Tobias Schubert

Multithreaded SAT Solving

This paper describes the multithreaded MiraXT SAT solver which was designed to take advantage of current and future shared memory multiprocessor systems. The paper highlights design and implementation details that allow the multiple threads to run and cooperate efficiently. Results show that in single threaded mode, MiraXT compares well to other state of the art solvers on industrial problems. In threaded mode, it provides cutting edge performance, as speedup is obtained on both SAT and UNSAT instances.

Incremental preprocessing methods for use in BMC

Traditional incremental SAT solvers have achieved great success in the domain of Bounded Model Checking (BMC). Recently, modern solvers have introduced advanced preprocessing procedures that have allowed them to obtain high levels of performance. Unfortunately, many preprocessing techniques such as variable and (blocked) clause elimination cannot be directly used in an incremental manner. This work focuses on extending these techniques and Craig interpolation so that they can be used effectively together in incremental SAT solving (in the context of BMC). The techniques introduced here doubled the performance of our BMC solver on both SAT and UNSAT problems. For UNSAT problems, preprocessing had the added advantage that Craig interpolation was able to find the fixed point sooner, reducing the number of incremental SAT iterations. Furthermore, our ideas seem to perform better as the benchmarks become larger, and/or deeper, which is exactly when they are needed. Lastly, our methods can be integrated into other SAT based BMC tools to achieve similar speedups.

PaMira - A Parallel SAT Solver with Knowledge Sharing

In this paper we describe PaMira, a powerful distributed SAT solver. PaMira is based on the highly optimized, sequential SAT engine Mira, incorporating all essential optimization techniques modern algorithms utilize to maximize performance. For the distributed execution an efficient work stealing method has been implemented. PaMira also employs the exchange of conflict clauses between the processes to guide the search more efficiently. We provide experimental results showing linear speedup on a multiprocessor environment with four AMD Opteron processors

Efficient SAT-based dynamic compaction and relaxation for longest sensitizable paths

Comprehensive coverage of small-delay faults under massive process variations is achieved when multiple paths through the fault locations are sensitized by the test pair set. Using one test pair per path may lead to impractical test set sizes and test application times due to the large number of near-critical paths in state-of-the-art circuits.

SAT-based analysis of sensitisable paths

Manufacturing defects in nanoscale technologies have highly complex timing behaviour that is also affected by process variations. While conventional wisdom suggests that it is optimal to detect a delay defect through the longest sensitisable path, non-trivial defect behaviour along with modelling inaccuracies necessitate consideration of paths of well-controlled length during test generation. We present a generic methodology that yields tests through all sensitisable paths of user-specified length. The resulting tests can be employed within the framework of adaptive testing. The methodology is based on encoding the problem as a Boolean-satisfiability (SAT) instance and thereby leverages recent advances in SAT-solving technology.

PaQuBE: Distributed QBF Solving with Advanced Knowledge Sharing

In this paper we present the parallel QBF Solver PaQuBE . This new solver leverages the additional computational power that can be exploited from modern computer architectures, from pervasive multicore boxes to clusters and grids, to solve more relevant instances and faster than previous generation solvers. PaQuBE extends QuBE , its sequential core, by providing a Master/Slave Message Passing Interface (MPI) based design that allows it to split the problem up over an arbitrary number of distributed processes. Furthermore, PaQuBE s progressive parallel framework is the first to support advanced knowledge sharing in which solution cubes as well as conflict clauses can be shared. According to the last QBF Evaluation, QuBE is the most powerful state-of-the-art QBF Solver. It was able to solve more than twice as many benchmarks as the next best independent solver. Our results here, show that PaQuBE provides additional speedup, solving even more instances, faster.

Provably optimal test cube generation using quantified boolean formula solving

Circuits that employ test pattern compression rely on test cubes to achieve high compression ratios. The less inputs of a test pattern are specified, the better it can be compacted and hence the lower the test application time. Although there exist previous approaches to generate such test cubes, none of them are optimal. We present for the first time a framework that yields provably optimal test cubes by using the theory of quantified Boolean formulas (QBF). Extensive comparisons with previous methods demonstrate the quality gain of the proposed method.

SAT-ATPG using preferences for improved detection of complex defect mechanisms

Failures caused by phenomena such as crosstalk or power-supply noise are gaining in importance in advanced nanoscale technologies. The detection of such complex defects benefits from the satisfaction of certain constraints, for instance justifying specific transitions on neighbouring lines of the defect location. We present a SAT-based ATPG-tool that supports the enhanced conditional multiple-stuck-at fault model (ECMS@). This model can specify multiple fault locations along with a set of hard conditions imposed on arbitrary lines; hard conditions must hold in order for the fault effect to become active. Additionally, optimisation constraints that may be required for best coverage can be specified via a set of soft conditions. The introduced tool justifies as many of these conditions as possible, using a mechanism known as SAT with preferences. Several applications are discussed and evaluated by extensive experimental data. Furthermore, a novel fault-clustering technique is introduced, thanks to which the time required to classify all stuck-at faults in a suite of industrial benchmarks was reduced by up to 65%.

Parallel SAT solving in bounded model checking

Bounded Model Checking (BMC) is an incremental refutation technique to search for counterexamples of increasing length. The existence of a counterexample of a fixed length is expressed by a first-order logic formula that is checked for satisfiability using a suitable solver. We apply communicating parallel solvers to check satisfiability of the BMC formulae. In contrast to other parallel solving techniques, our method does not parallelize the satisfiability check of a single formula, but the parallel solvers work on formulae for different counterexample lengths. We adapt the method of constraint sharing and replication of Shtrichman, originally developed for sequential BMC, to the parallel setting. Since the learning mechanism is now parallelized, it is not obvious whether there is a benefit from the concepts of Shtrichman in the parallel setting. We demonstrate on a number of benchmarks that adequate communication between the parallel solvers yields the desired results.

Automatic initialization for skeleton tracking in optical motion capture

The ability to track skeletal movements is important in a variety of applications including animation, biological studies and animal experiments. To detect even small movements, such a method should provide highly accurate estimates. Besides that it should not impede the mammal in its motion. This motivates the usage of a passive optical motion capture system. Thereby the main challenges are the initialization, the association of the unlabeled markers to their corresponding segment also across the frames, and the estimation of the skeleton configuration. While many existing approaches can deal with the latter two problems, they typically need a specific pose for initialization. This is rather unpractical in the context of animal tracking and often requires a manual initialization process. In this paper, we present an approach to reliably track animals and humans in marker-based optical motion capture systems with freely attached markers. Our method is also able to perform an automatic initialization without any pre-or post-processing of the data. To achieve this, our approach utilizes a large database of previously observed poses. We present our algorithm and its evaluation on real-world data sets with an animal and humans. The results demonstrate that our initialization method performs accurately for the most kind of initial poses and our tracking approach outperforms a popular fully automatic skeleton tracking method especially with respect to the smoothness of the motion.