The goal of this work is to gain insight into whether processingin-memory (PIM) technology can be used to accelerate the performance of link discovery algorithms, which represent an important class of emerging knowledge discovery techniques. PIM chips that integrate processor logic into memory devices offer a new opportunity for bridging the growing gap between processor and memory speeds, especially for applications with high memory-bandwidth requirements. As LD algorithms are data-intensive and highly parallel, involving read-only queries over large data sets, parallel computing power extremely close (physically) to the data has the potential of providing dramatic computing speedups. For this reason, we evaluated the mapping of LD algorithms to a processing-in-memory (PIM) workstationclass architecture, the DIVA / Godiva hardware testbeds developed by USC/ISI. Accounting for differences in clock speed and data scaling, our analysis shows a performance gain on a single PIM, with the potential for greater improvement when multiple PIMs are used. Measured speedups of 8x are shown on two additional bandwidth benchmarks, even though the Itanium-2 has a clock rate 6X faster. 1.

The need to search for complex and recurring patterns in database sequences is shared by many applications. In this paper, we investigate the design and optimization of a query language capable of expressing and supporting efficiently the search for complex sequential patterns in database systems. Thus, we first introduce SQL-TS, an extension of SQL to express these patterns, and then we study how to optimize the queries for this language. We take the optimal text search algorithm of Knuth, Morris and Pratt, and generalize it to handle complex queries on sequences. Our algorithm exploits the interdependencies between the elements of a pattern to minimize repeated passes over the same data. Experimental results on typical sequence queries, such as double bottom queries, confirm that substantial speedups are achieved by our new optimization techniques.

The need to search for complex and recurring patterns in database sequences is shared by many applications. In this paper, we discuss how to express and support efficiently sophisticated sequential pattern queries in databases. Thus, we first introduce SQL-TS, an extension of SQL, to express these patterns, and then we study how to optimize search queries for this language. We take the optimal text search algorithm of Knuth, Morris and Pratt, and generalize it to handle complex queries on sequences. Our algorithm exploits the inter-dependencies between the elements of a sequential pattern to minimize repeated passes over the same data. Experimental results on typical sequence queries, such as double bottom queries, confirm that substantial speedups are achieved by our new optimization techniques.

Robot soccer competition provides an excellent opportunity for robotics research. In particular, robot players in a soccer game must perform real-time visual recognition, navigate in a dynamic field, track moving objects, collaborate with teammates, and strike the ball in the correct direction. All these tasks demand robots that are autonomous (sensing, thinking, and acting as independent creatures), efficient (functioning under time and resource constraints), cooperative (collaborating with each other to accomplish tasks that are beyond individual's capabilities), and intelligent (reasoning and planing actions and perhaps learning from experience). Furthermore, all these capabilities must be integrated into a single and complete system. To build such integrated robots, we should use different approaches from those employed in separate research disciplines. This paper describes our experience (problems and solutions) in this aspect for building soccer robots. Our robots share the same general architecture and basic hardware, but they have integrated abilities to play different roles and utilize different strategies in their behavior. Our philosophy in building these robots is to use the least possible sophistication to make them as robust as possible. In RoboCup97, our Dreamteam robots performed well (scored 8 of 9 goals of all teams in the league) and won the world championship in the middle-sized robot league.

The access patterns of the users of a web-site are traditionally analyzed in order to facilitate the user access to the site's information. In this study, however, a systematic approach is introduced in order to analyze the users' navigation paths to the advantage of the web-site owner. Briefly, as users navigate through a web-site, it seems that they are transparently filling a questionnaire designed a priori by the web-site owner. To achieve this, we first cluster the users who navigate similar paths employing the Path Mining algorithm. Next, the correlation between a set of target questions and the structure of the WWW-site is quantified. This has been done by borrowing the concept of channel from information theory. Finally, we compute the probability of a user's certain answer to each question, given the user's navigation path. The accuracy of the computed probabilities highly depends on the channel parameters. Hence, we describe a learning process based on a set of training data...