Narwhal and Bullshark, Sui's Mempool and Consensus Engines
This is a brief introduction to Narwhal and Bullshark, the high-throughput mempool and consensus engines offered by Mysten Labs. Sui uses Narwhal as the mempool and Bullshark as the consensus engine by default, to sequence transactions that require a total ordering, synchronize transactions between validators and periodically checkpoint the network's state.
The names highlight that the components split the responsibilities of:
- ensuring the availability of data submitted to consensus = Narwhal
- agreeing on a specific ordering of this data = Bullshark
The Sui Consensus Engine represents the latest variant of decades of work on multi-proposer, high-throughput consensus algorithms that reach throughputs of more than 125,000 transactions per second with a two-second latency for a deployment of 50 parties, with production cryptography, permanent storage, and a scaled-out primary-worker architecture.
The Sui Consensus Engine approach can offer dramatic scalability benefits in the following cases:
- a blockchain that has experimented with larger and larger blocks and has measured runaway latencies before the execution phase
- a blockchain with fast execution (e.g., focused on transactions or with an UTXO data model), but which mempool and consensus do not keep up
The Narwhal mempool offers:
- a high-throughput data availability engine, with cryptographic proofs of data availability at a primary node
- a structured graph data structure for traversing this information
- a scaled architecture, splitting the disk I/O and networking requirements across several workers
The consensus component offers a zero-message overhead consensus algorithm, leveraging graph traversals.
A Narwhal instance sets up a message-passing system comprised of a set of $3f+1$ units of stake divided amongst a set of nodes, and assumes a computationally bounded adversary that controls the network and can corrupt parties holding up to f units of stake. The validators collaborate in forming a leaderless graph of batches of transactions - which the literature (in the context of DAG-based consensus) designates as blocks and that Sui labels collections - to emphasize that this happens in a context where the mempool data is used by an unspecified consensus algorithm.
The graph's vertices consist of certified collections. Each valid collection signed by its validator-author must contain a round number and must itself be signed by a quorum (2f+1) of validator stake. These 2f+1 signatures are called a certificate of availability. Furthermore, that collection must contain hash pointers to a quorum of valid certificates (that is, certificates from validators with 2f + 1 units of stake) from the previous round (see Danezis & al. Fig 2), which constitute the edges of the graph.
Each collection is formed in the following way: each validator reliably broadcasts a collection for each round. Subject to specified validity conditions, if validators with 2f + 1 stake receive a collection, they acknowledge it with a signature each. Signatures from 2f + 1 validators by stake form a certificate of availability that is then shared and potentially included in collections at round r + 1.
The following figure represents five rounds of construction of such a DAG (1 to 5), with authorities A, B, C and D participating. For simplicity, each validator holds 1 unit of stake. The collections transitively acknowledged by A's latest round in A5 are represented in full lines in the graph.
How it works
- The graph construction allows inserting more transactions in the system at each authority and at each round.
- The certificates prove the data availability of each collection, or block, at each round.
- Their contents constitute a DAG that can be traversed identically at each honest node.
Narwhal is implemented using Tokio, RocksDB and generic cryptography implemented in fastcrypto.
To conduct a fresh deployment of Sui Consensus Engine, follow the instructions at Running Benchmarks.
Narwhal and Tusk (Danezis et al. 2021) is a consensus system leveraging directed acyclic graphs (DAG). DAG-based consensus has been developed over the last 30 years, and some of the history is summarized in (Wang & al. 2020). The closest theoretical ancestor of Narwhal & Tusk is DAG-Rider (Keidar & al. 2021).
Narwhal & Tusk are developed in the asynchronous model. A partially synchronous variant of Narwhal and Tusk, called Bullshark, is presented in (Giridharan 2022).
Narwhal and Tusk started as a research prototype at Facebook Novi.
Bullshark: DAG BFT Protocols Made Practical - Bullshark replaces Tusk for even greater performance.
Bullshark: The Partially Synchronous Version - A simplified version of Bullshark that is used in Sui today.
DAG Meets BFT - The Next Generation of BFT Consensus - Explains the evolution of the consensus protocol used by Sui.
- Danezis, G., Kogias, E. K., Sonnino, A., & Spiegelman, A. (2021). Narwhal and Tusk: A DAG-based Mempool and Efficient BFT Consensus. ArXiv:2105.11827 [Cs]. http://arxiv.org/abs/2105.11827
- Giridharan, N., Kokoris-Kogias, L., Sonnino, A., & Spiegelman, A. (2022). Bullshark: DAG BFT Protocols Made Practical. ArXiv:2201.05677 [Cs]. http://arxiv.org/abs/2201.05677
- Spiegelman, A., Giridharan, N., Sonnino, A., & Kokoris-Kogias, L. (2022). Bullshark: The Partially Synchronous Version. ArXiv:2209.05633 [Cs]. https://arxiv.org/abs/2209.05633
- Keidar, I., Kokoris-Kogias, E., Naor, O., & Spiegelman, A. (2021). All You Need is DAG. ArXiv:2102.08325 [Cs]. http://arxiv.org/abs/2102.08325
- Wang, Q., Yu, J., Chen, S., & Xiang, Y. (2020). SoK: Diving into DAG-based Blockchain Systems. ArXiv:2012.06128 [Cs]. http://arxiv.org/abs/2012.06128