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Kahn process networks as concurrent data structures : lock freedom, parallelism, relaxation in shared memory

Abstract : In this thesis, we are interested in Kahn process networks, a simple yet expressive model of concurrency, and its parallel implementation on modern shared-memory architectures. Kahn process networks expose concurrency to the programmer through an arrangement of sequential processes and single-producer single-consumer channels. The focus is on the implementation aspects. Of particular importance to our study are two parameters: lock freedom and relaxed memory. The development of fast andefficient lock-free algorithms ties into concerns of controlled resource consumption and reliable performance on current and future platforms with unfair or skewed scheduling such as virtual machines and GPUs. Our work with relaxed memory models complements this more theoretical approach by offering a window into realistic sharedmemory architectures. We present a new lock-free algorithm for a Kahn process network interpreter. It is disjoint-access parallel: we allow multiple threads to work on the same shared Kahn process network, fully utilizing the parallelism exhibited by independent processes. It is nonblockingin that it guarantees global progress in bounded memory, even in the presence of (possibly infinite) delays affecting the executing threads. To our knowledge, it is the first lock-free system of this size, and integrates various well-known non-blocking techniques and concepts (e.g., safe memory reclamation, multi-word updates, assistance) with ideas and optimizations specific to the Kahn network setting. We also discuss a variant of the algorithm, which is blocking and targeted at high-performance computing, with encouraging experimental results.
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Submitted on : Thursday, April 5, 2018 - 12:14:08 PM
Last modification on : Wednesday, October 14, 2020 - 4:12:40 AM


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Nhat Minh Lê. Kahn process networks as concurrent data structures : lock freedom, parallelism, relaxation in shared memory. Programming Languages [cs.PL]. Université Paris sciences et lettres, 2016. English. ⟨NNT : 2016PSLEE051⟩. ⟨tel-01759291⟩



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