grayfail

grayfail / echelon

Public

O(1) amortized priority queue based on an Adaptive Ladder Queue implementation.

crates.iocratesechelon datastructures queue
19
0
100% credibility
Found Apr 10, 2026 at 19 stars -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
Rust
AI Summary

Echelon is a Rust library offering an efficient priority queue for managing large-scale event scheduling in simulations and job systems.

How It Works

1
🔍 Discover Echelon

You hear about Echelon, a super-smart task organizer that instantly finds the next most urgent item from huge lists of scheduled events.

2
🛠️ Prepare your organizer

You set up Echelon in your project, ready to handle all your timed tasks like a dream.

3
✨ Add your events

You simply add tasks with their due times, and Echelon keeps everything perfectly tracked.

4
▶️ Process tasks

You start pulling out the earliest task each time, watching it work flawlessly.

5
⚡ Scale to millions

Even as your list grows to thousands or millions of events, it stays lightning-fast without slowing down.

🎉 Blazing-fast results

Your simulations or schedules run smoothly and super quick, saving you time and hassle.

Sign up to see the full architecture

4 more

Sign Up Free

Star Growth

See how this repo grew from 19 to 19 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is echelon?

Echelon is a Rust crate for an amortized O(1) priority queue tailored to heavy-tailed distributions like Pareto or log-normal timestamps. It tackles the slowdown of standard O(log n) heaps in large-scale discrete-event simulation, job scheduling, and network modeling, where skewed priorities make log n a real drag. Users get a `TimestampQueue` or generic `LadderQueue` with push/pop in amortized O(1) time complexity, plus iterators and drain methods for easy integration.

Why is it gaining traction?

It crushes BinaryHeap in benchmarks: 3.8x throughput on 1M holds, p50 latency flat at 41ns across sizes—visible amortized O(1) insertion and delete-min. Rust's Criterion suite pits it against heaps and maps on 8 distributions, proving wins on Pareto-heavy loads without custom tuning. For 5th-echelon github seekers chasing echelon 2025 performance, the adaptive auto-tuning hooks devs tired of heap sift-down spikes.

Who should use this?

Rust simulation engineers running discrete-event models with 100k+ events. Job queue maintainers handling skewed deadlines in schedulers. Network sim coders modeling packet bursts—anywhere heavy tails amplify O(log n) pain over uniform cases.

Verdict

Grab it for benchmarks if your queues scale big and skew hard; docs and tests are pro-level. But 19 stars and 1.0% credibility scream early alpha—vet in your workload before betting the farm.

(198 words)

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.