Lawrence A. Crowl, Mark E. Crovella, Thomas J. LeBlanc, Michael L. Scott  Home/Search
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Abstract: Applications typically have several potential sources of parallelism, and in choosing a particular parallelization, the programmer must balance the benefits of each source of parallelism with the corresponding overhead. The tradeoffs are often difficult to analyze, as they may depend on the hardware architecture, software environment, input data, and properties of the algorithm. An example of this dilemma occurs in a wide range of problems that involve processing trees, wherein processors... (Update)
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.... the structure of the input dataset, the specific problem definition, the number of processors used, and the particular machine used [10]. Exploring each of these environmental factors fully requires the predictive power of modeling; it is simply impractical to measure the...
.... pixels in an image, or the connectivity of an input graph all are significant runtime factors; we have shown in previous work [Crowl et al. 1994] that factors such as these can be quite important in finding the proper implementation for a parallel program. To model the...
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BibTeX entry: (Update)
Crowl, L., Crovella, M., LeBlanc, T., and Scott, M. The advantages of multiple parallelizations in combinatorial search. Journal of Parallel and Distributed Computing 21 (1994), 110--123. http://citeseer.ist.psu.edu/crowl94advantages.html More
@article{ crowl94advantages,
author = "Lawrence A. Crowl and Mark E. Crovella and Thomas J. LeBlanc and Michael L. Scott",
title = "The advantages of multiple parallelizations in combinatorial search",
journal = "Journal of Parallel and Distributed Computing",
volume = "21",
number = "1",
pages = "110--123",
year = "1994",
url = "citeseer.ist.psu.edu/crowl94advantages.html" }
Citations (may not include all citations):138 SPLASH: Stanford Parallel Applications for Shared-Memory (context) - Singh, Weber et al. - 1992
130 Implementation of a Portable Nested Data-Parallel Language - Blelloch, Chatterjee et al. - 1993
121 Using Processor Affinity in Loop Scheduling on Shared-Memory.. - Markatos, LeBlanc - 1992
51 Parallel Depth-First Search (context) - Rao, Kumar - 1989
40 Chores: Enhanced Run-Time Support for Shared-Memory Parallel.. (context) - Eager, Zahorjan - 1993
35 DIB --- A Distributed Implementation of Backtracking (context) - Finkel, Manber - 1987
31 An Algorithm for Subgraph Isomorphism (context) - Ullman - 1976
26 Multiprocessing of Combinatorial Search Problems (context) - Wah, Li et al. - 1985
18 the Efficiency of Parallel Backtracking - Rao, Kumar - 1993
13 Programming Task and Data Parallelism on a Multicomputer (context) - Subhlok, Stichnoth et al. - 1993
13 Performance Debugging using Parallel Performance Predicates - Crovella, LeBlanc - 1993
8 A Critique of the Programming Language C - Tichy, Phillippsen et al. - 1992
4 Compiling Nested Data-Parallel Programs for SharedMemory Mul.. - Chatterjee - 1993
4 Parallel Programming with Control Abstraction - Crowl, LeBlanc - 1993
2 Subgraph Isomorphism on the BBN Butterfly Multiprocessor (context) - Costanzo, Crowl et al. - 1986
1 An Empirical Study of Parallel Search for Constraint Satisfa.. (context) - Natarajan - 1987
1 Performance Measurements of Scheduling Strategies and Parall.. (context) - Chen, Daglass et al. - 1984
1 Control Abstraction in Parallel Programming Languages - Crowl, LeBlanc - 1992
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