2018年博士论文奖

L. Alvisi, I. Keidar, A. Richa, A. Schwarzmann
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引用次数: 0

摘要

2018年分布式计算原理博士论文奖的获得者是Rati Gelashvili博士,他的论文题为“同步的复杂性”,是在麻省理工学院Nir Shavit教授的指导下完成的。分布式算法的核心是如何高效地解决不同模型下的leader选举和一致性等同步问题。Gelashvili的论文对解决同步任务的复杂性进行了深入而广泛的研究。它对理解在各种模型中解决同步任务的复杂性做出了重大贡献。特别是,它推动了我们对共识的理解的边界,共识是异步计算线程相互协调的算法过程,这是30多年来广泛研究的主题。在他论文的一部分中,Gelashvili挑战了Herlihy基于共识的可计算性层次结构的基础,该层次结构是25年来多处理器和多核机器中并发数据结构和同步原语的计算能力分类的理论基础。他注意到Herlihy的经典层次结构将同步指令视为不同的对象,这种方法与现实世界相去甚远,在现实世界中,多处理器确实允许进程将受支持的原子指令应用于任意内存位置。Gelashvili表明,与普遍看法相反,解决共识并不需要多核架构支持“强”同步指令,如比较与交换。相反,“较弱”指令(如减量和乘法)的组合就足够了。他接着为并发对象提出了另一种基于复杂性的层次结构。该论文通过证明随机共识匿名情况的线性空间界进一步开辟了一条新的研究路线,这是15年来该问题的第一个重大进展,获得了DISC 2015年最佳论文奖,并且Gelashvili为此开发了新的下界技术。除了它们的重要性之外,这些结果在技术上也很复杂,在数学上也很漂亮。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
2018 Doctoral Dissertation Award
The winner of the 2018 Principles of Distributed Computing Doctoral Dissertation Award is Dr. Rati Gelashvili, for his dissertation titled "On the Complexity of Synchronization," written under the supervision of Prof. Nir Shavit at the Massachusetts Institute of Technology. The field of distributed algorithms revolves around efficiently solving synchronization tasks, such as leader election and consensus in different models. Gelashvili's thesis provides an extraordinary study of the complexity of solving synchronization tasks, which is both deep and broad. It makes significant contributions towards understanding the complexity of solving synchronization tasks in various models. In particular, it pushes the boundary of our understanding of consensus, the algorithmic process by which asynchronous computation threads coordinate with each other, which has been the subject of extensive research for over 30 years. In one part of his thesis, Gelashvili challenges the underpinnings of Herlihy's consensus-based computability hierarchy, which has been the theoretical basis for classifying the computational power of concurrent data structures and synchronization primitives in multiprocessors and multicore machines for two and a half decades. He observes that Herlihy's classical hierarchy treats synchronization instructions as distinct objects, an approach that is far from the real-world, where multiprocessors do let processes apply supported atomic instructions to arbitrary memory locations. Gelashvili shows that, contrary to common belief, solving consensus does not require multicore architectures to support "strong" synchronization instructions such as compare-and-swap. Rather, combinations of "weaker" instructions such as decrement and multiply suffice. He goes on to propose an alternative complexity-based hierarchy for concurrent objects. The dissertation further opens a new line of research by proving a linear-space bound for the anonymous case of randomized consensus, the first major progress on this problem in 15 years, which won the Best Paper Award at DISC 2015, and for which Gelashvili developed novel lower bound techniques. Apart from their great importance, these results are also technically complex and mathematically beautiful.
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