GridSAT: a system for solving satisfiability problems using a computational grid

Chrabakh, Wahid; Wolski, Rich

doi:10.1016/j.parco.2006.01.004

Cited by 22 publications

(10 citation statements)

References 20 publications

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“…GrADSAT [13] is a parallel SAT solver based on the zChaff solver and equipped with a master-slave architecture in which the problem space is divided into subspaces, these sub-spaces are solved by independent zChaff clients and learnt clauses whose size (i.e., number of literals) is less or equal to a given limit are exchanged between clients. The technique organizes load-balancing through a work stealing technique which allows the master to push work to idle clients.…”

Section: Complete Methods For Parallel Satmentioning

confidence: 99%

Improving Parallel Local Search for SAT

Arbeláez

Hamadi

2011

Lecture Notes in Computer Science

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Abstract. In this work, our objective is to study the impact of knowledge sharing on the performance of portfolio-based parallel local search algorithms. Our work is motivated by the demonstrated importance of clause-sharing in the performance of complete parallel SAT solvers. Unlike complete solvers, state-of-the-art local search algorithms for SAT are not able to generate redundant clauses during their execution. In our settings, each member of the portfolio shares its best configuration (i.e., one which minimizes conflicting clauses) in a common structure. At each restart point, instead of classically generating a random configuration to start with, each algorithm aggregates the shared knowledge to carefully craft a new starting point. We present several aggregation strategies and evaluate them on a large set of problems.

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Section: Complete Methods For Parallel Satmentioning

confidence: 99%

Improving Parallel Local Search for SAT

Arbeláez

Hamadi

2011

Lecture Notes in Computer Science

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“…In contrast to existing Grid SAT solvers [49,50], lemma exchange in Satciety is topologyaware. For this purpose, the system classifies each neighbor node-all nodes within the view of a node-as either direct or indirect.…”

Section: Topology-aware Distributed Dynamic Learningmentioning

confidence: 99%

“…GridSAT [49,71] by Chrabakh and Wolski is a parallel SAT Solver especially designed for Globus based Grids. The basic parallel procedure employs exploratory problem decomposition controlled by a dedicated master node.…”

Section: Parallel Sat Solving On Gridsmentioning

confidence: 99%

Parallel SAT Solving on Peer-to-Peer Desktop Grids

Sven

Blochinger

2010

J Grid Computing

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Satciety is a distributed parallel satisfiability (SAT) solver which focuses on tackling the domain-specific problems inherent to one of the most challenging environments for parallel computing-Peer-to-Peer Desktop Grids. Satciety efficiently addresses issues related to resource volatility and heterogeneity, limited node and network capabilities, as well as non-uniform communication costs. This is achieved through a sophisticated distributed task pool execution model, problem size reduction through multistage SAT formula preprocessing, context-aware memory management, and adaptive topologyaware distributed dynamic learning. Despite the demanding conditions prevailing in Desktop Grids, Satciety achieves considerable speedups compared to state-of-the-art sequential SAT solvers.

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“…Some of the solvers are based on network exchange [22], and some solvers are based on database storage [23], and also some based on shared memory [12]. From the early sharing of all to the subsequent selective sharing, the learnt clause sharing strategy of the parallel solver is gradually formed.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Learnt Clause Evaluation Algorithm for SAT Problem

Wu¹,

Chen²,

Xu³

et al. 2018

IJCIS

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It is of great theoretical and practical significance to develop the efficient SAT solvers due to its important applications in hardware and software verifications and so on, and learnt clauses play the crucial role in state of the art SAT solvers. In order to effectively manage learnt clauses, avoid the geometrical growth of learnt clauses, reduce the memory footprint of the redundant learnt clauses and improve the efficiency of the SAT solver eventually, learnt clauses need to be evaluated properly. The commonly used evaluation methods are based on the length of learnt clause, while short clauses are kept according to these methods. One of the current mainstream practices is the variable state independent decaying sum (VSIDS) evaluation method, the other is based on the evaluation of the literals blocks distance (LBD). There have been also some attempts to combine these two methods. The present work is focused on the hybrid evaluation algorithm by combining the trend intensity and the LBD. Based on the analysis of the frequency of learnt clauses, the trend of learnt clause being used is taken as an evaluation method which is then mixed with the LBD evaluation algorithm. The hybrid algorithm not only reflects the distribution of learnt clauses in conflict analysis, but also makes full use of literals information. The experimental comparison shows that the hybrid evaluation algorithm has advantages over the LBD evaluation algorithm in both the serial version and the parallel version of SAT solver, and the number of problems solved has significantly increased.

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GridSAT: a system for solving satisfiability problems using a computational grid

Cited by 22 publications

References 20 publications

Improving Parallel Local Search for SAT

Improving Parallel Local Search for SAT

Parallel SAT Solving on Peer-to-Peer Desktop Grids

A Hybrid Learnt Clause Evaluation Algorithm for SAT Problem

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