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ABSTRACT
Priority queues are used in many applications including real-time systems, operating systems, and simulations. Their implementation may have a profound effect on the performance of such applications. In this article, we study the performance of well-known sequential priority queue implementations and the recently proposed parallel access priority queues. To accurately assess the performance of a priority queue, the performance measurement methodology must be appropriate. We use the Classic Hold, the Markov Model, and an Up/Down access pattern to measure performance and look at both the average access time and the worst-case time that are of vital interest to real-tiem applicatons. Our results suggest that the best choice for priority queue algorithms depends heavily on the application. For queue sizes smaller than 1,000 elements, the Splay Tree, the Skew Heap, and Henriksen's algorithm show good average access times. For large queue sized of 5,000 elements or more, the Calendar Queue and the Lazy Queue offer good average access times but have very long worst-case access times. The Skew Heap and the splay Tree exhibit the best worst-case access times. Among the parallel access priority queues tested, the Parallel Access Skew Heap provides the best performance on small shares memory multiprocessors.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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1
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AHMED, H., RONNGREN, R., AND AYANI, R. 1994. Impact of event scheduling in time warp parallel simulations. In Proceedings of the 27th Annual Hawaii International Conference on System Sciences, Vol II, 455-463.
|
| |
2
|
AYANI, R. 1990. LR-algorithm: Concurrent operations on priority queues. In Proceedings of the Second IEEE Symposium on Parallel and Distributed Systems, 22-25.
|
| |
3
|
BAYER, R. AND SCHKOLNIK, M. 1977. Concurrency of operations on B-trees. Acta Inf. 9, 1-22.
|
 |
4
|
|
| |
5
|
BISWAS, B. AND BROWNE, g.C. 1987. Simultaneous update of priority structures. In Proceedings of the 1987 International Conference on Parallel Processing, 17-21.
|
 |
6
|
|
 |
7
|
|
| |
8
|
Christopher D. Carothers , Richard Fujimoto , Yi-Bing Lin , Paul England, Distributed Simulation of Large-Scale PCS Networks, Proceedings of the Second International Workshop on Modeling, Analysis, and Simulation On Computer and Telecommunication Systems, p.2-6, January 31-February 02, 1994
|
| |
9
|
|
| |
10
|
COMFORT, J.C. 1984. The simulation of a master-slave event set processor. Simulation 42, 3 (March), 117-124.
|
 |
11
|
|
| |
12
|
Samir Das , Richard Fujimoto , Kiran Panesar , Don Allison , Maria Hybinette, GTW: a time warp system for shared memory multiprocessors, Proceedings of the 26th conference on Winter simulation, p.1332-1339, December 11-14, 1994, Orlando, Florida, United States
|
| |
13
|
ELLIS, C. S. 1980. Concurrent search and insertion in AVL trees. IEEE Trans. Comput. C-29, 9 (Sept.), 811-817.
|
 |
14
|
|
 |
15
|
|
| |
16
|
|
 |
17
|
|
 |
18
|
|
 |
19
|
|
 |
20
|
Douglas W. Jones , James O. Henriksen , Robert M. O'Keefe , C. Dennis Pegden , Robert G. Sargent , Brian W. Unger, Implementations of time (panel), Proceedings of the 18th conference on Winter simulation, p.409-416, December 08-10, 1986, Washington, D.C., United States
[doi> 10.1145/318242.318467]
|
 |
21
|
|
| |
22
|
|
| |
23
|
|
 |
24
|
|
 |
25
|
|
 |
26
|
|
 |
27
|
|
| |
28
|
OBAL, W. D. AND SANDERS, W. H.1994. Importance sampling simulation in UltraSAN. Simulation 62, 2 (Feb.), 98-111.
|
 |
29
|
|
 |
30
|
|
| |
31
|
|
| |
32
|
RIBOE, J. 1991. The camel distribution. Tech. Rep. TRITA-TCS-9104, Dept. of Teleinformatics, The Royal Institute of Technology, Stockholm.
|
 |
33
|
Robert Rönngren , Rassul Ayani , Richard M. Fujimoto , Samir R. Das, Efficient implementation of event sets in Time Warp, Proceedings of the seventh workshop on Parallel and distributed simulation, p.101-108, May 16-19, 1993, San Diego, California, United States
|
| |
34
|
RONNGREN, R., RIBOE, J., AND AYANI, R. 1993a. Lazy queue: New approach to implementing the pending event set. Int. J. Comput. Simul. 3, 303-332.
|
| |
35
|
|
 |
36
|
|
| |
37
|
|
| |
38
|
STEINMAN, J.S. 1992. SPEEDES: A unified approach to parallel simulation. In Proceedings of the Sixth Workshop on Parallel and Distributed Simulation, Vol. 24, No. 3, 75-84.
|
 |
39
|
|
| |
40
|
TARJAN, R.E. 1985. Amortized computational complexity. SIAM J. Algebraic Discrete Meth. 6, 2 (April), 306-318.
|
| |
41
|
UNGER, B. W., GOETZ, D. J., AND MARYKA, S.W. 1994. Simulation of SS7 common channel signaling. IEEE Commun. Mag. 32, 3 (March), 52-62.
|
| |
42
|
VAUCHER, J. G. 1977. On the distribution of event times for the notices in a simulation event list. INFOR 15, 2 (June), 171-182.
|
 |
43
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CITED BY 13
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Christopher D. Carothers , Kalyan S. Perumalla , Richard M. Fujimoto, The effect of state-saving in optimistic simulation on a cache-coherent non-uniform memory access architecture, Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future, p.1624-1633, December 05-08, 1999, Phoenix, Arizona, United States
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REVIEW
"Pradip K. Srimani : Reviewer"
The priority queue is an important data structure that is essential
to the design of many system programs, such as operating systems, as
well as to the design of many applications, such as simulations. In
fact, priority queues must be used whe
more...
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