Orca is a language for implementing parallel applications on loosely coupled distributed systems. Unlike most languages for distributed programming, it allows processes on different machines to share data. Such data are encapsulated in data-objects, which are instances of user-defined abstract data types. The implementation of Orca takes care of the physical distribution of objects among the local memories of the processors. In particular, an implementation may replicate and/or migrate objects in order to decrease access times to objects and increase parallelism. This paper gives a detailed description of the Orca language design and motivates the design choices. Orca is intended for applications programmers rather than systems programmers. This is reflected in its design goals to provide a simple, easy to use language that is type-secure and provides clean semantics. The paper discusses three example parallel applications in Orca, one of which is described in detail. It also describes one of the existing implementations, which is based on reliable broadcasting. Performance measurements of this system are given for three parallel applications. The measurements show that significant speedups can be obtained for all three applications. Finally, the paper compares Orca with several related languages and systems. 1.

... work on how to program a computer to play chess. Since then, developing game-playing programs that can compete with (and even exceed) the abilities of the human world champions has been a long-sought-after goal of the AI research community. In Shannon’s time, it would have seemed unlikely that only a scant 50 years would be needed to develop programs that play world-class backgammon, checkers, chess, Othello, and Scrabble. These remarkable achievements are the result of a better understanding of the problems being solved, major algorithmic insights, and tremendous advances in hardware technology. Computer games research is one of the important success stories of AI. This article reviews the past successes,

In the 40 years since Arthur Samuel's 1960 Advances in Computers chapter, enormous progress has been made in developing programs to play games of skill at a level comparable to, and in some cases beyond, what the best humans can achieve. In Samuel's time, it would have seemed unlikely that only a scant 40 years would be needed to develop programs that play world-class backgammon, checkers, chess, Othello, and Scrabble. These remarkable achievements are the result of a better understanding of the problems being solved, major algorithmic insights, and tremendous advances in hardware technology. Computer games research is one of the major success stories of articial intelligence. This chapter can be viewed as a successor to Samuel's work. A review of the scientic advances made in developing computer games is given. These ideas are the ingredients required for a successful program. Case studies for the games of backgammon, bridge, checkers, chess, Othello, poker, and Scrabb...

The only control-parallel programming model to win wide acceptance to date has been procedural message passing. One reason that higher-level systems have not been widely accepted is that there is no consensus on what they should offer; one reason for this is that there has been no systematic comparison of the usability of alternatives models and systems. This paper describes a problem suite with which the usability, rather than performance, of parallel programming systems may be assessed. Introduction While data parallelism is now widely accepted, most control-parallel programming systems are used only by their authors, or not used at all. The only general exceptions are low-level procedural message-passing (PMP) systems such as PVM and PARMACS [GS92, BRH90]. While these are appropriate for systems-level programming, they make applications programming tedious and error-prone. Like the VT100, the PMP model does not offer much, but is the only reliable common denominator between ...

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We review possible and probable industrial applications of HPCC focusing on the software and hardware issues. Thirty-three separate categories are illustrated by detailed descriptions of five areas -- computational chemistry; Monte Carlo methods from physics to economics; manufacturing, and computational fluid dynamics; command and control, or crisis management; and multimedia services to client computers and settop boxes. The hardware varies from tightly-coupled parallel supercomputers to heterogeneous distributed systems. The software models span HPF and data parallelism, to distributed information systems and object/dataflow parallelism on the Web. We nd that in each case, it is reasonably clear that "HPCC works in principle," and postulate that this knowledge can be used in a new generation of software infrastructure based on the WebWindows approach, and discussed in an accompanying paper.

With the continuing price-performance improvement of small computers there is growing interest in looking again at some of the heuristic techniques developed for problemsolving and planning programs, to see if they can be enhanced or replaced by more algorithmic methods. The application of raw computing power, while and anathema to some, often provides better answers than is possible by reasoning or analogy. Thus brute force techniques form a good basis against which to compare more sophisticated methods designed to mirror the human deductive process. One source of extra computing power comes through the use of parallel processing on a multicomputer, an so this aspect is also covered here. Here we review the development of heuristic algorithms for application in singleagent and adversary games. We provide a detailed study of iterative deepening A * and its many variants, and show howe ective various enhancements, including the use of refutation lines and a transposition table, can be. For adversary games a full review of improved versions of the alpha-beta algorithm (e.g. Principal Variation Search) is

We review a decade's work on message passing MIMD parallel computers in the areas of hardware, software and applications. We conclude that distributed memory parallel computing works, and describe the implications of this for future portable software systems.

s are available from the same host in the directory /pub/TR/UBLCS/ABSTRACTS in plain text format. All local authors can be reached via e-mail at the address last-name@cs.unibo.it. UBLCS Technical Report Series 93-1 Consistent Global States of Distributed Systems: Fundamental Concepts and Mechanism, by Ö. Babaog;lu and K. Marzullo, January 1993. 93-2 Understanding Non-Blocking Atomic Commitment, by Ö. Babaog;lu and S. Toueg, January 1993. 93-3 Anchors and Paths in a Hypertext Publishing System, by C. Maioli and F. Vitali, February 1993. 93-4 A Formalization of Priority Inversion, by Ö. Babaog;lu, K. Marzullo and F. Schneider, March 1993. 93-5 Some Modifications to the Dexter Model for the Formal Description of Hypertexts, by S. Lamberti, C. Maioli and F. Vitali, April 1993. 93-6 Versioning Issues in a Collaborative Distributed Hypertext System, by C. Maioli, S. Sola and F. Vitali, April 1993. 93-7 Distributed Programming with Logic Tuple Spaces, by P. Ciancarini, April 1993. 93-8 Coordi...

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