{"title":"2018 Doctoral Dissertation Award","authors":"L. Alvisi, I. Keidar, A. Richa, A. Schwarzmann","doi":"10.1145/3212734.3232541","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":198284,"journal":{"name":"Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3212734.3232541","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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.