Abstract

Abstract
This paper intents to describe the work of integration developed in the metalwork manufacturing cell of CCP (Centro de CIM do Porto). It focus on the manufacturing cell philosophy, the structure of the cell controller, and the integration work with the MMS communication standard. The present work was developed at CCP as a part of the ESPRIT 5629 Project, concluded in October 1995.

Abstract
This paper presents the semantic foundations of commutativity analysis, an analysis technique for automatically parallelizing programs written in a sequential, imperative programming language. Commutativity analysis views the computation as composed of operations on objects. It then analyzes the program at this granularity to discover when operations commute (i.e. generate the same result regardless of the order in which they execute). If all of the operations required to perform a given computation commute, the compiler can automatically generate parallel code. This paper shows that the basic analysis technique is sound. We have implemented a parallelizing compiler that uses commutativity analysis as its basic analysis technique; this paper also presents performance results from two automatically parallelized applications. © Springer-Verlag Berlin Heidelberg 1996.

Abstract
Two operations commute if they generate the same result regardless of the order in which they execute. Commutativity is an important property — commuting operations enable significant optimizations in the fields of parallel computing, optimizing compilers, parallelizing compilers and database concurrency control. Algorithms that statically decide if operations commute can be an important component of systems in these fields because they enable the automatic application of these optimizations. In this paper we define the commutativity decision problem and establish its complexity for a variety of basic instructions and control constructs. Although deciding commutativity is, in general, undecidable or computationally intractable, we believe that efficient algorithms exist that can solve many of the cases that arise in practice. © Springer-Verlag Berlin Heidelberg 1996.

Abstract
This paper introduces an analysis technique, commutativity analysis, for automatically parallelizing computations that manipulate dynamic, pointer-based data structures. Commutativity analysis views computations as composed of operations on objects. It then analyzes the program to discover when operations commute, i.e. leave the objects in the same state regardless of the order in which they execute. If all of the operations required to perform a given computation commute, the compiler can automatically generate parallel code. Commutativity analysis eliminates many of the limitations that have prevented existing compilers, which use data dependence analysis, from successfully parallelizing pointer-based applications. It enables compilers to parallelize computations that manipulate graphs and eliminates the need to analyze the data structure construction code to extract global properties of the data structure topology. This paper shows how to use symbolic execution and expression manipulation to statically determine that operations commute and how to exploit the extracted commutativity information to generate parallel code. It also presents performance results that demonstrate that commutativity analysis can be used to successfully parallelize the Barnes-Hut hierarchical N-body solver, an important scientific application that manipulates a complex pointer-based data structure.

Abstract
The implementation of a robotic assembly cell and it's integration on a CIM environment creats a multitude of problems. The design for robotic assembly which is a complex interactive task between design, CAD and robot simulation and off-line programming groups, the development of flexible mechanical tools for the assembly robot, and the implementation of the assembly cell controller for monotoring and control of the assembly process in the CIM factory, are some of the difficulties to be solved. In this paper we present a description of the solution implemented in CCP - Centro de CIM do Porto, during the ESPRIT 5629 project, project approved in October 1995.