A fast mutual exclusion algorithm
ACM Transactions on Computer Systems (TOCS)
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ACM Transactions on Computer Systems (TOCS)
Improving fast mutual exclusion
PODC '92 Proceedings of the eleventh annual ACM symposium on Principles of distributed computing
Speeding Lamport's fast mutual exclusion algorithm
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Adaptive and efficient mutual exclusion (extended abstract)
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Adaptive solutions to the mutual exclusion problem
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Adaptive mutual exclusion with local spinning
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Lamport on mutual exclusion: 27 years of planting seeds
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Proceedings of the twenty-first annual symposium on Principles of distributed computing
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Tight RMR lower bounds for mutual exclusion and other problems
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
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Theoretical Computer Science
Adaptive mutual exclusion with local spinning
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Fast randomized test-and-set and renaming
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A study of shared-memory mutual exclusion protocols using CADP
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Read/Write based fast-path transformation for FCFS mutual exclusion
SOFSEM'05 Proceedings of the 31st international conference on Theory and Practice of Computer Science
A practical single-register wait-free mutual exclusion algorithm on asynchronous networks
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A tight RMR lower bound for randomized mutual exclusion
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
Brief announcement: a tight RMR lower bound for randomized mutual exclusion
PODC '12 Proceedings of the 2012 ACM symposium on Principles of distributed computing
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Proceedings of the 2013 ACM symposium on Principles of distributed computing
A practical wait-free simulation for lock-free data structures
Proceedings of the 19th ACM SIGPLAN symposium on Principles and practice of parallel programming
Computing with infinitely many processes
Information and Computation
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We present the first adaptive algorithm for N-process mutual exclusion under read/write atomicity in which all busy waiting is by local spinning. In our algorithm, each process p performs O(min(k, log N)) remote memory references to enter and exit. its critical section, where k is the maximum "point contention" experienced by p. The space complexity of our algorithm is 驴(N), which is clearly optimal.