DIB—a distributed implementation of backtracking

Abstract

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.

Cilk: An Efficient Multithreaded Runtime System

“…First, to lower communication costs, we would like to steal large amounts of work, and in a tree-structured computation, shallow threads are likely to spawn more work than deep ones. This heuristic notion is the justification cited by earlier researchers [8,15,21,35,43] who proposed stealing work that is shallow in the spawn tree. We cannot, however, prove that shallow threads are more likely to spawn work than deep ones.…”

“…Cilk' s scheduler uses the technique of work stealing [4,8,14,15,16,21,29,30,31,37,43] in which a processor (the thief) who runs out of work selects another processor (the victim) from whom to steal work, and then steals the shallowest ready thread in the victim's spawn tree. Cilk' s strategy is for thieves to choose victims at random [4,29,40].…”

“…With P processors, the execution time cannot be less than T 1 =P or less than T 1 . The Cilk scheduler uses "work stealing" [4,8,14,15,16,21,29,30,31,37,43] to achieve execution time very near to the sum of these two measures. Off-line techniques for computing such efficient schedules have been known for a long time [6,18,19], but this efficiency has been difficult to achieve on-line in a distributed environment while simultaneously using small amounts of space and communication.…”

DPSA: Deterministic Parallel Search Algorithm in Large Database

“…This process continues until all processors go idle or a solution is found. Finkel and Manber (1987) have presented the performance results of PDFS for a number of problems such as traveling salesman problem and other problems. Monien and Vornberger (1987) showed that a linear speedup can be obtained to solve combinatorial problems using parallelism.…”

Persistent Fault-Tolerance for Divide-and-Conquer Applications on the Grid

“…In the DIB system [11], processors redo work of other processors even if no crash has been detected. Redoing occurs while a processor waits for its steal request being granted.…”