Constructing Shared Objects That Are Both Robust and High-Throughput

Shared counters are among the most basic coordination structures in distributed computing. Known implementations of shared counters are either blocking, non-linearizable, or have a sequential bottleneck. We present the first counter algorithm that is both linearizable, nonblocking, and can provably achieve high throughput in semisynchronous executions. The algorithm is based on a novel variation of the software combining paradigm that we call bounded-wait combining. It can thus be used to obtain implementations, possessing the same properties, of any object that supports combinable operations, such as stack or queue. Unlike previous combining algorithms where processes may have to wait for each other indefinitely, in the bounded-wait combining algorithm a process only waits for other processes for a bounded period of time and then ‘takes destiny in its own hands'. In order to reason rigorously about the parallelism attainable by our algorithm, we define a novel metric for measuring the throughput of shared objects which we believe is interesting in its own right. We use this metric to prove that our algorithm can achieve throughput of Ω(N / logN) in executions where process speeds vary only by a constant factor, where N is the number of processes that can participate in the algorithm. We also introduce and use pseduo-transactions – a technique for concurrent execution that may prove useful for other algorithms.