Abstract:
In the recent past, devising algorithms for concurrent data structures has been driven by the need for scalability. Further,
there is an increased traction across the industry towards power efficient concurrent data structure designs. In this context, we
introduce a scalable and energy-efficient concurrent binary search tree with fatnodes (namely, FatCBST), and present algorithms to
perform basic operations on it. Unlike a single node with one value, a fatnode consists of a set of values. FatCBST minimizes structural
changes while performing update operations on the tree. In addition, fatnodes help to exploit the spatial locality in the cache hierarchy
and also reduce the height of the tree. FatCBST allows multiple threads to perform update operations on an existing fatnode
simultaneously. Experimental results show that for low contention workloads as well as large set sizes, FatCBST scales well and also
provides high performance-per-watt values as compared to the state-of-the-art implementations. For high contention workloads with
small set sizes, FatCBST suffers from contention.
