How to linearize your cluster
Posted by Lagrang3
Feb 9, 2025/10:45 UTC
The discussion revolves around the implementation options available for the Goldberg-Tarjan maxflow/min-cut algorithm, specifically focusing on the preflow-push method. It highlights two main approaches to achieve this: using a dynamic tree data structure and employing a queue for processing active nodes in FIFO order. The use of a dynamic tree data structure is noted for achieving the fastest theoretical time complexity of (O(nm \log(n^2/m))), indicating its efficiency in handling large datasets or complex networks where the number of nodes (n) and edges (m) are significant.
On the other hand, the FIFO-preflow-push method, despite its relatively simpler implementation and higher time complexity of (O(n^3)), is presented as a viable alternative. This approach is particularly mentioned for its straightforwardness in coding, making it accessible for those who might prioritize ease of implementation over optimal performance. An example of such an implementation can be found in a provided GitHub link (example code), which serves as a practical resource for readers interested in applying the FIFO-preflow-push method in their projects.
The information encapsulates the trade-offs between computational efficiency and ease of implementation when choosing an approach for the preflow-push version of the Goldberg-Tarjan algorithm. While the dynamic tree structure offers the best theoretical performance, the FIFO method stands out for its simplicity and ease of coding, providing a valuable alternative for certain applications or for programmers with specific implementation preferences.
TLDR
Join Our Newsletter
We’ll email you summaries of the latest discussions from authoritative bitcoin sources, like bitcoin-dev, lightning-dev, and Delving Bitcoin.
Explore all Products
We'd love to hear your feedback on this project?
Give Feedback