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Hash tries are a trie-based data structure with nearly ideal characteristics for the implementation of hash maps. Starting from a particular lock-free hash map data structure, named Lock-Free Hash Tries, we focus on solving the problem of memory reclamation without losing the lock-freedom property. To the best of our knowledge, outside garbage collected environments, there is no current implementation of hash maps that is able to reclaim memory in a lock-free manner. To achieve this goal, we propose an approach for memory reclamation specific to Lock-Free Hash Tries that explores the characteristics of its structure in order to achieve efficient memory reclamation with low and well-defined memory bounds. We present and discuss in detail the key algorithms required to easily reproduce our implementation by others. Experimental results show that our approach obtains better results when compared with other state-of-the-art memory reclamation methods and provides a competitive and scalable hash map implementation, if compared to lock-based implementations.

Hash tries are a trie-based data structure with nearly ideal characteristics for the implementation of hash maps. In this paper, we present a novel, simple and scalable hash trie map design that fully supports the concurrent search, insert and remove operations on hash maps. To the best of our knowledge, our proposal is the first that puts together the following characteristics: (i) be lock-free; (ii) use fixed size data structures; and (iii) maintain the access to all internal data structures as persistent memory references. Our design is modular enough to allow different types of configurations aimed for different performances in memory usage and execution time and can be easily implemented in any type of language, library or within other complex data structures. We discuss in detail the key algorithms required to easily reproduce our implementation by others and we present a proof of correctness showing that our proposal is linearizable and lock-free for the search, insert and remove operations. Experimental results show that our proposal is quite competitive when compared against other state-of-the-art proposals implemented in Java.

The literature describes two high performance concurrent stack algorithms based on combining funnels and elimination trees. Unfortunately, the funnels are linearizable but blocking, and the elimination trees are non-blocking but not linearizable. Neither is used in practice since they perform well only at exceptionally high loads. The literature also describes a simple lock-free linearizable stack algorithm that works at low loads but does not scale as the load increases. The question of designing a stack algorithm that is non-blocking, linearizable, and scales well throughout the concurrency range, has thus remained open. This paper presents such a concurrent stack algorithm. It is based on the following simple observation: that a single elimination array used as a backoff scheme for a simple lock-free stack is lock-free, linearizable, and scalable. As our empirical results show, the resulting elimination-backoff stack performs as well as the simple stack at low loads, and increasingly outperforms all other methods (lock-based and non-blocking) as concurrency increases. We believe its simplicity and scalability make it a viable practical alternative to existing constructions for implementing concurrent stacks.

We present a practical lock-free shared data structure that efficiently implements the operations of a concurrent deque as well as a general doubly linked list. The implementation supports parallelism for disjoint accesses and uses atomic primitives which are available in modern computer systems. Previously known lock-free algorithms of doubly linked lists are either based on non-available atomic synchronization primitives, only implement a subset of the functionality, or are not designed for disjoint accesses. Our algorithm only requires single-word compare-and-swap atomic primitives, supports fully dynamic list sizes, and allows traversal also through deleted nodes and thus avoids unnecessary operation retries. We have performed an empirical study of our new algorithm on two different multiprocessor platforms. Results of the experiments performed under high contention show that the performance of our implementation scales linearly with increasing number of processors. Considering deque implementations and systems with low concurrency, the algorithm by Michael shows the best performance. However, as our algorithm is designed for disjoint accesses, it performs significantly better on systems with high concurrency and non-uniform memory architecture.

Irregular parallel algorithms pose a significant challenge for achieving high performance because of the difficulty predicting memory access patterns or execution paths. Within an irregular application, fine-grained synchronization is one technique for managing the coordination of work; but in practice the actual performance for irregular problems depends on the input, the access pattern to shared data structures, the relative speed of processors, and the hardware support of synchronization primitives. In this paper, we focus on lock-free and mutual exclusion protocols for handling fine-grained synchronization. Mutual exclusion and lock-free protocols have received a fair amount of attention in coordinating accesses to shared data structures from concurrent processes. Mutual exclusion offers a simple programming abstraction, while lock-free data structures provide better fault tolerance and eliminate problems associated with critical sections such as priority inversion and deadlock. These synchronization protocols, however, are seldom used in parallel algorithm designs, especially for algorithms under the SPMD paradigm, as their implementations are highly hardware dependent and their costs are hard to characterize. Using graph-theoretic algorithms for illustrative purposes, we show experimental results on two shared-memory multiprocessors, the IBM pSeries 570 and the Sun Enterprise 4500, that irregular parallel algorithms with efficient fine-grained synchronization may yield good performance.

We consider the use of lock-free techniques for implementing shared objects in real-time Pfair-scheduled multiprocessor systems. Lock-free objects are more economical than locking techniques when implementing relatively simple objects such as buffers, stacks, queues, and lists. However, the use of such objects on real-time multiprocessors is generally considered impractical due to the need for analytical real-time guarantees. In this paper, we explain how the quantum-based nature of Pfair scheduling enables the effective use of such objects on real-time multiprocessors and present analysis specific to Pfair-scheduled systems. In addition, we show that analytical improvements can be obtained by using such objects in conjunction with group-based scheduling techniques. In this approach, a group of tasks is scheduled as a single entity (called a supertask in the Pfair literature). Such grouping prevents tasks from executing simultaneously, and hence from executing in parallel. Consequently, grouping tasks can improve the worst-case scenario with respect to object contention. Grouping also enables the use of less costly uniprocessor algorithms when all tasks sharing an object reside within the same group. We illustrate these optimizations with a case study that focuses on shared queues. Finally, we present and experimentally evaluate a simple heuristic for grouping tasks in order to reduce object contention. Though the analysis presented herein focuses specifically on Pfair-scheduled systems, the observations and techniques should be applicable to other quantum-scheduled systems as well.

We present an efficient and practical lock-free implementation of a concurrent priority queue that is suitable for both fully concurrent (large multi-processor) systems as well as pre-emptive (multi-process) systems. Many algorithms for concurrent priority queues are based on mutual exclusion. However, mutual exclusion causes blocking which has several drawbacks and degrades the overall performance of the system. Non-blocking algorithms avoid blocking, and several implementations have been proposed. Previously known non-blocking algorithms of priority queues did not perform well in practice because of their complexity, and they are often based on non-available atomic synchronization primitives. Our algorithm is based on the randomized sequential list structure called Skiplist, and a real-time extension of our algorithm is also described. In our performance evaluation we compare our algorithm with a well-representable set of earlier known implementations of priority queues. The experimental results clearly show that our lock-free implementation outperforms the other lock-based implementations in practical scenarios for 3 threads and more, both on fully concurrent as well as on pre-emptive systems.

Most multiprocessors are multiprogrammed to achieve acceptable response time and to increase their utilization. Unfortunately, inopportune preemption may significantly degrade the performance of synchronized parallel applications. To address this problem, researchers have developed two principal strategies for a concurrent, atomic update of shared data structures: (1)preemption-safe lockingand (2)nonblocking(lock-free)algorithms. Preemption-safe locking requires kernel support. Nonblocking algorithms generally require a universal atomic primitive such ascompare-and-swaporload-linked/store-conditionaland are widely regarded as inefficient. We evaluate the performance of preemption-safe lock-based and nonblocking implementations of important data structures?queues, stacks, heaps, and counters?including nonblocking and lock-based queue algorithms of our own, in microbenchmarks and real applications on a 12-processor SGI Challenge multiprocessor. Our results indicate that our nonblocking queue consistently outperforms the best known alternatives and that data-structure-specific nonblocking algorithms, which exist for queues, stacks, and counters, can work extremely well. Not only do they outperform preemption-safe lock-based algorithms on multiprogrammed machines, they also outperform ordinary locks on dedicated machines. At the same time, since general-purpose nonblocking techniques do not yet appear to be practical, preemption-safe locks remain the preferred alternative for complex data structures: they outperform conventional locks by significant margins on multiprogrammed systems.