Help-Optimal and Language-Portable Lock-Free Concurrent Data Structures
Paper in proceedings, 2016

Helping is a widely used technique to guarantee lock-freedom in many concurrent data structures. An optimized helping strategy improves the overall performance of a lock-free algorithm. In this paper, we propose help-optimality, which essentially implies that no operation step is accounted for exclusive helping in the lock-free synchronization of concurrent operations. To describe the concept, we revisit the designs of a lock-free linked-list and a lock-free binary search tree and present improved algorithms. Our algorithms employ atomic single-word compare-and-swap (CAS) primitives and are linearizable. We design the algorithms without using any language/platformspecific mechanism. Specifically, we use neither bit-stealing froma pointer nor runtime type introspection of objects. Thus, our algorithms are language-portable. Further, to optimize the amortized number of steps per operation, if a CAS execution tomodify a shared pointer fails, we obtain a fresh set of thread-local variables without restarting an operation from scratch. We use several micro-benchmarks in both C/C++ and Java to validate the efficiency of our algorithms against existing state-of-the-art. The experiments show that the algorithms are scalable. Our implementations perform on a par with highly optimizedones and in many cases yield 10%-50% higher throughput.

Help

Language-portable

Concurrent data structure

Lock-free

Linearizability

Binary search tree

Help-optimal

Linked-list

Author

Bapi Chatterjee

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Ivan Walulya

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Philippas Tsigas

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

45th International Conference on Parallel Processing (ICPP), 2016

0190-3918 (ISSN)

Vol. 2016 september 360-369

Subject Categories

Computer and Information Science

DOI

10.1109/ICPP.2016.48

ISBN

978-150902823-8

More information

Created

10/7/2017