The Aurora or-parallel Prolog system

Lusk, Ewing L.; Butler, Ralph; Disz, Terry; Olson, Robert; Overbeek, Ross; Warren, David H.; Calderwood, Alan; Szeredi, Péter; Haridi, Seif; Brand, Per; Carlsson, Mats; Ciepielewski, Andrzej; Hausman, Bogumil

doi:10.1007/bf03037208

Cited by 161 publications

(87 citation statements)

References 5 publications

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“…6). The obtained results are compared with two of the most known multisequential Prolog systems, Aurora [6] and Muse [1] running on a shared memory multiprocessor machine (Sequent Symmetry). In the comparison, it is important to take into account the different stage of development of the systems (Aurora supports sequential side-effect predicates, Muse supports garbage collection, and our implementation is a prototype) and the different architeture on which they are implemented.…”

Section: Performance Results and Discussionmentioning

confidence: 99%

“…In shared memory systems, different branches belonging to one choicepoint can be shared [6,1], that is, the same choicepoint is shared by several workers, which can backtrack to follow the different alternatives. However in distributed systems this type of sharing would require many messages to synchronize all workers sharing different branches from the same choicepoints.…”

Section: Sharing Quantum Of Workmentioning

confidence: 99%

“…Several approaches have been proposed to exploit OR parallelism in Prolog programs. The most significant are: the process tree models [4], where each node in the search tree is associated with a process which tries to solve it, data flow models [5,10], where the search tree is represented as a set of processes synchronized by the.data flow, and multisequential models [8,9,6,1,2]. The latter are based on having multiple Prolog engines that work like sequential ones combined with a method to keep the multiple variable bindings that different Prolog engines could achieve, and with a method to share the work between the system workers 1.…”

Section: Introductionmentioning

confidence: 99%

“…The most known are the Aurora Prolog system [6] on shared memory multiprocessors, and the Muse Prolog system [1] on a multiprocessor machine with distributed and shared memory. Both of them have very good performance results.…”

Section: Introductionmentioning

confidence: 99%

“…It is based on a distributed scheduler that allows the work to be shared between the workers in the network, and on an incremental copy mechanism. The distributed scheduler is particularly important w This work was supported by the project CICYT-TIC 340/90 1 A worker represents a process or processor in the same sense as it does in Aurora [6] and Muse [1].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

An OR parallel Prolog model for distributed memory systems

Benjumea¹,

Troya²

1993

Lecture Notes in Computer Science

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show abstract

Section: Performance Results and Discussionmentioning

confidence: 99%

Section: Sharing Quantum Of Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

An OR parallel Prolog model for distributed memory systems

Benjumea¹,

Troya²

1993

Lecture Notes in Computer Science

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Optimization schemas for parallel implementation of non‐deterministic languages and systems

Gupta

Pontelli

2001

Softw Pract Exp

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Naive parallel implementation of non‐deterministic systems (such as a theorem proving system) and languages (such as logic, constraint, or concurrent constraint languages) can result in poor performance. We present three optimization schemas, based on flattening of the computation tree, procrastination of overheads, and sequentialization of computations that can be systematically applied to parallel implementations of non‐deterministic systems/languages to reduce the parallel overhead and to obtain improved efficiency of parallel execution. The effectiveness of these schemas is illustrated by applying them to the ACE parallel logic programming system. The performance data presented show that considerable improvement in execution efficiency can be achieved. Copyright © 2001 John Wiley & Sons, Ltd.

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P#: a concurrent Prolog for the .NET framework

Cook

2004

Softw Pract Exp

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We discuss P#, our implementation of a tool that allows interoperation between a concurrent superset of the Prolog programming language and C#. This enables Prolog to be used as a native implementation language for Microsoft's .NET platform. P# compiles a linear logic extension of Prolog to C# source code. We can thus create C# objects from Prolog and use C#'s graphical, networking and other libraries. We add language constructs on the Prolog side that allow concurrent Prolog code to be written. A primitive predicate is provided that evaluates a Prolog structure on a newly forked thread. Communication between threads is based on the unification of variables contained in such a structure. It is also possible for threads to communicate through a globally accessible table. All of the new features are available to the programmer through new built-in Prolog predicates. We discuss two software engineering tools implemented using P#. 816 J. J. COOK that is readable, well structured and can easily be modified by a human. Fully realizing this ideal is a long way off, but progress can be made toward it.There already exist translators that translate from Prolog to C, see [3], for example 5], Janus and Erlang. GNU-Prolog was formerly known as wamcc. There are also many Prolog tools that are based on Java, such as Prolog Café [6-10], BinProlog [11], and the commercial product MINERVA [13]. The Prolog in C translators have an emphasis on efficiency that leads them to produce unnatural code, in the case of GNU-Prolog involving jumps into functions. However, Java is more restrictive in the way in which flow of control can be programmed, for example it does not have a goto construct, and so the output of Prolog Café is more readable than that of the Prolog to C translators. As a consequence of the code being better structured, some runtime efficiency is lost, but the ability to easily use Java's libraries from Prolog is gained. With Prolog Café, Prolog code and Java code interoperate in much the same way as any other foreign language interface [14]. However, the integration is closer and more easily programmed than with, for example, a C to Java foreign language interface since in Prolog Café all of the Prolog types are internally represented as Java Objects.C# is a relatively new object-oriented programming language that has drawn on the languages C++ [15] and Java [16,17]. We now summarize the essential points of C#, see [18,19] for more details. Like Java, C# is compiled into an intermediate language. C# shares with Java some features not found in C++, such as garbage collection, reflection, thread support, static inner classes, and the ability to add finally clauses to try blocks. C# supports Java-style interfaces and abstract methods, and like Java does not allow classes to be defined by multiple inheritance. The support for concurrency is similar to that of Java, being based on locked regions and monitors. C# also shares features with C++ that are not found in Java, such as operator overloading, namespaces, jumps, enums, pr...

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The Aurora or-parallel Prolog system

Cited by 161 publications

References 5 publications

An OR parallel Prolog model for distributed memory systems

An OR parallel Prolog model for distributed memory systems

Optimization schemas for parallel implementation of non‐deterministic languages and systems

P#: a concurrent Prolog for the .NET framework

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