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Ethereum: Multi-Core Bitcoin Node Sync
I sync my node across 32 CPUs and it’s very slow.
Of course, syncing is not parallel. I wonder if there is a fundamental barrier to using the divide and conquer method.
Let’s say I need to sync a large blockchain, say 100MB or more. If I were to use the traditional method and sync all nodes at once, it would take an absurd amount of time – probably even days or weeks.
But what if I could break this task down into smaller parts? For example, I could create multiple processes to quickly sync some nodes while others run alone.
Some people have implemented this approach in exactly this way by using the divide and conquer method. Here’s a sketch of what that might look like:
- Get a piece of data: Take a portion of the blockchain and sync it to a single node.
- Create a new process: Start a new process that starts syncing that smaller piece of data.
- Use multiple cores
: Use as many CPU cores as possible to make progress on this new quest.
- Move fragments: Periodically move fragments of data from the old process’s area of interest back to a node with less load so the new process can work with them.
This approach allows nodes to stay in sync at their own pace without having to wait for everyone else to catch up. However, there are some fundamental obstacles that make this method difficult:
- Interprocess communication: Communication between processes can be difficult, especially when processing large amounts of data.
- Resource management: Coordinating the allocation and use of resources (e.g. CPU cores) is important but can be difficult to manage effectively.
- Global consensus
: Ensuring that all nodes have agreed on the latest data and the synchronization process requires a certain level of coordination that can be difficult to achieve.
Despite these challenges, some experienced developers are experimenting with this divide-and-conquer approach. For example:
- Binance Smart Chain: Binance uses a similar method by splitting the blockchain into smaller pieces and processing them in parallel.
- Polygon: Polygon is another project that has implemented a divide-and-conquer synchronization strategy that uses multiple processes to quickly spin up a few nodes.
While this approach may not be suitable for all use cases, it is an interesting example of looking for alternative ways to make synchronization more efficient and scalable.