The assessment of chess players is both an increasingly attractive opportunity and an unfortunate necessity. The chess community needs to limit potential reputational damage by inhibiting cheating and unjustified accusations of cheating: there has been a recent rise in both. A number of counter-intuitive discoveries have been made by benchmarking the intrinsic merit of players’ moves: these cal...

There are a number of models that were proposed in recent years for message passing parallel systems. Examples are the postal model and its generalization the LogP model. In the postal model a parameter h is used to model the communication latency of the message-passing system. Each node during each round can send a fixed-size message and, simultaneously, receive a message of the same size. Fur...

Performance modeling has long been considered a difficult science requiring expertise from seasoned capacity planners. Currently there has been a shift in the area of performance modeling towards ease-of-use and automation of the entire process. Automation not only hides this difficult science from the users but also delivers immediate Return on Investment for administrators with deploy and run...

Performance prediction has gained increasing attention in the IR field since the half of the past decade and has become an established research topic in the field. The present work restates the problem in the subarea of Collaborative Filtering (CF), where it has barely been researched so far. We investigate the adaptation of clarity-based query performance predictors to define predictors of nei...

Statistical modeling and evaluation of the performance of obstacle detection systems for Unmanned Ground Vehicles (UGV's) is essential for the design, evaluation, and comparison of sensor systems. In this report, we address this issue for imaging range sensors by dividing the evaluation problem into two levels: quality of the range data itself and quality of the obstacle detection algorithms ap...

Individual characteristics and informal social processes are among the factors that contribute to a student’s performance in an academic context. Universities can leverage this knowledge to limit drop-out rates and increase performance through interventions targeting at-risk students. Data-driven recommendation systems have been proposed to identify such students for early interventions. Howeve...

While much research work has been devoted to analysis and prediction of individuals’ behavior in social networks, very few studies about the analysis of business networks are conducted. Empowered by recent research on automated mining of business networks, this paper illustrates the design of a novel business network-based model called Energy Cascading Model (ECM) for the analysis and predictio...

Unstructured parallelism is the hardest problem to analyze and to program. In this paper we present a generic approach TGEX for analyzing and executing unstructured problems. It separates the speciication of a computational problem from the control of the parallel execution. A computational problem is rst partitioned in terms of a computation task graph which serves as a machine-independent rep...

This paper presents a performance modeling methodology that is faster than traditional cycle-accurate simulation, more sophisticated than performance estimation based on system peak-performance metrics, and is shown to be effective on a class of High Performance Computing PETSc kernels. The method yields insight into the factors that affect performance and scalability on parallel computers.

As the complexity of the Semantic Web increases, efficient ways to query the Semantic Web data is becoming increasingly important. Moreover, consumers of the Semantic Web data may need explanations for debugging or understanding the reasoning behind producing the data. In this paper, firstly we address the problem of SPARQL query performance prediction. Secondly we discuss how to explain Linked...