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检索条件"主题词=Concurrent Data Structures"

共 173 条记录，以下是121-130 订阅

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Upper and Lower Bounds for Deterministic Approximate Objects 41

Upper and Lower Bounds for Deterministic Approximate Objects

引用

41st IEEE International Conference on Distributed Computing Systems (ICDCS)

作者： Hendler, Danny Khattabi, Adnane Milani, Alessia Travers, Corentin Ben Gurion Univ Negev Beer Sheva Israel Univ Bordeaux LaBRI Bordeaux France Bordeaux INP LaBRI Bordeaux France

ISBN: (纸本)9781665445139

Relaxing the sequential specification of shared objects has been proposed as a promising approach to obtain implementations with better complexity. In this paper, we study the step complexity of relaxed variants of two common shared objects: max registers and counters. In particular, we consider the k-multiplicative-accurate max register and the k-multiplicative-accurate counter, where read operations are allowed to err by a multiplicative factor of k (for some k is an element of N). More accurately, reads are allowed to return an approximate value x of the maximum value v previously written to the max register, or of the number v of increments previously applied to the counter, respectively, such that v/k <= x <= v.k. We provide upper and lower bounds on the complexity of implementing these objects in a wait-free manner in the shared memory model.

关键词： Distributed computing distributed algorithms shared memory fault tolerance concurrent data structures relaxed specifications

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Revisiting the Combining Synchronization Technique 12

Revisiting the Combining Synchronization Technique

引用

17th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

作者： Fatourou, Panagiota Kallimanis, Nikolas D. Univ Crete Dept Comp Sci Iraklion Greece Univ Ioannina Dept Comp Sci GR-45110 Ioannina Greece

ISBN: (纸本)9781450311601

Fine-grain thread synchronization has been proved, in several cases, to be outperformed by efficient implementations of the combining technique where a single thread, called the combiner, holding a coarse-grain lock, serves, in addition to its own synchronization request, active requests announced by other threads while they are waiting by performing some form of spinning. Efficient implementations of this technique significantly reduce the cost of synchronization, so in many cases they exhibit much better performance than the most efficient finely synchronized algorithms. In this paper, we revisit the combining technique with the goal to discover where its real performance power resides and whether or how ensuring some desired properties (e.g., fairness in serving requests) would impact performance. We do so by presenting two new implementations of this technique;the first (CC-Synch) addresses systems that support coherent caches, where as the second (DSM-Synch) works better in cacheless NUMA machines. In comparison to previous such implementations, the new implementations (1) provide bounds on the number of remote memory references (RMRs) that they perform, (2) support a stronger notion of fairness, and (3) use simpler and less basic primitives than previous approaches. In all our experiments, the new implementations out perform by far all previous state-of-the-art combining-based and fine-grain synchronization algorithms. Our experimental analysis sheds light to the questions we aimed to answer. Several modern multi-core systems organize the cores into clusters and provide fast communication within the same cluster and much slower communication across clusters. We present an hierarchical version of CC-Synch, called H-Synch which exploits the hierarchical communication nature of such systems to achieve better performance. Experiments show that H-Synch significantly outpperforms previous state-of-the-art hierarchical approaches. We provide new implementations of co

关键词： Algorithms Experimentation Theory Performance Synchronization techniques combining hierarchical algorithms blocking algorithms concurrent data structures

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Lock-Free data-Structure Iterators 1

引用

27th International Symposium on Distributed Computing (DISC)

作者： Petrank, Erez Timnat, Shahar Technion Israel Inst Technol Dept Comp Sci IL-32000 Haifa Israel

ISBN: (数字)9783642415272

ISBN: (纸本)9783642415272;9783642415265

concurrent data structures are often used with large concurrent software. An iterator that traverses the data structure items is a highly desirable interface that often exists for sequential data structures but is missing from (almost all) concurrent data-structure implementations. In this paper we introduce a technique for adding a linearizable wait-free iterator to a wait-free or a lock-free data structure that implements a set. We use this technique to implement an iterator for the wait-free and lock-free linked-lists and for the lock-free skip-list.

关键词： concurrent data structures lock-freedom wait-freedom linked-list skiplist iterator snapshot

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The Power of Choice in Priority Scheduling 17

The Power of Choice in Priority Scheduling

引用

36th ACM Symposium on Principles of Distributed Computing (PODC)

作者： Alistarh, Dan Kopinsky, Justin Li, Jerry Nadiradze, Giorgi IST Austria Klosterneuburg Austria Swiss Fed Inst Technol Zurich Switzerland MIT Cambridge MA 02139 USA

ISBN: (纸本)9781450349925

Consider the following random process: we are given n queues, into which elements of increasing labels are inserted uniformly at random. To remove an element, we pick two queues at random, and remove the element of lower label (higher priority) among the two. The cost of a removal is the rank of the label removed, among labels still present in any of the queues, that is, the distance from the optimal choice at each step. Variants of this strategy are prevalent in state-of-the-art concurrent priority queue implementations. Nonetheless, it is not known whether such implementations provide any rank guarantees, even in a sequential model. We answer this question, showing that this strategy provides surprisingly strong guarantees: Although the single-choice process, where we always insert and remove from a single randomly chosen queue, has degrading cost, going to infinity as we increase the number of steps, in the two choice process, the expected rank of a removed element is O(n) while the expected worst-case cost is O(n log n). These bounds are tight, and hold irrespective of the number of steps for which we run the process. The argument is based on a new technical connection between "heavily loaded" balls-into-bins processes and priority scheduling. Our analytic results inspire a new concurrent priority queue implementation, which improves upon the state of the art in terms of practical performance.

关键词： relaxed data structures concurrent data structures randomized algorithms

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Dag-Calculus: A Calculus for Parallel Computation 2016

Dag-Calculus: A Calculus for Parallel Computation

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21st ACM SIGPLAN International Conference on Functional Programming (ICFP)

作者： Acar, Umut A. Chargueraud, Arthur Rainey, Mike Sieczkowski, Filip Carnegie Mellon Univ Pittsburgh PA 15213 USA Inria Rocquencourt France

ISBN: (纸本)9781450342193

Increasing availability of multicore systems has led to greater focus on the design and implementation of languages for writing parallel programs. Such languages support various abstractions for parallelism, such as fork-join, async-finish, futures. While they may seem similar, these abstractions lead to different semantics, language design and implementation decisions, and can significantly impact the performance of end-user applications. In this paper, we consider the question of whether it would be possible to unify various paradigms of parallel computing. To this end, we propose a calculus, called dag calculus, that can encode fork-join, async-finish, and futures, and possibly others. We describe dag calculus and its semantics, establish translations from the aforementioned paradigms into dag calculus. These translations establish that dag calculus is sufficiently powerful for encoding programs written in prevailing paradigms of parallelism. We present concurrent algorithms and data structures for realizing dag calculus on multicore hardware and prove that the proposed techniques are consistent with the semantics. Finally, we present an implementation of the calculus and evaluate it empirically by comparing its performance to highly optimized code from prior work. The results show that the calculus is expressive and that it competes well with, and sometimes outperforms, the state of the art.

关键词： Calculus operational semantics parallelism proofs experiments concurrent data structures

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The Future(s) of Shared data structures 14

The Future(s) of Shared Data Structures

引用

ACM Symposium on Principles of Distributed Computing (PODC)

作者： Kogan, Alex Herlihy, Maurice Oracle Labs Burlington MA 01803 USA Brown Univ Providence RI USA Oracle Labs Providence RI USA

ISBN: (纸本)9781450329446

This paper considers how to use futures, a well-known mechanism to manage parallel computations, to improve the performance of long-lived, mutable shared data structures in large-scale multicore systems. We show that futures can enable type-specific optimizations such as combining and elimination, improve cache locality and reduce contention. To exploit these benefits in an effective way, however, it is important to define clear notions of correctness. We propose new extensions to linearizability appropriate for method calls that return futures as results. To illustrate the utility and trade-offs of these extensions, we describe implementations of three common data structures: stacks, queues, and linked lists, designed to exploit futures. Our experimental results show that optimizations enabled by futures lead to substantial performance improvements, in some cases up to two orders of magnitude, compared to well-known lock-free alternatives.

关键词： concurrent data structures futures elimination combining linearizability

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Symmetric Tokens based Group Mutual Exclusion 20

Symmetric Tokens based Group Mutual Exclusion

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49th International Conference on Parallel Processing (ICPP)

作者： Aravind, Alex Univ Northern British Columbia Prince George BC Canada

ISBN: (纸本)9781450388689

The group mutual exclusion (GME) problem is a generalization of the mutual exclusion problem. The problem is fundamental to parallel and distributed processing, as it is inherent in several applications in the modern multicore-integrated cloud era of the distributed computing world. This paper proposes a First-Come-First-Served (FCFS) GME algorithm that only uses atomic read/write operations for n threads. The proposed algorithm has three key features: (i) its simplicity;(ii) it has O(n) complexity in both space (shared variable requirement) and time (remote memory references (RMR)) in cache coherent (CC) models;and (ii) it settles the open problem posed in 2001.

关键词： Concurrency group mutual exclusion concurrent data structures concurrent servers symmetric tokens RMR complexity

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The Performance Power of Software Combining in Persistence 22

The Performance Power of Software Combining in Persistence

引用

27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP)

作者： Fatourou, Panagiota Kallimanis, Nikolaos D. Kosmas, Eleftherios Univ Paris LIPADE F-75006 Paris France Fdn Res Technol Hellas FORTH Inst Comp Sci Ilellas Greece Univ Crete Dept Comp Sci Iraklion Greece

ISBN: (纸本)9781450392044

The availability of Non-Volatile Main Memory (known as NVMM) enables the design of recoverable concurrent algorithms. We study the power of software combining in achieving recoverable synchronization and designing persistent data structures. Software combining is a general synchronization approach, which attempts to simulate the ideal world when executing synchronization requests (i.e., requests that must be executed in mutual exclusion). A single thread, called the combiner, executes all active requests, while the rest of the threads are waiting for the combiner to notify them that their requests have been applied. Software combining significantly decreases the synchronization cost and outperforms many other synchronization techniques in various cases. We identify three persistence principles, crucial for performance, that an algorithm's designer has to take into consideration when designing highly-efficient recoverable synchronization protocols or data structures. We illustrate how to make the appropriate design decisions in all stages of devising recoverable combining protocols to respect these principles. Specifically, we present two recoverable software combining protocols, satisfying different progress properties, that are many times faster and have much lower persistence cost than a large collection of existing persistent techniques for achieving scalable synchronization. We build fundamental recoverable data structures, such as stacks and queues, based on these protocols that outperform by far existing recoverable implementations of such data structures. We also provide the first recoverable implementation of a concurrent heap and present experiments to show that it has good performance when the size of the heap is not very large.

关键词： non-volatile memory NVM-based computing persistence recoverable algorithms and data structures software combining concurrent data structures stack queue heap synchronization wait-freedom performance principles performance analysis

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Gallatin: A General-Purpose GPU Memory Manager 24

Gallatin: A General-Purpose GPU Memory Manager

引用

29th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming (PPoPP)

作者： McCoy, Hunter Pandey, Prashant Univ Utah Salt Lake City UT 84112 USA

ISBN: (纸本)9798400704352

Dynamic memory management is critical for efficiently porting modern data processing pipelines to GPUs. However, building a general-purpose dynamic memory manager on GPUs is challenging due to the massive parallelism and weak memory coherence. Existing state-of-the-art GPU memory managers, Ouroboros and Reg-Eff, employ traditional data structures such as arrays and linked lists to manage memory objects. They build specialized pipelines to achieve performance for a fixed set of allocation sizes and fall back to the CUDA allocator for allocating large sizes. In the process, they lose general-purpose usability and fail to support critical applications such as streaming graph processing. In this paper, we introduce Gallatin, a general-purpose and high-performance GPU memory manager. Gallatin uses the van Emde Boas (vEB) tree data structure to manage memory objects efficiently and supports allocations of any size. Furthermore, we develop a highly-concurrentGPUimplementation of the vEB tree which can be broadly used in other GPU applications. It supports constant time insertions, deletions, and successor operations for a given memory size. In our evaluation, we compare Gallatin with state-of-theart specialized allocator variants. Gallatin is up to 374x faster on single-sized allocations and up to 264xfaster on mixed-size allocations than the next-best allocator. In scalability benchmarks, Gallatin is up to 254x times faster than the next-best allocator as the number of threads increases. For the graph benchmarks, Gallatin is 1.5x faster than the state-of-the-art for bulk insertions, slightly faster for bulk deletions, and is 3x faster than the next-best allocator for all graph expansion tests.

关键词： GPU Memory allocation concurrent data structures High performance computing

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Brief Announcement: Efficient Graph Algorithms without Synchronization

Brief Announcement: Efficient Graph Algorithms without Synch...

引用

29th ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing

作者： Schneider, Johannes Wattenhofer, Roger ETH Comp Engn & Networks Lab CH-8092 Zurich Switzerland

We give a graph decomposition technique that creates entirely independent subproblems for graph problems such as coloring and dominating sets that can be solved without synchronization on a distributed memory system. ... 详细信息

ISBN: (纸本)9781605588889

关键词： parallel algorithms concurrent data structures coloring dominating sets

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