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About 4,142 papers for “Concurrent data structure”

The Performance of Concurrent Data Structure Algorithms

Theodore Johnson, E. Shasha · 1994

This thesis develops a validated model of concurrent data structure algorithm performance, concentrating on concurrent B-trees. The thesis first develops two analytical tools, which are explained in the next two paragraphs, for the analysis. Yao showed that the space utilization of a B-tree built from random inserts is 69%. Assuming that nodes merge only when empty, we show that the utilization is 39% when the number of insert and delete operations is the same. However, if there are just 5% more inserts than deletes, then the utilization is at least 62%. In addition to the utilization, we calculate the probabilities of splitting and merging, important parameters for calculating concurrent B-tree algorithm performance. We compare merge-at-empty B-trees with merge-at-half B-trees. We conclude that merge-at-empty Btrees have a slightly lower space utilization but a much lower restructuring rate than merge-at-half B-trees, making merge-at-empty B-trees preferable for concurrent B-tree algo...

Cited by 0

Verifying weak memory concurrent data structure implementations

Henkes, Casper (author) · Research Repository (Delft University of Technology) · 2024

From formal hardware models to programming language implementations concurrency is everywhere. While there has been a lot of work done on verifying concurrent systems a large part of it is focused on SC. In practice, it is more common to encounter weak memory models for which the techniques developed for SC do not work. There exists previous research on verifying weak memory concurrent programs, however, this work is often limited in scope and is often difficult to understand and apply to a broader context. This thesis gives a general approach for calculating higher-level relations between function calls in a weak memory context that work for weak memory concurrent mutex, stack, and queue data structures. These relations allow us to abstract away implementation details for easier reasoning about program behaviour. These function-level relations and data structure models defined using them are implemented in a stateless model checker and used to verify several existing mutex, stack, and queue implementations.

Cited by 0Open access

Generating Concurrent Programs From Sequential Data Structure Knowledge

Sarat Chandra Varanasi, Neeraj Mittal, Gopal Gupta · arXiv (Cornell University) · 2020

In this paper we tackle the problem of automatically designing concurrent data structure operations given a sequential data structure specification and knowledge about concurrent behavior. Designing concurrent code is a non-trivial task even in simplest of cases. Humans often design concurrent data structure operations by transforming sequential versions into their respective concurrent versions. This requires an understanding of the data structure, its sequential behavior, thread interactions during concurrent execution and shared memory synchronization primitives. We mechanize this design process using automated commonsense reasoning. We assume that the data structure description is provided as axioms alongside the sequential code of its algebraic operations. This information is used to automatically derive concurrent code for that data structure, such as dictionary operations for linked lists and binary search trees. Knowledge in our case is expressed using Answer Set Programming (ASP), and we employ deduction, induction and abduction---just as humans do---in the reasoning involved. ASP allows for succinct modeling of first order theories of pointer data structures, run-time thread interactions and shared memory synchronization. Our reasoner can systematically make the same judgments as a human reasoner while constructing provably safe concurrent code. We present several reasoning challenges involved in transforming the sequential data structure into its equivalent concurrent version. All the reasoning tasks are encoded in ASP and our reasoner can make sound judgments to transform sequential code into concurrent code. To the best of our knowledge, our work is the first one to use commonsense reasoning to automatically transform sequential programs into concurrent code.

Cited by 0Open access

An Implementation of Concurrent Union-find Data Structure in Java

Yu Wang · 2006

Written in Java, DisjointSet implements an concurrent Union-Find data structure discussed in [1] using disjoint forests. Concurrency is implemented using threads in Java and is guaranteed calling lock and unlock methods before and after the critical sections. We call such data structure thread safe. To allow any object to be contained in the disjoint set, our implementation uses generics[2], which is represented by T. For testing, we use long integer type, Long for the disjoint set. Testing results from both serial code and concurrent code are compared. The Java code is to be compiled by Sun JDK 1.5.

Cited by 0

Efficient concurrent data structure access parallelism techniques for increasing scalability

Rukundo, Adones · Chalmers Research (Chalmers University of Technology) · 2023

Multi-core processors have revolutionised the way data structures are designed by bringing parallelism to mainstream computing. Key to exploiting hardware parallelism available in multi-core processors are concurrent data structures. However, some concurrent data structure abstractions are inherently sequential and incapable of harnessing the parallelism performance of multi-core processors. Designing and implementing concurrent data structures to harness hardware parallelism is challenging due to the requirement of correctness, efficiency and practicability under various application constraints. In this thesis, our research contribution is towards improving concurrent data structure access parallelism to increase data structure performance. We propose new design frameworks that improve access parallelism of already existing concurrent data structure designs. Also, we propose new concurrent data structure designs with significant performance improvements. To give an insight into the interplay between hardware and concurrent data structure access parallelism, we give a detailed analysis and model the performance scalability with varying parallelism.In the first part of the thesis, we focus on data structure semantic relaxation. By relaxing the semantics of a data structure, a bigger design space, that allows weaker synchronization and more useful parallelism, is unveiled. Investigating new data structure designs, capable of trading semantics for achieving better performance in a monotonic way, is a major challenge in the area. We algorithmically address this challenge in this part of the thesis. We present an efficient, lock-free, concurrent data structure design framework for out-of-order semantic relaxation. We introduce a new two-dimensional algorithmic design, that uses multiple instances of a given data structure to improve access parallelism. In the second part of the thesis, we propose an efficient priority queue that improves access parallelism by reducing the number of synchronization points for each operation. Priority queues are fundamental abstract data types, often used to manage limited resources in parallel systems. Typical proposed parallel priority queue implementations are based on heaps or skip lists. In recent literature, skip lists have been shown to be the most efficient design choice for implementing priority queues. Though numerous intricate implementations of skip list based queues have been proposed in the literature, their performance is constrained by the high number of global atomic updates per operation and the high memory consumption, which are proportional to the number of sub-lists in the queue. In this part of the thesis, we propose an alternative approach for designing lock-free linearizable priority queues, that significantly improve memory efficiency and throughput performance, by reducing the number of global atomic updates and memory consumption as compared to skip-list based queues. To achieve this, our new design combines two structures; a search tree and a linked list, forming what we call a Tree Search List Queue (TSLQueue). Subsequently, we analyse and introduce a model for lock-free concurrent data structure access parallelism. The major impediment to scaling concurrent data structures is memory contention when accessing shared data structure access points, leading to thread serialisation, and hindering parallelism. Aiming to address this challenge, a significant amount of work in the literature has proposed multi-access techniques that improve concurrent data structure parallelism. However, there is little work on analysing and modelling the execution behaviour of concurrent multi-access data structures especially in a shared memory setting. In this part of the thesis, we analyse and model the general execution behaviour of concurrent multi-access data structures in the shared memory setting. We study and analyse the behaviour of the two popular random access patterns: shared (Remote) and exclusive (Local) access, and the behaviour of the two most commonly used atomic primitives for designing lock-free data structures: Compare and Swap, and, Fetch and Add.

Cited by 0Open access

Relaxing Concurrent Data-structure Semantics for Increasing Performance: A Multi-structure 2D Design Framework

Adones Rukundo, Aras Atalar, Philippas Tsigas · arXiv (Cornell University) · 2019

There has been a significant amount of work in the literature proposing semantic relaxation of concurrent data structures for improving scalability and performance. By relaxing the semantics of a data structure, a bigger design space, that allows weaker synchronization and more useful parallelism, is unveiled. Investigating new data structure designs, capable of trading semantics for achieving better performance in a monotonic way, is a major challenge in the area. We algorithmically address this challenge in this paper.To address this challenge, we present an efficient lock-free, concurrent data structure design framework for out-of-order semantic relaxation. Our framework introduces a new two dimensional algorithmic design, that uses multiple instances of an implementation of the given data structure. The first dimension of our design is the number of data structure instances onto which operations are spread to, in order to achieve increased parallelism through disjoint memory accesses. The second dimension is the number of consecutive operations of a single thread that can stay at the same data structure instance in order to benefit from data locality. Our design can flexibly explore this two-dimensional space to achieve the property of monotonically increasing throughput performance via relaxing concurrent data structure semantics within a tight deterministic relaxation bound, as we prove in the paper. We show how our framework can instantiate lock-free out-of-order queues, stacks, counters and dequeues. The experimental evaluation shows that our two-dimensional data structures: i) significantly outperform the respected previous proposed ones with respect to scalability and throughput performance and ii) monotonically increase throughput as relaxation increases.

Cited by 0Open access

A tree clock data structure for causal orderings in concurrent executions

Umang Mathur, Andreas Pavlogiannis, Hünkar Can Tunç et al. · 2022

Dynamic techniques are a scalable and effective way to analyze concurrent programs. Instead of analyzing all behaviors of a program, these techniques detect errors by focusing on a single program execution. Often a crucial step in these techniques is to define a causal ordering between events in the execution, which is then computed using vector clocks, a simple data structure that stores logical times of threads. The two basic operations of vector clocks, namely join and copy, require Θ(k) time, where k is the number of threads. Thus they are a computational bottleneck when k is large.

Cited by 9Open access

Techniques for Concurrent Access to Different Data Structure: A Research Review

Ranjeet Kaur, Pushpa Suri · 2013

Kurukshetra University, Kurukshetra Summary The data structures used in concurrent systems need to be modified. Modifications of shared data structures are done in several steps. If these steps are interleaved with modifications from other tasks, this can result in inconsistency of the data structure. Therefore the data structure needs to be protected from other tasks modifying it while the operation is executing. This can either be done using mutual exclusion(locks)/nonblocking/optimistic methods. The focus of this paper is to give a preview on data structure with efficient and practical approach of concurrency control.

Cited by 0

A Tree Clock Data Structure for Causal Orderings in Concurrent Executions

Umang Mathur, Andreas Pavlogiannis, Hünkar Can Tunç et al. · arXiv (Cornell University) · 2022

Dynamic techniques are a scalable and effective way to analyze concurrent programs. Instead of analyzing all behaviors of a program, these techniques detect errors by focusing on a single program execution. Often a crucial step in these techniques is to define a causal ordering between events in the execution, which is then computed using vector clocks, a simple data structure that stores logical times of threads. The two basic operations of vector clocks, namely join and copy, require $Θ(k)$ time, where $k$ is the number of threads. Thus they are a computational bottleneck when $k$ is large. In this work, we introduce tree clocks, a new data structure that replaces vector clocks for computing causal orderings in program executions. Joining and copying tree clocks takes time that is roughly proportional to the number of entries being modified, and hence the two operations do not suffer the a-priori $Θ(k)$ cost per application. We show that when used to compute the classic happens-before (HB) partial order, tree clocks are optimal, in the sense that no other data structure can lead to smaller asymptotic running time. Moreover, we demonstrate that tree clocks can be used to compute other partial orders, such as schedulable-happens-before (SHB) and the standard Mazurkiewicz (MAZ) partial order, and thus are a versatile data structure. Our experiments show that just by replacing vector clocks with tree clocks, the computation becomes from $2.02 \times$ faster (MAZ) to $2.66 \times$ (SHB) and $2.97 \times$ (HB) on average per benchmark. These results illustrate that tree clocks have the potential to become a standard data structure with wide applications in concurrent analyses.

Cited by 0Open access

Cover: A skip list data structure with concurrent inserts and deletes.

Chalmers Reproservice · 2008

This thesis deals with how to design and implement efficient, practical and reliable concurrent data structures. The design method using mutual exclusion incurs serious drawbacks, whereas the alternative non-blocking techniques avoid those problems and also admit improved parallelism. However, designing non-blocking algorithms is a very complex task, and a majority of the algorithms in the literature are either inefficient, impractical or both. We have studied how information available in real-time systems can improve and simplify non-blocking algorithms. We have designed new methods for recycling of buffers as well as time-stamps, and have applied them on known non-blocking algorithms for registers, snapshots and priority queues. We have designed, to the best of our knowledge, the first practical lockfree algorithm of a skip list data structure. Using our skip list construction we have designed a lock-free algorithm of the priority queue abstract data type, as well as a lock-free algorithm of the dictionary abstract data type.

Cited by 0

Generating Concurrent Programs From Sequential Data Structure Knowledge Using Answer Set Programming

Sarat Chandra Varanasi, Neeraj Mittal, Gopal Gupta · Electronic Proceedings in Theoretical Computer Science · 2021

We tackle the problem of automatically designing concurrent data structure operations given a sequential data structure specification and knowledge about concurrent behavior. Designing concurrent code is a non-trivial task even in simplest of cases. Humans often design concurrent data structure operations by transforming sequential versions into their respective concurrent versions. This requires an understanding of the data structure, its sequential behavior, thread interactions during concurrent execution and shared memory synchronization primitives. We mechanize this design process using automated commonsense reasoning. We assume that the data structure description is provided as axioms alongside the sequential code of its algebraic operations. This information is used to automatically derive concurrent code for that data structure, such as dictionary operations for linked lists and binary search trees. Knowledge in our case is expressed using Answer Set Programming (ASP), and we employ deduction and abduction -- just as humans do -- in the reasoning involved. ASP allows for succinct modeling of first order theories of pointer data structures, run-time thread interactions and shared memory synchronization. Our reasoner can systematically make the same judgments as a human reasoner, while constructing provably safe concurrent code. We present several reasoning challenges involved in transforming the sequential data structure into its equivalent concurrent version. All the reasoning tasks are encoded in ASP and our reasoner can make sound judgments to transform sequential code into concurrent code. To the best of our knowledge, our work is the first one to use commonsense reasoning to automatically transform sequential programs into concurrent code. We also have developed a tool that we describe that relies on state-of-the-art ASP solvers and performs the reasoning tasks involved to generate concurrent code.

Cited by 1Open access

A Comparison of Concurrent Correctness Criteria for Shared Memory Based Data Structure

Dipanjan Bhattacharya · Journal of International Crisis and Risk Communication Research · 2016

Developing concurrent algorithms requires safety and liveness to be defined in order to understand their proper behavior. Safety refers to the correctness criteria while liveness is the progress guarantee. Nowadays there are a variety of correctness conditions for concurrent objects. The way these correctness conditions differ and the various trade-offs they present with respect to performance, usability, and progress guarantees is poorly understood. This presents a daunting task for the developers and users of such concurrent algorithms who are trying to better understand the correctness of their code and the various trade-offs associated with their design choices and use. The purpose of this study is to explore the set of known correctness conditions for concurrent objects, find their correlations and categorize them, and provide insights regarding their implications with respect to performance and usability. In this thesis, a comparative study of Linearizability, Sequential Consistency, Quiescent Consistency and Quasi Linearizability will be presented using data structures like FIFO Queues, Stacks, and Priority Queues, and with a case study for performance of these implementations using different correctness criteria.

Cited by 0Open access

Automated Robustness Verification of Concurrent Data Structure Libraries against Relaxed Memory Models

Kartik Nagar, Anmol Sahoo, Romit Roy Chowdhury et al. · Proceedings of the ACM on Programming Languages · 2024

Clients reason about the behavior of concurrent data structure libraries such as sets, queues, or stacks using specifications that capture well-understood correctness conditions, such as linearizability. The implementation of these libraries, however, focused as they are on performance, may additionally exploit relaxed memory behavior allowed by the language or underlying hardware that weaken the strong ordering and visibility constraints on shared-memory accesses that would otherwise be imposed by a sequentially consistent (SC) memory model. As an alternative to developing new specification and verification mechanisms for reasoning about libraries under relaxed memory model, we instead consider the orthogonal problem of library robustness , a property that holds when all possible behaviors of a library implementation under relaxed memory model are also possible under SC. In this paper, we develop a new automated technique for verifying robustness of library implementations in the context of a C11-style memory model. This task is challenging because a most-general client may invoke an unbounded number of concurrently executing library operations that can manipulate an unbounded number of shared locations. We establish a novel inductive technique for verifying library robustness that leverages prior work on the robustness problem for the C11 memory model based on the search for a non-robustness witness under SC executions. We crucially rely on the fact that this search is carried out over SC executions, and use high-level SC specifications (including linearizability) of the library to verify the absence of a non-robustness witness. Our technique is compositional - we show how we can safely preserve robustness of multiple interacting library implementations and clients using additional SC fences to guarantee robustness of entire executions. Experimental results on a number of complex realistic library implementations demonstrate the feasibility of our approach.

Cited by 1Open access

CSSTs: A Dynamic Data Structure for Partial Orders in Concurrent Execution Analysis

Hünkar Can Tunç, Ameya Prashant Deshmukh, Berk Çirişci et al. · 2024

Dynamic analyses are a standard approach to analyzing and testing concurrent programs. Such techniques observe program traces σ and analyze them to infer the presence or absence of bugs. At its core, each analysis maintains a partial order P that represents order dependencies between the events of σ. Naturally, the scalability of the analysis largely depends on maintaining P efficiently. The standard data structure for this task has thus far been Vector Clocks. These, however, are slow for analyses that follow a non-streaming style, costing O(n) time for inserting (and propagating) each new ordering in P, where n is the size of σ, while they cannot handle the deletion of existing orderings.

Cited by 3Open access

Artifact for "A Tree Clock Data Structure for Causal Orderings in Concurrent Executions"

Mathur, Umang, Pavlogiannis, Andreas, Tunç, Hünkar Can et al. · Zenodo (CERN European Organization for Nuclear Research) · 2021

Dynamic techniques are a scalable and effective way to analyze concurrent programs. Instead of analyzing all behaviors of a program, these techniques detect errors by focusing on a single program execution. Often a crucial step in these techniques is to define a causal ordering between events in the execution, which is then computed using <em>vector clocks</em>, a simple data structure that stores logical times of threads. The two basic operations of vector clocks, namely join and copy, require Θ(<em>k</em>) time, where <em>k</em> is the number of threads. Thus they are a computational bottleneck when <em>k</em> is large. In this work, we introduce <em>tree clocks</em>, a new data structure that replaces vector clocks for computing causal orderings in program executions. Joining and copying tree clocks takes time that is roughly proportional to the number of entries being modified, and hence the two operations do not suffer the a-priori Θ(<em>k</em>) cost per application. We show that when used to compute the classic happens-before HB partial order, tree clocks are <em>optimal</em>, in the sense that no other data structure can lead to smaller asymptotic running time. Moreover, we demonstrate that tree clocks can be used to compute other partial orders, such as schedulable-happens-before (SHB) and the standard Mazurkiewicz (MAZ) partial order, and thus are a versatile data structure. Our large-scale experiments on standard benchmarks show that just by replacing vector clocks with tree clocks, the computation becomes from 1.73X faster (MAZ) to 2.53X faster SHB on average per benchmark. These results illustrate that tree clocks have the potential to become a standard data structure with wide applications in concurrent dynamic analyses.

Cited by 0Open access