Automating the process of parallel performance experimentation, analysis, and problem diagnosis can enhance environments for performance-directed application development, compilation, and execution. This is especially true when parametric studies, modeling, and optimization strategies require large amounts of data to be collected and processed for knowledge synthesis and reuse. This paper describes the integration of the PerfExplorer performance data mining framework with the OpenUH compiler infrastructure. OpenUH provides auto-instrumentation of source code for performance experimentation and PerfExplorer provides automated and reusable analysis of the performance data through a scripting interface. More importantly, PerfExplorer inference rules have been developed to recognize and diagnose performance characteristics important for optimization strategies and modeling. Three case studies are presented which show our success with automation in OpenMP and MPI code tuning, parametric characterization, Pand power modeling. The paper discusses how the integration supports performance knowledge engineering across applications and feedback-based compiler optimization in general.

Presents an experimental toolkit for modeling and solving fuzzy constraint satisfaction problems (FCSPs) called JFSolver. JFSolver is a Java based library developed as an extension of a crisp constraint programming library to provide an enhanced functionality for handling fuzzy constraints including fuzzy constraint specification, propagation and search mechanisms. JFSolver comprises an application programming interface for fuzzy constraint programming and a graphical editor for interactive problem definition and solving. This functionality is demonstrated with an illustrative example.

This paper overviews an experimental fuzzy e-negotiation agents system, FeNAs, that can support automated negotiation in the presence of imprecise information. The system uses the principles of fuzzy constraint-based reasoning involving fuzzy constraint modeling, satisfaction and propagation. It is demonstrated with a prototype for the used car-trading problem. The system supports multi-issue negotiations where offers consist of a number of issues that can include the price of the car and other value-added services such as warranty and the value of the trade-in car. The agents exchange offers on the basis of the information available and negotiation strategies used by each party. Information available to both the buyer and the seller can include the make, model, color, transmission, age and mileage of the car. Each agent has also some private information including preferences, priorities and financial constraints that are not available to other agents. This information can be imprecise where constraints, preferences and priorities are defined as fuzzy constraints describing the level of satisfaction of an agent (and its user) with different potential solutions. The overall objective of an agent is to find a solution that maximizes the agent's utility at the highest possible level of constraint satisfaction subject to its acceptability by other agents. During negotiation the agents follow a common protocol of negotiation and individual negotiation strategies.