Implementing and Improving Skiplists

Matt Hall discusses the implementation and performance of skiplists, a data structure that simplifies the complexities of balanced binary trees. Skiplists consist of multiple levels of linked lists, where each level contains a subset of the data from the level below, allowing for efficient searching similar to binary search trees. The author explains the process of inserting and retrieving values in a skiplist, emphasizing the use of a random number generator to determine the levels at which a new value should be inserted.

The implementation is demonstrated using Zig programming language, detailing the structure of nodes and the algorithms for descending to find insertion points and ascending to insert new values. Performance benchmarks indicate that the majority of time is spent in the descent operation, raising concerns about cache efficiency due to pointer chasing.

To improve performance, Hall suggests modifying the node structure to use a dynamic array of pointers instead of individual pointers for downward links. However, initial tests show that this change results in a 20% increase in wall time and memory usage, indicating that while the new structure may be more cache-friendly, it does not yield the expected performance benefits. The article concludes with a reflection on the challenges of optimizing data structures and the importance of careful benchmarking to assess performance improvements accurately.