Dynamic circular work-stealing deque

Chase, David; Lev, Yossi

doi:10.1145/1073970.1073974

Cited by 183 publications

(138 citation statements)

References 9 publications

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“…As an example, consider the problem of implementing the Chase-Lev work-stealing queue [11] ("CL") on a relaxed memory model. Work stealing is a popular mechanism for efficient load-balancing used in runtime libraries for languages such as Java, Cilk [3] and X10 [10].…”

Section: Introductionmentioning

confidence: 99%

Automatic inference of memory fences

2012

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We addresses the problem of automatic verification and fence inference in concurrent programs running under relaxed memory models. Modern architectures implement relaxed memory models in which memory operations may be reordered and executed non-atomically. Instructions called memory fences are provided to the programmer, allowing control of this behavior. To ensure correctness of many algorithms, the programmer is often required to explicitly insert memory fences into her program. However, she must use as few fences as possible, or the benefits of the relaxed architecture may be lost. It is our goal to help automate the fence insertion process.We present an algorithm for automatic inference of memory fences in concurrent programs, relieving the programmer from this complex task. Given a finite-state program, a safety specification and a description of the memory model our algorithm computes a set of ordering constraints that guarantee the correctness of the program under the memory model. The computed constraints are maximally permissive: removing any constraint from the solution would permit an execution violating the specification. These constraints are then realized as additional fences in the input program.We implemented our approach in a pair of tools called fender and blender and used them to infer correct and efficient placements of fences for several non-trivial algorithms, including practical mutual exclusion primitives and concurrent data structures.

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Section: Introductionmentioning

confidence: 99%

Automatic inference of memory fences

2012

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“…Two unbounded non-blocking deques were proposed, the deque by Hendler et al based on linked lists of small arrays [10], and the Chase-Lev deque that uses dynamic circular arrays [5].…”

Section: Work-stealing Dequesmentioning

confidence: 99%

“…Tasks are often stored as pointers that are removed from the deque when the task is stolen [9,2,10,5]. To virtually eliminate the overhead of task creation for tasks that are never stolen, Faxén proposed a direct task stack, storing tasks instead of pointers in the work queue, implemented in Wool [7,8].…”

Section: Work-stealing Dequesmentioning

confidence: 99%

Lace: Non-blocking Split Deque for Work-Stealing

Dijk

Pol

2014

Lecture Notes in Computer Science

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Work-stealing is an efficient method to implement load balancing in fine-grained task parallelism. Typically, concurrent deques are used for this purpose. A disadvantage of many concurrent deques is that they require expensive memory fences for local deque operations. In this paper, we propose a new non-blocking work-stealing deque based on the split task queue. Our design uses a dynamic split point between the shared and the private portions of the deque, and only requires memory fences when shrinking the shared portion. We present Lace, an implementation of work-stealing based on this deque, with an interface similar to the work-stealing library Wool, and an evaluation of Lace based on several common benchmarks. We also implement a recent approach using private deques in Lace. We show that the split deque and the private deque in Lace have similar low overhead and high scalability as Wool.

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“…1 shows a pseudo-code of the ChaseLev work-stealing queue [7] (note that our implementation handle the complete C code). A work-stealing queue is a special kind of double-ended queue that provides three operations: put, take, and steal.…”

Section: Overviewmentioning

confidence: 99%

“…Chase-Lev's WSQ [7] put, take operate on the same end of the queue, steal works at the opposite end. Both take and steal implemented using CAS.…”

Section: Algorithm Descriptionmentioning

confidence: 99%

Dynamic synthesis for relaxed memory models

Liu

Nedev

Prisadnikov

et al. 2012

Proceedings of the 33rd ACM SIGPLAN Conference on Programming Language Design and Implementation

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Modern architectures implement relaxed memory models which may reorder memory operations or execute them non-atomically. Special instructions called memory fences are provided, allowing control of this behavior.To implement a concurrent algorithm for a modern architecture, the programmer is forced to manually reason about subtle relaxed behaviors and figure out ways to control these behaviors by adding fences to the program. Not only is this process time consuming and error-prone, but it has to be repeated every time the implementation is ported to a different architecture.In this paper, we present the first scalable framework for handling real-world concurrent algorithms running on relaxed architectures. Given a concurrent C program, a safety specification, and a description of the memory model, our framework tests the program on the memory model to expose violations of the specification, and synthesizes a set of necessary ordering constraints that prevent these violations. The ordering constraints are then realized as additional fences in the program.We implemented our approach in a tool called DFENCE based on LLVM and used it to infer fences in a number of concurrent algorithms. Using DFENCE, we perform the first in-depth study of the interaction between fences in real-world concurrent C programs, correctness criteria such as sequential consistency and linearizability, and memory models such as TSO and PSO, yielding many interesting observations. We believe that this is the first tool that can handle programs at the scale and complexity of a lock-free memory allocator.

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Dynamic circular work-stealing deque

Cited by 183 publications

References 9 publications

Automatic inference of memory fences

Automatic inference of memory fences

Lace: Non-blocking Split Deque for Work-Stealing

Dynamic synthesis for relaxed memory models

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