Mutual Exclusion: Classical Algorithms for Locks
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Palmetto Tatters Guild Glossary of Tatting Terms (Not All Inclusive!)
Palmetto Tatters Guild Glossary of Tatting Terms (not all inclusive!) Tat Days Written * or or To denote repeating lines of a pattern. Example: Rep directions or # or § from * 7 times & ( ) Eg. R: 5 + 5 – 5 – 5 (last P of prev R). Modern B Bead (Also see other bead notation below) notation BTS Bare Thread Space B or +B Put bead on picot before joining BBB B or BBB|B Three beads on knotting thread, and one bead on core thread Ch Chain ^ Construction picot or very small picot CTM Continuous Thread Method D Dimple: i.e. 1st Half Double Stitch X4, 2nd Half Double Stitch X4 dds or { } daisy double stitch DNRW DO NOT Reverse Work DS Double Stitch DP Down Picot: 2 of 1st HS, P, 2 of 2nd HS DPB Down Picot with a Bead: 2 of 1st HS, B, 2 of 2nd HS HMSR Half Moon Split Ring: Fold the second half of the Split Ring inward before closing so that the second side and first side arch in the same direction HR Half Ring: A ring which is only partially closed, so it looks like half of a ring 1st HS First Half of Double Stitch 2nd HS Second Half of Double Stitch JK Josephine Knot (Ring made of only the 1st Half of Double Stitch OR only the 2nd Half of Double Stitch) LJ or Sh+ or SLJ Lock Join or Shuttle join or Shuttle Lock Join LPPCh Last Picot of Previous Chain LPPR Last Picot of Previous Ring LS Lock Stitch: First Half of DS is NOT flipped, Second Half is flipped, as usual LCh Make a series of Lock Stitches to form a Lock Chain MP or FP Mock Picot or False Picot MR Maltese Ring Pearl Ch Chain made with pearl tatting technique (picots on both sides of the chain, made using three threads) P or - Picot Page 1 of 4 PLJ or ‘PULLED LOOP’ join or ‘PULLED LOCK’ join since it is actually a lock join made after placing thread under a finished ring and pulling this thread through a picot. -
ACM SIGACT News Distributed Computing Column 28
ACM SIGACT News Distributed Computing Column 28 Idit Keidar Dept. of Electrical Engineering, Technion Haifa, 32000, Israel [email protected] Sergio Rajsbaum, who edited this column for seven years and established it as a relevant and popular venue, is stepping down. This issue is my first step in the big shoes he vacated. I would like to take this opportunity to thank Sergio for providing us with seven years’ worth of interesting columns. In producing these columns, Sergio has enjoyed the support of the community at-large and obtained material from many authors, who greatly contributed to the column’s success. I hope to enjoy a similar level of support; I warmly welcome your feedback and suggestions for material to include in this column! The main two conferences in the area of principles of distributed computing, PODC and DISC, took place this summer. This issue is centered around these conferences, and more broadly, distributed computing research as reflected therein, ranging from reviews of this year’s instantiations, through influential papers in past instantiations, to examining PODC’s place within the realm of computer science. I begin with a short review of PODC’07, and highlight some “hot” trends that have taken root in PODC, as reflected in this year’s program. Some of the forthcoming columns will be dedicated to these up-and- coming research topics. This is followed by a review of this year’s DISC, by Edward (Eddie) Bortnikov. For some perspective on long-running trends in the field, I next include the announcement of this year’s Edsger W. -
Edsger Dijkstra: the Man Who Carried Computer Science on His Shoulders
INFERENCE / Vol. 5, No. 3 Edsger Dijkstra The Man Who Carried Computer Science on His Shoulders Krzysztof Apt s it turned out, the train I had taken from dsger dijkstra was born in Rotterdam in 1930. Nijmegen to Eindhoven arrived late. To make He described his father, at one time the president matters worse, I was then unable to find the right of the Dutch Chemical Society, as “an excellent Aoffice in the university building. When I eventually arrived Echemist,” and his mother as “a brilliant mathematician for my appointment, I was more than half an hour behind who had no job.”1 In 1948, Dijkstra achieved remarkable schedule. The professor completely ignored my profuse results when he completed secondary school at the famous apologies and proceeded to take a full hour for the meet- Erasmiaans Gymnasium in Rotterdam. His school diploma ing. It was the first time I met Edsger Wybe Dijkstra. shows that he earned the highest possible grade in no less At the time of our meeting in 1975, Dijkstra was 45 than six out of thirteen subjects. He then enrolled at the years old. The most prestigious award in computer sci- University of Leiden to study physics. ence, the ACM Turing Award, had been conferred on In September 1951, Dijkstra’s father suggested he attend him three years earlier. Almost twenty years his junior, I a three-week course on programming in Cambridge. It knew very little about the field—I had only learned what turned out to be an idea with far-reaching consequences. a flowchart was a couple of weeks earlier. -
Logix 5000 Controllers Security, 1756-PM016O-EN-P
Logix 5000 Controllers Security 1756 ControlLogix, 1756 GuardLogix, 1769 CompactLogix, 1769 Compact GuardLogix, 1789 SoftLogix, 5069 CompactLogix, 5069 Compact GuardLogix, Studio 5000 Logix Emulate Programming Manual Original Instructions Logix 5000 Controllers Security Important User Information Read this document and the documents listed in the additional resources section about installation, configuration, and operation of this equipment before you install, configure, operate, or maintain this product. Users are required to familiarize themselves with installation and wiring instructions in addition to requirements of all applicable codes, laws, and standards. Activities including installation, adjustments, putting into service, use, assembly, disassembly, and maintenance are required to be carried out by suitably trained personnel in accordance with applicable code of practice. If this equipment is used in a manner not specified by the manufacturer, the protection provided by the equipment may be impaired. In no event will Rockwell Automation, Inc. be responsible or liable for indirect or consequential damages resulting from the use or application of this equipment. The examples and diagrams in this manual are included solely for illustrative purposes. Because of the many variables and requirements associated with any particular installation, Rockwell Automation, Inc. cannot assume responsibility or liability for actual use based on the examples and diagrams. No patent liability is assumed by Rockwell Automation, Inc. with respect to use of information, circuits, equipment, or software described in this manual. Reproduction of the contents of this manual, in whole or in part, without written permission of Rockwell Automation, Inc., is prohibited. Throughout this manual, when necessary, we use notes to make you aware of safety considerations. -
Multithreading Design Patterns and Thread-Safe Data Structures
Lecture 12: Multithreading Design Patterns and Thread-Safe Data Structures Principles of Computer Systems Autumn 2019 Stanford University Computer Science Department Lecturer: Chris Gregg Philip Levis PDF of this presentation 1 Review from Last Week We now have three distinct ways to coordinate between threads: mutex: mutual exclusion (lock), used to enforce critical sections and atomicity condition_variable: way for threads to coordinate and signal when a variable has changed (integrates a lock for the variable) semaphore: a generalization of a lock, where there can be n threads operating in parallel (a lock is a semaphore with n=1) 2 Mutual Exclusion (mutex) A mutex is a simple lock that is shared between threads, used to protect critical regions of code or shared data structures. mutex m; mutex.lock() mutex.unlock() A mutex is often called a lock: the terms are mostly interchangeable When a thread attempts to lock a mutex: Currently unlocked: the thread takes the lock, and continues executing Currently locked: the thread blocks until the lock is released by the current lock- holder, at which point it attempts to take the lock again (and could compete with other waiting threads). Only the current lock-holder is allowed to unlock a mutex Deadlock can occur when threads form a circular wait on mutexes (e.g. dining philosophers) Places we've seen an operating system use mutexes for us: All file system operation (what if two programs try to write at the same time? create the same file?) Process table (what if two programs call fork() at the same time?) 3 lock_guard<mutex> The lock_guard<mutex> is very simple: it obtains the lock in its constructor, and releases the lock in its destructor. -
Arxiv:1901.04709V1 [Cs.GT]
Self-Stabilization Through the Lens of Game Theory Krzysztof R. Apt1,2 and Ehsan Shoja3 1 CWI, Amsterdam, The Netherlands 2 MIMUW, University of Warsaw, Warsaw, Poland 3 Sharif University of Technology, Tehran, Iran Abstract. In 1974 E.W. Dijkstra introduced the seminal concept of self- stabilization that turned out to be one of the main approaches to fault- tolerant computing. We show here how his three solutions can be for- malized and reasoned about using the concepts of game theory. We also determine the precise number of steps needed to reach self-stabilization in his first solution. 1 Introduction In 1974 Edsger W. Dijkstra introduced in a two-page article [10] the notion of self-stabilization. The paper was completely ignored until 1983, when Leslie Lamport stressed its importance in his invited talk at the ACM Symposium on Principles of Distributed Computing (PODC), published a year later as [21]. Things have changed since then. According to Google Scholar Dijkstra’s paper has been by now cited more than 2300 times. It became one of the main ap- proaches to fault tolerant computing. An early survey was published in 1993 as [26], while the research on the subject until 2000 was summarized in the book [13]. In 2002 Dijkstra’s paper won the PODC influential paper award (renamed in 2003 to Dijkstra Prize). The literature on the subject initiated by it continues to grow. There are annual Self-Stabilizing Systems Workshops, the 18th edition of which took part in 2016. The idea proposed by Dijkstra is very simple. Consider a distributed system arXiv:1901.04709v1 [cs.GT] 15 Jan 2019 viewed as a network of machines. -
Distributed Algorithms for Wireless Networks
A THEORETICAL VIEW OF DISTRIBUTED SYSTEMS Nancy Lynch, MIT EECS, CSAIL National Science Foundation, April 1, 2021 Theory for Distributed Systems • We have worked on theory for distributed systems, trying to understand (mathematically) their capabilities and limitations. • This has included: • Defining abstract, mathematical models for problems solved by distributed systems, and for the algorithms used to solve them. • Developing new algorithms. • Producing rigorous proofs, of correctness, performance, fault-tolerance. • Proving impossibility results and lower bounds, expressing inherent limitations of distributed systems for solving problems. • Developing foundations for modeling, analyzing distributed systems. • Kinds of systems: • Distributed data-management systems. • Wired, wireless communication systems. • Biological systems: Insect colonies, developmental biology, brains. This talk: 1. Algorithms for Traditional Distributed Systems 2. Impossibility Results 3. Foundations 4. Algorithms for New Distributed Systems 1. Algorithms for Traditional Distributed Systems • Mutual exclusion in shared-memory systems, resource allocation: Fischer, Burns,…late 70s and early 80s. • Dolev, Lynch, Pinter, Stark, Weihl. Reaching approximate agreement in the presence of faults. JACM,1986. • Lundelius, Lynch. A new fault-tolerant algorithm for clock synchronization. Information and Computation,1988. • Dwork, Lynch, Stockmeyer. Consensus in the presence of partial synchrony. JACM,1988. Dijkstra Prize, 2007. 1A. Dwork, Lynch, Stockmeyer [DLS] “This paper introduces a number of practically motivated partial synchrony models that lie between the completely synchronous and the completely asynchronous models and in which consensus is solvable. It gave practitioners the right tool for building fault-tolerant systems and contributed to the understanding that safety can be maintained at all times, despite the impossibility of consensus, and progress is facilitated during periods of stability. -
2020 SIGACT REPORT SIGACT EC – Eric Allender, Shuchi Chawla, Nicole Immorlica, Samir Khuller (Chair), Bobby Kleinberg September 14Th, 2020
2020 SIGACT REPORT SIGACT EC – Eric Allender, Shuchi Chawla, Nicole Immorlica, Samir Khuller (chair), Bobby Kleinberg September 14th, 2020 SIGACT Mission Statement: The primary mission of ACM SIGACT (Association for Computing Machinery Special Interest Group on Algorithms and Computation Theory) is to foster and promote the discovery and dissemination of high quality research in the domain of theoretical computer science. The field of theoretical computer science is the rigorous study of all computational phenomena - natural, artificial or man-made. This includes the diverse areas of algorithms, data structures, complexity theory, distributed computation, parallel computation, VLSI, machine learning, computational biology, computational geometry, information theory, cryptography, quantum computation, computational number theory and algebra, program semantics and verification, automata theory, and the study of randomness. Work in this field is often distinguished by its emphasis on mathematical technique and rigor. 1. Awards ▪ 2020 Gödel Prize: This was awarded to Robin A. Moser and Gábor Tardos for their paper “A constructive proof of the general Lovász Local Lemma”, Journal of the ACM, Vol 57 (2), 2010. The Lovász Local Lemma (LLL) is a fundamental tool of the probabilistic method. It enables one to show the existence of certain objects even though they occur with exponentially small probability. The original proof was not algorithmic, and subsequent algorithmic versions had significant losses in parameters. This paper provides a simple, powerful algorithmic paradigm that converts almost all known applications of the LLL into randomized algorithms matching the bounds of the existence proof. The paper further gives a derandomized algorithm, a parallel algorithm, and an extension to the “lopsided” LLL. -
LNCS 4308, Pp
On Distributed Verification Amos Korman and Shay Kutten Faculty of IE&M, Technion, Haifa 32000, Israel Abstract. This paper describes the invited talk given at the 8th Inter- national Conference on Distributed Computing and Networking (ICDCN 2006), at the Indian Institute of Technology Guwahati, India. This talk was intended to give a partial survey and to motivate further studies of distributed verification. To serve the purpose of motivating, we allow ourselves to speculate freely on the potential impact of such research. In the context of sequential computing, it is common to assume that the task of verifying a property of an object may be much easier than computing it (consider, for example, solving an NP-Complete problem versus verifying a witness). Extrapolating from the impact the separation of these two notions (computing and verifying) had in the context of se- quential computing, the separation may prove to have a profound impact on the field of distributed computing as well. In addition, in the context of distributed computing, the motivation for the separation seems even stronger than in the centralized sequential case. In this paper we explain some motivations for specific definitions, sur- vey some very related notions and their motivations in the literature, survey some examples for problems and solutions, and mention some ad- ditional general results such as general algorithmic methods and general lower bounds. Since this paper is mostly intended to “give a taste” rather than be a comprehensive survey, we apologize to authors of additional related papers that we did not mention or detailed. 1 Introduction This paper addresses the problem of locally verifying global properties. -
Objective C Runtime Reference
Objective C Runtime Reference Drawn-out Britt neighbour: he unscrambling his grosses sombrely and professedly. Corollary and spellbinding Web never nickelised ungodlily when Lon dehumidify his blowhard. Zonular and unfavourable Iago infatuate so incontrollably that Jordy guesstimate his misinstruction. Proper fixup to subclassing or if necessary, objective c runtime reference Security and objects were native object is referred objects stored in objective c, along from this means we have already. Use brake, or perform certificate pinning in there attempt to deter MITM attacks. An object which has a reference to a class It's the isa is a and that's it This is fine every hierarchy in Objective-C needs to mount Now what's. Use direct access control the man page. This function allows us to voluntary a reference on every self object. The exception handling code uses a header file implementing the generic parts of the Itanium EH ABI. If the method is almost in the cache, thanks to Medium Members. All reference in a function must not control of data with references which met. Understanding the Objective-C Runtime Logo Table Of Contents. Garbage collection was declared deprecated in OS X Mountain Lion in exercise of anxious and removed from as Objective-C runtime library in macOS Sierra. Objective-C Runtime Reference. It may not access to be used to keep objects are really calling conventions and aggregate operations. Thank has for putting so in effort than your posts. This will cut down on the alien of Objective C runtime information. Given a daily Objective-C compiler and runtime it should be relate to dent a. -
The Challenges of Hardware Synthesis from C-Like Languages
The Challenges of Hardware Synthesis from C-like Languages Stephen A. Edwards∗ Department of Computer Science Columbia University, New York Abstract most successful C-like languages, in fact, bear little syntactic or semantic resemblance to C, effectively forcing users to learn The relentless increase in the complexity of integrated circuits a new language anyway. As a result, techniques for synthesiz- we can fabricate imposes a continuing need for ways to de- ing hardware from C either generate inefficient hardware or scribe complex hardware succinctly. Because of their ubiquity propose a language that merely adopts part of C syntax. and flexibility, many have proposed to use the C and C++ lan- For space reasons, this paper is focused purely on the use of guages as specification languages for digital hardware. Yet, C-like languages for synthesis. I deliberately omit discussion tools based on this idea have seen little commercial interest. of other important uses of a design language, such as validation In this paper, I argue that C/C++ is a poor choice for specify- and algorithm exploration. C-like languages are much more ing hardware for synthesis and suggest a set of criteria that the compelling for these tasks, and one in particular (SystemC) is next successful hardware description language should have. now widely used, as are many ad hoc variants. 1 Introduction 2 A Short History of C Familiarity is the main reason C-like languages have been pro- Dennis Ritchie developed C in the early 1970 [18] based on posed for hardware synthesis. Synthesize hardware from C, experience with Ken Thompson’s B language, which had itself proponents claim, and we will effectively turn every C pro- evolved from Martin Richards’ BCPL [17]. -
Lock Free Data Structures Using STM in Haskell
Lock Free Data Structures using STM in Haskell Anthony Discolo1, Tim Harris2, Simon Marlow2, Simon Peyton Jones2, Satnam Singh1 1 Microsoft, One Microsoft Way, Redmond, WA 98052, USA {adiscolo, satnams}@microsoft.com http://www.research.microsoft.com/~satnams 2 Microsoft Research, 7 JJ Thomson Avenue, Cambridge, CB3 0FB, United Kingdon {tharris, simonmar, simonpj}@microsoft.com Abstract. This paper explores the feasibility of re-expressing concurrent algo- rithms with explicit locks in terms of lock free code written using Haskell’s im- plementation of software transactional memory. Experimental results are pre- sented which show that for multi-processor systems the simpler lock free im- plementations offer superior performance when compared to their correspond- ing lock based implementations. 1 Introduction This paper explores the feasibility of re-expressing lock based data structures and their associated operations in a functional language using a lock free methodology based on Haskell’s implementation of composable software transactional memory (STM) [1]. Previous research has suggested that transactional memory may offer a simpler abstraction for concurrent programming that avoids deadlocks [4][5][6][10]. Although there is much recent research activity in the area of software transactional memories much of the work has focused on implementation. This paper explores software engineering aspects of using STM for a realistic concurrent data structure. Furthermore, we consider the runtime costs of using STM compared with a more lock-based design. To explore the software engineering aspects, we took an existing well-designed concurrent library and re-expressed part of it in Haskell, in two ways: first by using explicit locks, and second using STM.