For this issue, Matthias Englert has contributed an alternative and simpler proof of a result by Gamzu and Segev, which was in ACM Transactions on Algorithms in 2009. The problem considered in this paper was the reordering bu↵er problem on the line. Gamzu and Segev were the first to give an O(log n)-competitive algorithm for this problem, and there has been no improvement on this since then, leaving a gap with the best known lower bound of 2.154 by the same authors. Matthias’ proof shows that this result can be slightly improved (a smaller hidden constant) and simplified. Who is going to be the first to give a constant competitive algorithm, or show that this cannot be done?
为此，Matthias Englert在2009年的ACM Transactions on Algorithms上为Gamzu和Segev的结果提供了另一种更简单的证明。本文考虑的问题是在线上的重排序问题。Gamzu和Segev是第一个为这个问题给出O(log n)竞争算法的人，从那时起，这个算法就没有任何改进，与同一作者最著名的下界2.154有差距。Matthias的证明表明，这个结果可以稍微改进(一个更小的隐藏常数)并简化。谁会第一个给出一个恒定竞争算法，或者证明这是不可能做到的?
{"title":"SIGACT News Online Algorithms Column 33","authors":"R. V. Stee","doi":"10.1145/3197406.3197417","DOIUrl":"https://doi.org/10.1145/3197406.3197417","url":null,"abstract":"For this issue, Matthias Englert has contributed an alternative and simpler proof of a result by Gamzu and Segev, which was in ACM Transactions on Algorithms in 2009. The problem considered in this paper was the reordering bu↵er problem on the line. Gamzu and Segev were the first to give an O(log n)-competitive algorithm for this problem, and there has been no improvement on this since then, leaving a gap with the best known lower bound of 2.154 by the same authors. Matthias’ proof shows that this result can be slightly improved (a smaller hidden constant) and simplified. Who is going to be the first to give a constant competitive algorithm, or show that this cannot be done?","PeriodicalId":22106,"journal":{"name":"SIGACT News","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82270429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
How many operations are needed to compute a given polynomial f(x1; x2; : : : ; xn)? Answering questions of this form naturally leads us on a search for clever algorithmic techniques to reduce the number of operations required. Simultaneously, it also leads us towards the complementary task of finding techniques and paradigms for proving lower bounds on the minimum number of operations required. In this survey we describe one such paradigm for obtaining lower bounds.
{"title":"Guest Column: A Paradigm for Arithmetic Circuit Lower Bounds","authors":"N. Kayal, Chandan Saha","doi":"10.1145/3197406.3197416","DOIUrl":"https://doi.org/10.1145/3197406.3197416","url":null,"abstract":"How many operations are needed to compute a given polynomial f(x1; x2; : : : ; xn)? Answering questions of this form naturally leads us on a search for clever algorithmic techniques to reduce the number of operations required. Simultaneously, it also leads us towards the complementary task of finding techniques and paradigms for proving lower bounds on the minimum number of operations required. In this survey we describe one such paradigm for obtaining lower bounds.","PeriodicalId":22106,"journal":{"name":"SIGACT News","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88130425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nowadays concurrency is everywhere. Be it a mainstream multi-core machine, a computing cluster, or a large-scale distributed service, a modern computing system involves multiple processes that concurrently perform independent computations and communicate to synchronize their activities. Understanding concurrency is therefore getting essential in both practice and research in computer science. The first summer school on Practice and Theory of Concurrent Computing took place on July 3-7, 2017 in Saint-Petersburg, Russia. The school was hosted by ITMO university, and financially supported by DevExperts, Yandex, Télécom ParisTech, and ANR-DFG DISCMAT project.
{"title":"The First Summer School on Practice and Theory of Concurrent Computing SPTCC 2017","authors":"P. Kuznetsov","doi":"10.1145/3197406.3197421","DOIUrl":"https://doi.org/10.1145/3197406.3197421","url":null,"abstract":"Nowadays concurrency is everywhere. Be it a mainstream multi-core machine, a computing cluster, or a large-scale distributed service, a modern computing system involves multiple processes that concurrently perform independent computations and communicate to synchronize their activities. Understanding concurrency is therefore getting essential in both practice and research in computer science. The first summer school on Practice and Theory of Concurrent Computing took place on July 3-7, 2017 in Saint-Petersburg, Russia. The school was hosted by ITMO university, and financially supported by DevExperts, Yandex, Télécom ParisTech, and ANR-DFG DISCMAT project.","PeriodicalId":22106,"journal":{"name":"SIGACT News","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74423739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Warmest thanks to Neeraj Kayal and Chandan Saha for starting off all our 2018s so very nicely with their wonderful article, “A Paradigm for Arithmetic Circuit Lower Bounds”! And please do stay tuned for the coming articles in the Complexity Theory Column, namely, Josh Grochow and David H. Wolpert (tentative topic: new complexity questions regarding the thermodynamics of computation; so much more than (ir)reversibility), Lane A. Hemaspaandra and Holger Spakowski (tentative topic: team diagonalization), William Gasarch (not-at-all-tentative topic: the third P versus NP poll), William Gasarch (tentative topic: the muffin problem), and Emanuele Viola (topic: TBD). Yes, you can believe your eyes: The start of 2019 will be a gala “half-year of Bill (Gasarch)”! And please warm up your predicting hats, because in the very next issue of SIGACT News (June 2018) you will find in Bill’s Open Questions Column the poll questions he would like your answers to, as well as his discussion of his (surely provocative) thoughts about those questions. And then the results (based on your answers!) of his poll will appear as Complexity Theory Column #100 in the March 2019 issue of SIGACT News.
最热烈的感谢Neeraj Kayal和Chandan Saha，他们的精彩文章“算术电路下界的范例”非常好地开启了我们所有的2018年!请继续关注复杂性理论专栏的后续文章，即Josh Grochow和David H. Wolpert(暂定主题:关于计算热力学的新复杂性问题;还有Lane A. Hemaspaandra和Holger Spakowski(暂定主题:团队对角化)，William Gasarch(根本不是暂定主题:第三个P对NP民意调查)，William Gasarch(暂定主题:松饼问题)，Emanuele Viola(暂定主题:待定)。是的，你可以相信你的眼睛:2019年的开始将是一个盛大的“比尔(Gasarch)半年”!请准备好你的预测帽，因为在下一期的SIGACT新闻(2018年6月)中，你将在比尔的开放问题专栏中找到他希望你回答的民意调查问题，以及他对这些问题(肯定是挑衅的)想法的讨论。然后，他的民意调查结果(基于你的回答!)将出现在2019年3月的《SIGACT新闻》的复杂性理论专栏#100中。
{"title":"SIGACT News Complexity Theory Column 97","authors":"L. Hemaspaandra","doi":"10.1145/3197406.3197415","DOIUrl":"https://doi.org/10.1145/3197406.3197415","url":null,"abstract":"Warmest thanks to Neeraj Kayal and Chandan Saha for starting off all our 2018s so very nicely with their wonderful article, “A Paradigm for Arithmetic Circuit Lower Bounds”! And please do stay tuned for the coming articles in the Complexity Theory Column, namely, Josh Grochow and David H. Wolpert (tentative topic: new complexity questions regarding the thermodynamics of computation; so much more than (ir)reversibility), Lane A. Hemaspaandra and Holger Spakowski (tentative topic: team diagonalization), William Gasarch (not-at-all-tentative topic: the third P versus NP poll), William Gasarch (tentative topic: the muffin problem), and Emanuele Viola (topic: TBD). Yes, you can believe your eyes: The start of 2019 will be a gala “half-year of Bill (Gasarch)”! And please warm up your predicting hats, because in the very next issue of SIGACT News (June 2018) you will find in Bill’s Open Questions Column the poll questions he would like your answers to, as well as his discussion of his (surely provocative) thoughts about those questions. And then the results (based on your answers!) of his poll will appear as Complexity Theory Column #100 in the March 2019 issue of SIGACT News.","PeriodicalId":22106,"journal":{"name":"SIGACT News","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82546286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
According to the author, “the book was written to serve as a first encounter with algorithms.” The book tries to provide an understanding of algorithms that can be commonly encountered by people in different disciplines. The flow of the discussion covers salient points of the algorithms without necessitating a technical deep dive. This makes the book more accessible to people from disciplines other than just Computer Science. The chapter titles are imaginative and serve to hook the interest of the reader. In addition, the chapter titles segue nicely into the discussions per chapter. For example, the first chapter is titled “Stock Spans.” The chapter starts with a discussion of how stock spans are solvable in several ways, depending on the constraints identified. This is a great jumping off point to discussions of how we can determine which algorithms would serve us better. Also the problem is basic enough that a discussion of basic structures fits well.
{"title":"Review of Real-World Algorithms: A Beginner's Guide by Panos Louridas","authors":"Ramon de Vera","doi":"10.1145/3197406.3197410","DOIUrl":"https://doi.org/10.1145/3197406.3197410","url":null,"abstract":"According to the author, “the book was written to serve as a first encounter with algorithms.” The book tries to provide an understanding of algorithms that can be commonly encountered by people in different disciplines. The flow of the discussion covers salient points of the algorithms without necessitating a technical deep dive. This makes the book more accessible to people from disciplines other than just Computer Science. The chapter titles are imaginative and serve to hook the interest of the reader. In addition, the chapter titles segue nicely into the discussions per chapter. For example, the first chapter is titled “Stock Spans.” The chapter starts with a discussion of how stock spans are solvable in several ways, depending on the constraints identified. This is a great jumping off point to discussions of how we can determine which algorithms would serve us better. Also the problem is basic enough that a discussion of basic structures fits well.","PeriodicalId":22106,"journal":{"name":"SIGACT News","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78284303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I entered the field of Computer Science as an undergraduate because I very much enjoyed programming. Of course, there is far more to the discipline than that and, as I studied, I found myself pursuing more esoteric topics, landing for quite a while in the land of computational complexity theory. But programming was, and remains, my first love. And that’s why, once again, I find myself reading and, at times, wrestling with yet another of Don Knuth’s TAOCP fascicles. As I have written before in this column, Knuth is able to combine a more theoretical topic, in this case the satisfiability problem, with practical approaches to solving it, approaches that encourage the reader to write some code. It’s this mix of the theoretical and the practical that I, and I believe many others, find engaging. As we all know, the satisfiability problem (SAT) is NP-complete and is considered the ur-problem of the theory. According to Bill Gasarch’s survey, to which Knuth refers in a footnote on page 1, most feel we are a long way from showing whether P 6= NP. Despite that, many have realized that we can still attack large classes of SAT problems, classes coming from many practical applications, with techniques that work reasonably efficiently. Fascicle 6 is Knuth’s contribution to this and is the next in a series of paperback publications that together will form Volume 4 of “The Art of Computer Programming” (TAOCP). The volume will appear as a trilogy, with Volume 4A already in hardcover. This fascicle will be the middle third of Volume 4B.
{"title":"Review of The Art of Computer Programming Fascicle 6 'Satisfiability' by Donald E. Knuth","authors":"J. Rogers","doi":"10.1145/3197406.3197409","DOIUrl":"https://doi.org/10.1145/3197406.3197409","url":null,"abstract":"I entered the field of Computer Science as an undergraduate because I very much enjoyed programming. Of course, there is far more to the discipline than that and, as I studied, I found myself pursuing more esoteric topics, landing for quite a while in the land of computational complexity theory. But programming was, and remains, my first love. And that’s why, once again, I find myself reading and, at times, wrestling with yet another of Don Knuth’s TAOCP fascicles. As I have written before in this column, Knuth is able to combine a more theoretical topic, in this case the satisfiability problem, with practical approaches to solving it, approaches that encourage the reader to write some code. It’s this mix of the theoretical and the practical that I, and I believe many others, find engaging. As we all know, the satisfiability problem (SAT) is NP-complete and is considered the ur-problem of the theory. According to Bill Gasarch’s survey, to which Knuth refers in a footnote on page 1, most feel we are a long way from showing whether P 6= NP. Despite that, many have realized that we can still attack large classes of SAT problems, classes coming from many practical applications, with techniques that work reasonably efficiently. Fascicle 6 is Knuth’s contribution to this and is the next in a series of paperback publications that together will form Volume 4 of “The Art of Computer Programming” (TAOCP). The volume will appear as a trilogy, with Volume 4A already in hardcover. This fascicle will be the middle third of Volume 4B.","PeriodicalId":22106,"journal":{"name":"SIGACT News","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88284137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The reordering bu↵er problem (or also sorting bu↵er problem) was introduced by Räcke, Sohler, and Westermann in 2002 [14] and has been extensively studied since then. In this problem, a metric space is given1 and a sequence of items arrive online. Each item is associated with a point in the metric space. We allow multiple items to be associated with the same point. An online algorithm can store up to k items in a bu↵er, but once the bu↵er is full, the algorithm has to process at least one of the items stored in the bu↵er. To process an item from the bu↵er, the algorithm moves a single server in the metric space to the point corresponding to that item. The goal is to minimize the total distance that the server has to travel to process the entire input sequence. The problem is reasonably well understood for some metric spaces. For uniform metric spaces for example, a deterministic O( p log k)-competitive algorithm is known, which is close to the lower bound of ⌦( p log k/ log log k) [1]. Similarly, [4] gives a O(log log k)-competitive randomized online algorithm, which is asymptotically tight [1]. For other metric spaces however, the picture is less clear. We will refrain from listing all known results in detail, but there have been a number of papers investigating this online problem for di↵erent metrics spaces and settings [2, 3, 7, 8, 9, 10, 11, 12, 13]. However, in this column, we will focus on line metric spaces. The last notable result for this metric was obtained eleven years ago by Gamzu and Segev [11]. Their main result is a deterministic O(log n)-competitive online algorithm for a line metric space with n evenly spaced points. In the reminder, we will sketch a slightly simplified and improved version of this result.
{"title":"The reordering buffer problem on the line revisited","authors":"Matthias Englert","doi":"10.1145/3197406.3197418","DOIUrl":"https://doi.org/10.1145/3197406.3197418","url":null,"abstract":"The reordering bu↵er problem (or also sorting bu↵er problem) was introduced by Räcke, Sohler, and Westermann in 2002 [14] and has been extensively studied since then. In this problem, a metric space is given1 and a sequence of items arrive online. Each item is associated with a point in the metric space. We allow multiple items to be associated with the same point. An online algorithm can store up to k items in a bu↵er, but once the bu↵er is full, the algorithm has to process at least one of the items stored in the bu↵er. To process an item from the bu↵er, the algorithm moves a single server in the metric space to the point corresponding to that item. The goal is to minimize the total distance that the server has to travel to process the entire input sequence. The problem is reasonably well understood for some metric spaces. For uniform metric spaces for example, a deterministic O( p log k)-competitive algorithm is known, which is close to the lower bound of ⌦( p log k/ log log k) [1]. Similarly, [4] gives a O(log log k)-competitive randomized online algorithm, which is asymptotically tight [1]. For other metric spaces however, the picture is less clear. We will refrain from listing all known results in detail, but there have been a number of papers investigating this online problem for di↵erent metrics spaces and settings [2, 3, 7, 8, 9, 10, 11, 12, 13]. However, in this column, we will focus on line metric spaces. The last notable result for this metric was obtained eleven years ago by Gamzu and Segev [11]. Their main result is a deterministic O(log n)-competitive online algorithm for a line metric space with n evenly spaced points. In the reminder, we will sketch a slightly simplified and improved version of this result.","PeriodicalId":22106,"journal":{"name":"SIGACT News","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85558616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Scalable distributed systems face inherent trade-offs arising from the relatively high cost of exchanging information between computing nodes. Brewer’s CAP (Consistency, Availability, Partition-Tolerance) principle states that when communication becomes impossible between isolated parts of the system (i.e., the network is partitioned), then the system must give up either safety (i.e., sometimes return an incorrect result) or liveness (i.e., sometimes fail to produce a result). Abadi generalized Brewer’s principle by defining the PACELC (if Partition then Availability or Consistency, Else Latency or Consistency) formulation, which captures the observation that the trade-off between safety and liveness is often made in practice even while the network is reliable. Building on Gilbert and Lynch’s formal proof of the CAP principle, this paper presents a formal treatment of Abadi’s formulation and connects this result to a body of prior work on latency bounds for distributed objects.
{"title":"Distributed Computing Column 69 Proving PACELC and Concurrent Computing Summer School","authors":"J. Welch","doi":"10.1145/3197406.3197419","DOIUrl":"https://doi.org/10.1145/3197406.3197419","url":null,"abstract":"Scalable distributed systems face inherent trade-offs arising from the relatively high cost of exchanging information between computing nodes. Brewer’s CAP (Consistency, Availability, Partition-Tolerance) principle states that when communication becomes impossible between isolated parts of the system (i.e., the network is partitioned), then the system must give up either safety (i.e., sometimes return an incorrect result) or liveness (i.e., sometimes fail to produce a result). Abadi generalized Brewer’s principle by defining the PACELC (if Partition then Availability or Consistency, Else Latency or Consistency) formulation, which captures the observation that the trade-off between safety and liveness is often made in practice even while the network is reliable. Building on Gilbert and Lynch’s formal proof of the CAP principle, this paper presents a formal treatment of Abadi’s formulation and connects this result to a body of prior work on latency bounds for distributed objects.","PeriodicalId":22106,"journal":{"name":"SIGACT News","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82963845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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