A code for simulating the solidi cation of a pure material from its undercooled melt based on a phase eld approach has been written for parallel distributed memory architectures using MPI. The numerical scheme is based on nite di erences and results in large sparse non-linear systems which are solved by a backtracking line search modi cation of Newton's method combined with GMRES. Experiments c...

Empirical evidence indicates that the most successful backtracking algorithms for solving constraint satisfaction problems do some level of forward constraint propagation. That is they check constraints against the as yet uninstantiated variables in the search tree. Two popular examples are the forward checking and maintaining arc-consistency algorithms. Although there is a growing body of empi...

We introduce a new framework for unifying and systematizing the performance analysis of first-order black-box optimization algorithms unconstrained convex minimization. The low-cost iteration complexity enjoyed by renders them particularly relevant applications in machine learning large-scale data analysis. Relying on sum-of-squares (SOS) optimization, we hierarchy semidefinite programs that gi...

The efficiency of Prolog compilers is increasing rapidly but the Prolog programs still cannot compete with traditional languages when executing simple conditionals. In this paper we present a possibility to increase Prolog performance by exploiting the shallow backtracking. Shallow backtracking is initiated when a call fails to unify with the head of a clause and it backtracks to another clause...

A number of researchers have presented evidence that the hardest constraint satisfaction problems tend to arise near the \crossover" point, where around half the problems have solutions. Two recent papers , however, argue that while this is true of the median search cost, the mean search cost has an entirely diierent behavior. The mean search cost appears to be dominated by a relatively small n...

Effective methods to reduce number of message cycles of adopt algorithm which is a complete algorithm for distributed constraint optimization problems are proposed. The Adopt algorithm can perform branch and bound search asynchronously. However, it has overhead in backtracking and searches same partial solution repeatedly. To reduce overhead of backtracking, lower and upper bound of cost of par...

The subgraph isomorphism problem deals with determining whether a given graph H is isomorphic to some subgraph of another graph G. In this paper we attempt to parallelize a fast serial subgraph isomorphism library, VFLib, which uses backtracking search to find a solution. Our parallel solution runs on Cilk++ for efficient execution on multicore machines. In our work we examine the benefits and ...

This paper reviews the connections between Graphplan’s planning-graph and the dynamic constraint satisfaction problem and motivates the need for adapting CSP search techniques to the Graphplan algorithm. It then describes how explanation based learning, dependency directed backtracking, dynamic variable ordering, forward checking, sticky values and random-restart search strategies can be adapte...

In this paper we explore the number of tree search operations required to solve binary constraint satisfaction problems. We show analytically and experimentally that the two principles of first trying the places most likely to fail and remembering what has been done to avoid repeating the same mistake twice improve the standard backtracking search. We experimentally show that a lookahead proced...

Abstract A key challenge in reservoir management and other fields of engineering involves optimizing a nonlinear function iteratively. Due to the lack available gradients commercial simulators attention over last decades has been on gradient free methods or approximations. In particular, ensemble-based optimization gained popularity decade due its simplicity efficient implementation when consid...