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检索条件"主题词=Concurrent Data Structures"

共 173 条记录，以下是11-20 订阅

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Opportunities and Limitations of Hardware Timestamps in concurrent data structures 37

Opportunities and Limitations of Hardware Timestamps in Conc...

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37th IEEE International Parallel and Distributed Processing Symposium (IPDPS)

作者： Grimes, Olivia Nelson-Slivon, Jacob Hassan, Ahmed Palmieri, Roberto Lehigh Univ Bethlehem PA 18015 USA

ISBN: (纸本)9798350337662

Designing high-performance, highly-concurrent linearizable data structures is complex, especially when bulk operations (e.g., range queries) are included. Relying on a single source of synchronization, such as a logical global timestamp, unequivocally eases the design of the synchronization schemes. However, such a design creates a single point of contention, and thus carries performance downsides. As a result, designers often face the dilemma between a simple design and a performance bottleneck. Recently, modern commodity architectures have enabled low-level mechanisms that guarantee that the timestamp registers of all CPUs are synchronized, thus enabling the use of hardware timestamps in data structure designs. Although recent work already exploits this, this work aims at understanding the opportunities and limitations of using hardware timestamps in existing data structure designs. We address this challenge by applying hardware timestamping to three recent state-of-the-art algorithms that use logical timestamps to support range queries in concurrent data structures. Our evaluation shows that the use of hardware timestamps does indeed improve performance compared to the original designs, achieving up to 5.5x improvement. More importantly, by removing the bottleneck of using global logical timestamps in these algorithms, we highlight the design choices that most significantly impact the use of hardware timestamps. Specifically, we show that the mechanism of labeling objects with timestamps plays an important role in maximizing the benefits of leveraging hardware timestamps.

关键词： concurrent data structures Linearizability Range Query

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Memory Tagging: Minimalist Synchronization for Scalable concurrent data structures 20

Memory Tagging: Minimalist Synchronization for Scalable Conc...

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32nd ACM Symposium on Parallelism in Algorithms and Architectures (SPAA)

作者： Alistarh, Dan Brown, Trevor Singhal, Nandini IST Austria Klosterneuburg Austria Univ Waterloo Waterloo ON Canada Microsoft R&D India New Delhi India

ISBN: (纸本)9781450369350

There has been a significant amount of research on hardware and software support for efficient concurrent data structures;yet, the question of how to build correct, simple, and scalable data structures has not yet been definitively settled. In this paper, we revisit this question from a minimalist perspective, and ask: what is the smallest amount of synchronization required for correct and efficient concurrent search data structures, and how could this minimal synchronization support be provided in hardware? To address these questions, we introduce memory tagging, a simple hardware mechanism which enables the programmer to "tag" a dynamic set of memory locations, at cache-line granularity, and later validate whether the memory has been concurrently modified, with the possibility of updating one of the underlying locations atomically if validation succeeds. We provide several examples showing that this mechanism can enable fast and arguably simple concurrent data structure designs, such as lists, binary search trees, balanced search trees, range queries, and Software Transactional Memory (STM) implementations. We provide an implementation of memory tags in the Graphite multi-core simulator, showing that the mechanism can be implemented entirely at the level of L1 cache, and that it can enable non-trivial speedups versus existing implementations of the above data structures.

关键词： concurrent data structures synchronization techniques transactional memory search data structures hardware mechanisms

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How to Relax Instantly: Elastic Relaxation of concurrent data structures 30th

How to Relax Instantly: Elastic Relaxation of Concurrent Dat...

引用

30th European Conference on Parallel and Distributed Processing (Euro-Par)

作者： von Geijer, Kare Tsigas, Philippas Chalmers Univ Technol Gothenburg Sweden

ISBN: (纸本)9783031695827;9783031695834

The sequential semantics of many concurrent data structures, such as stacks and queues, inevitably lead to memory contention in parallel environments, thus limiting scalability. Semantic relaxation has the potential to address this issue, increasing the parallelism at the expense of weakened semantics. Although prior research has shown that improved performance can be attained by relaxing concurrent data structure semantics, there is no one-size-fits-all relaxation that adequately addresses the varying needs of dynamic executions. In this paper, we first introduce the concept of elastic relaxation and consequently present the Lateral structure, which is an algorithmic component capable of supporting the design of elastically relaxed concurrent data structures. Using the Lateral, we design novel elastically relaxed, lock-free queues and stacks capable of reconfiguring relaxation during run-time. We establish linearizability and define upper bounds for relaxation errors in our designs. Experimental evaluations show that our elastic designs hold up against state-of-the-art statically relaxed designs, while also swiftly managing trade-offs between relaxation and operational latency. We also outline how to use the Lateral to design elastically relaxed lock-free counters and deques.

关键词： concurrent data structures lock-free relaxed semantics

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Brief Announcement: Tree Decomposition for Faster concurrent data structures

Brief Announcement: Tree Decomposition for Faster Concurrent...

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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

ISBN: (纸本)9781605588889

We show how to partition data structures representable by directed acyclic graphs, i.e. rooted trees, to allow for efficient complex operations, which lie beyond inserts, deletes and finds. The approach potentially improves the performance of any operation modifying more than one element of the data structure. It covers common data structures implementable via linked lists or trees such as sets and maps. We demonstrate its simplicity and its effectiveness using a concurrent sorted linked list. We achieve a speedup of up to 250% even for small divisions.

关键词： concurrent data structures graphs

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Constructing concurrent data structures on FPGA with Channels 19

Constructing Concurrent Data Structures on FPGA with Channel...

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ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA)

作者： Yan, Hui Li, Zhaoshi Liu, Leibo Yin, Shouyi Wei, Shaojun Tsinghua Univ Beijing Peoples R China

ISBN: (纸本)9781450361378

The performance of High-Level Synthesis (HLS) applications with irregular data structures is limited by its imperative programming paradigm like C/C++. In this paper, we show that constructing concurrent data structures with channels, a programming construct derived from CSP (communicating sequential processes) paradigm, is an effective approach to improve the performance of these applications. We evaluate concurrent data structure for FPGA by synthesizing a K-means clustering algorithm on the Intel HARP2 platform. A fully pipelined KMC processing element can be synthesized from OpenCL with the help of a SPSC (single-producer-single-consumer) queue and stack built from channels, achieving 15.2x speedup over a sequential baseline. The number of processing element can be scaled up by leveraging a MPMC (multiple-producer-multiple-consumer) stack with work distribution for dynamic load balance. Evaluation shows that an additional 3.5x speedup can be achieved when 4 processing element is instantiated. These results show that the concurrent data structure built with channels has great potential for improving the parallelism of HLS applications. We hope that our study will stimulate further research into the potential of channel-based HLS.

关键词： High-Level Synthesis concurrent data structures Communicating Sequential Processes K-means clustering Parallelism

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Relaxing the Correctness Conditions on concurrent data structures for Multicore CPUs. A Numerical Case Study 12th

Relaxing the Correctness Conditions on Concurrent Data Struc...

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12th International Conference on Parallel Processing and Applied Mathematics (PPAM)

作者： Laccetti, Giuliano Lapegna, Marco Mele, Valeria Montella, Raffaele Univ Napoli Federico II Dept Math & Applicat Naples Italy Univ Napoli Parthenope Dept Sci & Technol Naples Italy

ISBN: (纸本)9783319780542;9783319780535

The rise of new multicore CPUs introduced new challenges in the process of design of concurrent data structures: in addition to traditional requirements like correctness, linearizability and progress, the scalability is of paramount importance. It is a common opinion that these two demands are partially in conflict each others, so that in these computational environments it is necessary to relax the requirements on the traditional features of the data structures. In this paper we introduce a relaxed approach for the management of heap based priority queues on multicore CPUs, with the aim to realize a tradeoff between efficiency and sequential correctness. The approach is based on a sharing of information among only a small number of cores, so that to improve performance without completely losing the features of the data structure. The results obtained on a numerical algorithm show significant benefits in terms of parallel efficiency.

关键词： HPC heterogeneous systems concurrent data structures Programming models

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Using Delta Debugging to Minimize Stress Tests for concurrent data structures 10

Using Delta Debugging to Minimize Stress Tests for Concurren...

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10th IEEE International Conference on Software Testing, Verification and Validation (ICSTW)

作者： Xu, Jing Lei, Yu Carver, Richard Univ Texas Arlington Dept Comp Sci & Engn Arlington TX 76019 USA

ISBN: (纸本)9781509060313

concurrent data structures are often tested under stress to detect bugs that can only be exposed by some rare interleavings of instructions. A typical stress test for a concurrent data structure creates a number of threads that repeatedly invoke methods of the target data structure. After a failure is detected by a stress test, developers need to localize the fault causing the failure. However, the execution trace of a failed stress test may be very long, making it time-consuming to replay the failure and localize the fault. In this paper, we present an approach to minimizing stress tests for concurrent data structures. Our approach is to create a smaller test that still produces the same failure by removing some of the threads and/or method invocations in the original stress test.. We apply delta debugging to identify the threads and method invocations that are essential for causing the failure. Other threads and method invocations are removed to create a smaller stress test. To increase the chance of triggering the original failure during the execution of the new stress test, we force the new execution to replay the original failed execution trace when possible, and try to guide the execution back to the failed trace when the execution diverges. We describe a tool called TestMinimizer and report the results of an empirical study in which TestMinimizer was applied to 16 real-life concurrent data structures. The results of our evaluation showed that TestMinimizer can effectively and efficiently minimize the stress tests for these concurrent data structures.

关键词： stress testing minimization concurrent data structures delta debugging execution replay

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Universally Scalable concurrent data structures

Universally Scalable Concurrent Data Structures

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作者： Tudor Alexandru DAVID ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE

学位级别：博士

The increase in the number of cores in processors has been an important trend over the past decade. In order to be able to efficiently use such architectures, modern software must be scalable: performance should increase proportionally to the number of allotted cores. While some software is inherently parallel, with threads seldom having to coordinate, a large fraction of software systems are based on shared state, to which access must be coordinated. This shared state generally comes in the form of a concurrent data structure. It is thus essential for these concurrent data structures to be correct, fast and scalable, regardless of the scenario (i. e., different workloads, processors, memory units, programming abstractions). Nevertheless, few or no generic approaches exist that result in concurrent data structures which scale in a large spectrum of environments. This dissertation introduces a set of generic methods that allows to build - irrespective of the deployment environment - fast and scalable concurrent data structures. We start by identifying a set of sufficient conditions for concurrent search data structures to scale and perform well regardless of the workloads and processors they are running on. We introduce "asynchronized concurrency", a paradigm consisting of four complementary programming patterns, which calls for the design of concurrent search data structures to resemble that of their sequential counterparts. Next, we show that there is virtually no practical situation in which one should seek a "theoretically wait-free" algorithm at the expense of a state-of-the-art blocking algorithm in the case of search data structures: blocking algorithms are simple, fast, and can be made "practically wait-free". We then focus on the memory unit, and provide a method yielding fast concurrent data structures even when the memory is non-volatile, and structures must be recoverable in case of a transient failure. We start by introducing a generic technique that all

关键词： concurrent data structures multi-core transactions scalability performance non-volatile RAM

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Synchronization Costs in Parallel Programs and concurrent data structures

Synchronization Costs in Parallel Programs and Concurrent Da...

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作者： Vitalii Aksenov ITMO University

学位级别：博士

To use the computational power of modern computing machines, we have to deal with concurrent programs. Writing efficient concurrent programs is notoriously difficult, primarily due to the need of harnessing synchronization costs. In this thesis, we focus on synchronization costs in parallel programs and concurrent data structures. First, we present a novel granularity control technique for parallel programs designed for the dynamic multithreading environment. Then in the context of concurrent data structures, we consider the notion of concurrency-optimality and propose the first implementation of a concurrency-optimal binary search tree that, intuitively, accepts a concurrent schedule if and only if the schedule is correct. Also, we propose parallel combining, a technique that enables efficient implementations of concurrent data structures from their parallel batched counterparts. We validate the proposed techniques via experimental evaluations showing superior or comparable performance with respect to state-of-the-art algorithms. From a more formal perspective, we consider the phenomenon of helping in concurrent data structures. Intuitively, helping is observed when the order of some operation in a linearization is fixed by a step of another process. We show that no wait-free linearizable implementation of stack using read, write, compare&swap and fetch&add primitives can be help-free, correcting a mistake in an earlier proof by Censor-Hillel et al. Finally, we propose a simple way to analytically predict the throughput of data structures based on coarse-grained locking.

关键词： Parallel programs concurrent data structures synchronization performance granularity control algorithms

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Proving concurrent data structures Linearizable 27

Proving Concurrent Data Structures Linearizable

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27th IEEE International Symposium on Software Reliability Engineering (ISSRE)

作者： Singh, Vineet Neamtiu, Iulian Gupta, Rajiv Univ Calif Riverside Riverside CA 92521 USA New Jersey Inst Technol Newark NJ 07102 USA

ISBN: (纸本)9781467390026

Linearizability of concurrent data structure implementations is notoriously hard to prove. Consequently, current verification techniques can only prove linearizability for certain classes of data structures. We introduce a generic, sound, and practical technique to statically check the linearizability of concurrent data structure implementations. Our technique involves specifying the concurrent operations as a list of sub-operations and passing this specification on to an automated checker that verifies linearizability using relationships between individual sub-operations. We have proven the soundness of our technique. Our approach is expressive: we have successfully verified the linearizability of 12 popular concurrent data structure implementations including algorithms that are considered to be challenging to prove linearizable such as elimination back-off stack, lazy linked list, and time-stamped stack. Our checker is effective, as it can verify the specifications in less than a second.

关键词： concurrent data structures Linearizability verification

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