narwhal

KO | EN

gitlite — search

#ai #typescript #llm #go #golang #linux #docker #awesome #vue #pytorch #security #openai #ios #open-source

(★ 221)

Narwhal and Tusk: A DAG-based Mempool and Efficient BFT Consensus.

narwhal 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Narwhal and Tusk

[![build status](https://img.shields.io/github/workflow/status/asonnino/narwhal/Rust/master?style=flat-square&logo=github)](https://github.com/asonnino/narwhal/actions)
[![rustc](https://img.shields.io/badge/rustc-1.51+-blue?style=flat-square&logo=rust)](https://www.rust-lang.org)
[![license](https://img.shields.io/badge/license-Apache-blue.svg?style=flat-square)](https://raw.githubusercontent.com/facebookresearch/narwhal/main/LICENSE)

This repo provides an implementation of [Narwhal and Tusk](https://arxiv.org/pdf/2105.11827.pdf). The codebase has been designed to be small, efficient, and easy to benchmark and modify. It has not been designed to run in production but uses real cryptography ([dalek](https://doc.dalek.rs/ed25519_dalek)), networking ([tokio](https://docs.rs/tokio)), and storage ([rocksdb](https://docs.rs/rocksdb)).

## Quick Start
The core protocols are written in Rust, but all benchmarking scripts are written in Python and run with [Fabric](http://www.fabfile.org/).
To deploy and benchmark a testbed of 4 nodes on your local machine, clone the repo and install the python dependencies:
```
$ git clone https://github.com/asonnino/narwhal.git
$ cd narwhal/benchmark
$ pip install -r requirements.txt
```
You also need to install Clang (required by rocksdb) and [tmux](https://linuxize.com/post/getting-started-with-tmux/#installing-tmux) (which runs all nodes and clients in the background). Finally, run a local benchmark using fabric:
```
$ fab local
```
This command may take a long time the first time you run it (compiling rust code in `release` mode may be slow) and you can customize a number of benchmark parameters in `fabfile.py`. When the benchmark terminates, it displays a summary of the execution similarly to the one below.
```
-----------------------------------------
 SUMMARY:
-----------------------------------------
 + CONFIG:
 Faults: 0 node(s)
 Committee size: 4 node(s)
 Worker(s) per node: 1 worker(s)
 Collocate primary and workers: True
 Input rate: 50,000 tx/s
 Transaction size: 512 B
 Execution time: 19 s

Header size: 1,000 B
 Max header delay: 100 ms
 GC depth: 50 round(s)
 Sync retry delay: 10,000 ms
 Sync retry nodes: 3 node(s)
 batch size: 500,000 B
 Max batch delay: 100 ms

+ RESULTS:
 Consensus TPS: 46,478 tx/s
 Consensus BPS: 23,796,531 B/s
 Consensus latency: 464 ms

End-to-end TPS: 46,149 tx/s
 End-to-end BPS: 23,628,541 B/s
 End-to-end latency: 557 ms
-----------------------------------------
```

## Next Steps
The next step is to read the paper [Narwhal and Tusk: A DAG-based Mempool and Efficient BFT Consensus](https://arxiv.org/pdf/2105.11827.pdf). It is then recommended to have a look at the README files of the [worker](https://github.com/asonnino/narwhal/tree/master/worker) and [primary](https://github.com/asonnino/narwhal/tree/master/primary) crates. An additional resource to better understand the Tusk consensus protocol is the paper [All You Need is DAG](https://arxiv.org/abs/2102.08325) as it describes a similar protocol.

The README file of the [benchmark folder](https://github.com/asonnino/narwhal/tree/master/benchmark) explains how to benchmark the codebase and read benchmarks' results. It also provides a step-by-step tutorial to run benchmarks on [Amazon Web Services (AWS)](https://aws.amazon.com) accross multiple data centers (WAN).

## License
This software is licensed as [Apache 2.0](LICENSE).

narwhal

narwhal 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

narwhal

narwhal 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README