The LevelArray: A Fast, Practical Long-Lived Renaming Algorithm
| Autor: | Dan Alistarh, Nir Shavit, Justin Kopinsky, Alexander Matveev |
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| Přispěvatelé: | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Kopinsky, Justin, Matveev, Alexander, Shavit, Nir N. |
| Rok vydání: | 2014 |
| Předmět: |
FOS: Computer and information sciences
Computer science Hash function Register renaming Transactional memory Thread (computing) Parallel computing Data structure Randomized algorithm Computer Science - Distributed Parallel and Cluster Computing Shared memory Computer Science - Data Structures and Algorithms Data Structures and Algorithms (cs.DS) Distributed Parallel and Cluster Computing (cs.DC) Algorithm |
| Zdroj: | ICDCS MIT web domain |
| DOI: | 10.1109/icdcs.2014.43 |
| Popis: | The long-lived renaming problem appears in shared-memory systems where a set of threads need to register and deregister frequently from the computation, while concurrent operations scan the set of currently registered threads. Instances of this problem show up in concurrent implementations of transactional memory, flat combining, thread barriers, and memory reclamation schemes for lock-free data structures. In this paper, we analyze a randomized solution for long-lived renaming. The algorithmic technique we consider, called the Level Array, has previously been used for hashing and one-shot (single-use) renaming. Our main contribution is to prove that, in long-lived executions, where processes may register and deregister polynomially many times, the technique guarantees constant steps on average and O (log log n) steps with high probability for registering, unit cost for deregistering, and O (n) steps for collect queries, where n is an upper bound on the number of processes that may be active at any point in time. We also show that the algorithm has the surprising property that it is self-healing: under reasonable assumptions on the schedule, operations running while the data structure is in a degraded state implicitly help the data structure re-balance itself. This subtle mechanism obviates the need for expensive periodic rebuilding procedures. Our benchmarks validate this approach, showing that, for typical use parameters, the average number of steps a process takes to register is less than two and the worst-case number of steps is bounded by six, even in executions with billions of operations. We contrast this with other randomized implementations, whose worst-case behavior we show to be unreliable, and with deterministic implementations, whose cost is linear in n. National Science Foundation (U.S.) (Grant CCF-1217921) National Science Foundation (U.S.) (Grant CCF-1301926) United States. Dept. of Energy (Advanced Scientific Computing Research Grant ER26116/DE-SC0008923) Oracle Corporation Intel Corporation |
| Databáze: | OpenAIRE |
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