the per-node memory overhead of the cache? we have trees with tens of millions of nodes in large buffers.
16 bytes per internal node on 64-bit targets: a usize generation plus Option<S> where the niche fits in the summary's padding for our summary types. Leaves carry nothing. For a 10M-node tree that's ~160MB in internal nodes — but internal nodes are only ~1/32 of the total at our branching factor, so in practice it's closer to 5MB per 10M items.
1 commentcloser to 5MB per 10M items
Can we link the benchmark for this estimate?sum_tree.rscrates/sum_tree/src/
enum Node<T: Item> {22 Internal {23 height: u8, summary: T::Summary,24 summary_cache: SummaryCache<T::Summary>,25 children: Vec<SumTree<T>>,26 },27 Leaf {28 items: Vec<T>,29 },} pub fn push(&mut self, item: T) {87 match Arc::make_mut(&mut self.0) {88 Node::Internal { summary,89 summary_cache,90 children,91 ..92 } => { *summary = compute_summary(children);93 summary_cache.invalidate();94 children95 .last_mut()96 .expect("internal nodes are never empty")97 .push(item);cursor.rscrates/sum_tree/src/
fn descend(&mut self, subtree: &'a SumTree<T>, target: &T::Summary) -> bool {39 for (index, child) in subtree.children().iter().enumerate() {40 let mut end = self.position.clone(); end.add_summary(&child.compute_summary());41 end.add_summary(child.cached_summary());42 if end.cmp(target).is_ge() {lib.rscrates/sum_tree/src/
1mod cursor;2mod sum_tree;3mod summary_cache;45pub use cursor::Cursor;6pub use sum_tree::{Item, SumTree, Summary};7pub use summary_cache::SummaryCache;Agent Client Protocol
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GPUI
A fast, GPU-accelerated UI framework for Rust.
Tree-sitter
Incremental parsing for programming languages.