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MULTILISP: a language for concurrent symbolic computation
ACM Transactions on Programming Languages and Systems (TOPLAS)
On maintaining dynamic information in a concurrent environment
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The Crystal Multicomputer: Design and Implementation Experience
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An Algorithm for Finding Best Matches in Logarithmic Expected Time
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Anomalies in parallel branch-and-bound algorithms
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Design and implementation of a distributed systems language (crystal, charlotte, lynx, soda)
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YACKOS on a shared-memory multiprocessor
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Strategies for decentralized resource management
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ACM Computing Surveys (CSUR)
High level support for divide-and-conquer parallelism
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Cilk: an efficient multithreaded runtime system
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Distributed Shared Abstractions (DSA) on Multiprocessors
IEEE Transactions on Software Engineering
Thread scheduling for multiprogrammed multiprocessors
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ATLAS: an infrastructure for global computing
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Parallel interval-Newton using message passing: dynamic load balancing strategies
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State of the Art in Parallel Search Techniques for Discrete Optimization Problems
IEEE Transactions on Knowledge and Data Engineering
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IEEE Transactions on Parallel and Distributed Systems
On the Efficiency of Parallel Backtracking
IEEE Transactions on Parallel and Distributed Systems
Unstructured Tree Search on SIMD Parallel Computers
IEEE Transactions on Parallel and Distributed Systems
Asynchronous Random Polling Dynamic Load Balancing
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Dynamic Load Balancing for the Distributed Mining of Molecular Structures
IEEE Transactions on Parallel and Distributed Systems
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Decentralized load balancing for highly irregular search problems
Microprocessors & Microsystems
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Adaptive work-stealing with parallelism feedback
ACM Transactions on Computer Systems (TOCS)
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Journal of Parallel and Distributed Computing
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Parallel Computing
Using memory mapping to support cactus stacks in work-stealing runtime systems
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Future Generation Computer Systems
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DIB is a general-purpose package that allows a wide range of applications such as recursive backtrack, branch and bound, and alpha-beta search to be implemented on a multicomputer. It is very easy to use. The application program needs to specify only the root of the recursion tree, the computation to be performed at each node, and how to generate children at each node. In addition, the application program may optionally specify how to synthesize values of tree nodes from their children's values and how to disseminate information (such as bounds) either globally or locally in the tree. DIB uses a distributed algorithm, transparent to the application programmer, that divides the problem into subproblems and dynamically allocates them to any number of (potentially nonhomogeneous) machines. This algorithm requires only minimal support from the distributed operating system. DIB can recover from failures of machines even if they are not detected. DIB currently runs on the Crystal multicomputer at the University of Wisconsin-Madison. Many applications have been implemented quite easily, including exhaustive traversal (N queens, knight's tour, negamax tree evaluation), branch and bound (traveling salesman) and alpha-beta search (the game of NIM). Speedup is excellent for exhaustive traversal and quite good for branch and bound.