This repo provides an implementation of Narwhal and Tusk, a DAG-based mempool and efficient BFT consensus. The codebase has been designed to be small, efficient, and easy to benchmark and modify.

This repo uses fastcrypto as its cryptography library.

The core protocols are written in Rust, but all benchmarking scripts are written in Python and run with Fabric. To deploy and benchmark a testbed of four nodes on your local machine, clone the repo and install the python dependencies:

$ git clone https://github.com/mystenlabs/narwhal.git
$ cd narwhal/benchmark
$ pip install -r requirements.txt

You also need to install Clang (required by RocksDB) and 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
-----------------------------------------

The next step is to read the paper Narwhal and Tusk: A DAG-based Mempool and Efficient BFT Consensus. It is then recommended to have a look at the README files of the worker and primary crates. An additional resource to better understand the Tusk consensus protocol is the paper All You Need is DAG as it describes a similar protocol.

The README file of the benchmark folder 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) across multiple data centers (WAN).

This software is licensed as Apache 2.0.