Transactional memory

About: Transactional memory is a research topic. Over the lifetime, 2365 publications have been published within this topic receiving 60818 citations.

Relativistic red-black trees

Abstract: This paper presents algorithms for concurrently reading and modifying a red-black tree RBTree. The algorithms allow wait-free, linearly scalable lookups in the presence of concurrent inserts and deletes. They have deterministic response times for a given tree size and uncontended read performance that is at least 60% faster than other known approaches. The techniques used to derive these algorithms arise from a concurrent programming methodology called relativistic programming. Relativistic programming introduces write-side delay primitives that allow the writer to pay most of the cost of synchronization between readers and writers. Only minimal synchronization overhead is placed on readers. Relativistic programming avoids unnecessarily strict ordering of read and write operations while still providing the capability to enforce linearizability. This paper shows how relativistic programming can be used to build a concurrent RBTree with synchronization-free readers and both lock-based and transactional memory-based writers. Copyright © 2013 John Wiley & Sons, Ltd.

From causal to z-linearizable transactional memory

Abstract: The current generation of time-based transactional memories (TMs) has the advantage of being simple and efficient, and providing strong linearizability semantics. Linearizability matches well the goal of TM to simplify the design and implementation of concurrent applications. However, long transactions can have a much lower likelihood of committing than smaller transactions because of the strict ordering constraints imposed by linearizability. We investigate the use of weaker semantics for TM and introduce a new consistency criterion that we call z-linearizability. By combining properties of linearizability and serializability, z-linearizability provides a good trade-off between strong semantics and good practical performance even for long transactions.

Distributed transactional memory for metric-space networks

Abstract: Transactional Memory is a concurrent programming API in which concurrent threads synchronize via transactions (instead of locks). Although this model has mostly been studied in the context of multiprocessors, it has attractive features for distributed systems as well. In this paper, we consider the problem of implementing transactional memory in a network of nodes where communication costs form a metric. The heart of our design is a new cache-coherence protocol, called the Ballistic protocol, for tracking and moving up-to-date copies of cached objects. For constant-doubling metrics, a broad class encompassing both Euclidean spaces and growth-restricted networks, this protocol has stretch logarithmic in the diameter of the network.

Unifying thread-level speculation and transactional memory

Abstract: The motivation of this work is to ask whether Transactional Memory (TM) and Thread-Level Speculation (TLS), two prominent concurrency paradigms usually considered separately, can be combined into a hybrid approach that extracts untapped parallelism and speed-up from common programs. We show that the answer is positive by describing an algorithm, called TLSTM, that leverages an existing TM with TLS capabilities. We also show that our approach is able to achieve up to a 48% increase in throughput over the base TM, on read dominated workloads of long transactions in a multi-threaded application, among other results.