Relationships between memory models

There have been many proposals of shared memory systems, each one providing different types of memory coherence for interprocess communication. However, they have usually been defined using different formalisms. This makes it difficult to compare among them the different proposals put forward. In this paper we present a formal framework for specifying memory models with different coherency properties. We specify most of the known shared memory models using our framework, showing some of the relationships that hold among them.     

Style-based modeling and refinement of service-oriented architectures

Service-oriented architectures (SOA) provide a flexible and dynamic platform for implementing business solutions. In this paper, we address the modeling of such architectures by refining business-oriented architectures, which abstract from technology aspects, into service-oriented ones, focusing on the ability of dynamic reconfiguration (binding to new services at run-time) typical for SOA.The refinement is based on conceptual models of the platforms involved as architectural styles, formalized by graph transformation systems. Based on a refinement relation between abstract and platform-specific styles we investigate how to realize business-specific scenarios on the SOA platform by automatically deriving refined, SOA-specific reconfiguration scenarios.Research partially supported by the European Research Training Network SegraVis (on Syntactic and Semantic Integration of Visual Modelling Techniques)     

Architectural mechanisms for dynamic changes of behavior selection strategies in behavior-based systems

Behavior selection is typically a "built-in" feature of behavior-based architectures and hence, not amenable to change. There are, however, circumstances where changing behavior selection strategies is useful and can lead to better performance. In this paper, we demonstrate that such dynamic changes of behavior selection mechanisms are beneficial in several circumstances. We first categorize existing behavior selection mechanisms along three dimensions and then discuss seven possible circumstances where dynamically switching among them can be beneficial. Using the agent architecture framework activation, priority, observer, and component (APOC), we show how instances of all (nonempty) categories can be captured and how additional architectural mechanisms can be added to allow for dynamic switching among them. In particular, we propose a generic architecture for dynamic behavior selection, which can integrate existing behavior selection mechanisms in a unified way. Based on this generic architecture, we then verify that dynamic behavior selection is beneficial in the seven cases by defining architectures for simulated and robotic agents and performing experiments with them. The quantitative and qualitative analyzes of the results obtained from extensive simulation studies and experimental runs with robots verify the utility of the proposed mechanisms.     

High‐level specifications for automatically generating parallel code

The arrival of multicore systems, along with the speed‐up potential available in graphics processing units, has given us unprecedented low‐cost computing power. These systems address some of the known architecture problems but at the expense of considerably increased programming complexity. Heterogeneity, at both the architectural and programming levels, poses a great challenge to programmers. Many proposals have been put forth to facilitate the job of programmers. Leaving aside proposals based on the development of new programming languages because of the effort this represents for the user (effort to learn and reuse code), the remaining proposals are based on transforming sequential code into parallel code, or on transforming parallel code designed for one architecture into parallel code designed for another. A different approach relies on the use of skeletons. The programmer has available set of parallel standards that comprise the basis for developing parallel code while programming sequential code. In this context, we propose a methodology for developing an automatic source‐to‐source transformation in a specific domain. This methodology is instantiated in a framework aimed at solving dynamic programming problems. Using this framework, the final user (a physician, mathematician, biologist, etc.) can express her problem using an equation in Latex, and the system will automatically generate the optimal parallel code for homogeneous or heterogeneous architectures. This approach allows for great portability toward these new emerging architectures and for great productivity, as evidenced by the computational results.Copyright © 2012 John Wiley & Sons, Ltd.