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This paper presents a parallelization of the Constraint Programming solver OR-Tools, using the parallel framework Bobpp. The principle of the parallelization is to assign one sequential OR-Tools solver per core and to communicate work or nodes using the Bobpp global priority queue. As usual the communication or migration of work between solvers is a kind of Work Stealing. But here we have to deal...
Optimization methods generally do not fall into the most suitable algorithms for parallelization on a GPU. However, a relatively good efficiency still can be obtained if the method is properly adapted to the GPU programming model, which is the case for dynamic programming. In this article, we propose a parallelization strategy for thread grouping for dynamic programming in CUDA. We show that parametrizing...
We study in this paper the influence of the restart policy on the sequential and parallel performance of combinatorial search problems. Our evaluation relies on several experiments using a constraint-based local search method, named Adaptive Search, and a few combinatorial problems such as Magic Square and Costas Array Problems.
This paper describes the incorporation of the IEEE-TCPP Curriculum Initiative into CS 2 at the University of Illinois at Urbana-Champaign. With control over only one course that requires a semi-rigid curriculum, we detail a sequence of three lessons that explore the basics of parallelism in a visual manner. We draw a contrast between standard teaching methods for parallelism and assert that our approach...
As the importance of parallel and distributed computing (PDC) continues to increase, there is great need to introduce core PDC topics very early in the study of computer science. Even students with absolutely no prior programming experience, and perhaps little expectation of long-term computer science study, need hands-on level-appropriate experience with PDC topics in order to be well-educated in...
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