MOLOG: A system that extends PROLOG with modal logic

In this paper we present an extension of PROLOG using modal logic. A new deduction method is also given based on a rule closer to the classical inference rule of PROLOG.     

Prolog-ELF incorporating fuzzy logic

Prolog-ELF incorporating fuzzy logic and several useful functions into Prolog has been implemented as a basic language for building knowledge systems with uncertainty or fuzziness. Prolog-ELF inherits all the desirable basic features of Prolog. In addition to assertions with truth-values between 1.0 and 0.5 (0 for exceptional cases), fuzzy sets can be very easily manipulated. An application of fuzzy logical database is illustrated.     

Declarative error diagnosis

This paper presents an error diagnoser which finds errors in logic programs which use the extended syntax and advanced control facilities. The diagnoser isdeclarative, in the sense that the programmer need only know the intended interpretation of an incorrect program to use the diagnoser. In particular, the programmer needs no understanding whatever of the underlying computational behaviour of the PROLOG system which runs the program. It is argued that declarative error diagnosers will be indispensable components of advanced logic programming systems, which are currently under development.     

Uses of Prolog in implementation of expert systems

Prolog is becoming a popular language in A. I. applications and particularly in the implementation of knowledge based expert systems. We have identified three different uses of Prolog: (1) building expert systems directly in ordinary Prolog, (2) using Prolog as the implementation language for an higher level of interpretation, and (3) extending Prolog with suitable features and directly using it. In this paper, we define the three uses in more details, compare them, and cite some concrete examples.     

Set abstraction—An extension of all solutions predicate in logic programming language

The concept of set abstraction is introduced as a simple analogy of that of lambda abstraction in the theory of lambda calculus. The set abstraction is concerned with two extensions concerning Prolog language features: “set expression” and “predicate variable.” It has been argued in the literature that the set expression extension to Prolog does really contribute to the power of the language, while the extension of predicate variables does not add anything to Prolog. Combining these two concepts of extensions to Prolog, we define “set abstraction” as the set expression in which predicate variables are allowed as data objects. In other words, the set abstraction gets involved in the higher order predicate logic. By showing some application examples, it is demonstrated that with the help of predicate variables set abstractions can nicely handle the issues of the second order predicate logic. Further, the implementation programs written in Prolog and Concurrent Prolog are presented.     

P-Prolog: A parallel logic language based on exclusive relation

This paper presents a parallel logic programming language named P-Prolog which is being developed as a logic programming language featuring both and- and or-parallelism. Compared with the other parallel logic programming languages, syntactic constructs such as read-only annotation,⁶⁾ mode declaration²⁾ and communication constraints⁷⁾ are not used in P-Prolog. A new concept introduced in P-Prolog is the exclusive relation of guarded Horn clauses. Advances included in P-prolog. are:

1. The synchronization mechanism can determine the direction of data flow dynamically.
2. Guarded Horn clauses can be interpreted as eitherdon’t care nondeterminism ordon’t know non-determinism.

A prototype interpreter of P-Prolog has been implemented in C-Prolog. We are now implementing a P-Prolog interpreter in the C language.     

Temporal logic based hardware description and its verification with Prolog

Techniques of hierarchical specification and verification of hardware with temporal logic and Prolog are presented by example. Both hardware designs in gates and state-diagrams are translated into a relation between the present and the next state, which is represented in Prolog.¹⁾ Specifications are constructed by temporal logic that can express state sequences (e.g. timing diagrams) easily and also are translated into a relation between the present and the next state in Prolog. The verification method is based upon the temporal logic decision procedure in Ref. 2) and, referring to the relation tables between the present state and the next state, the verifier can reason in both directions—forward and backward in temporal sequences. Prolog has very powerful pattern matching, and its automatic backtracking capabilities facilitate easy-to-write verifier programs. It is concluded that a total verification system handling various design levels can be constructed with temporal logic and Prolog.     

Performance analysis of SSE and AVX instructions in multi-core CPUs and GPU computing on FDTD scheme for solid and fluid vibration problems

In this work a unified treatment of solid and fluid vibration problems is developed by means of the Finite-Difference Time-Domain (FDTD). The scheme here proposed takes advantage from a scaling factor in the velocity fields that improves the performance of the method and the vibration analysis in heterogenous media. Moreover, the scheme has been extended in order to simulate both the propagation in porous media and the lossy solid materials. In order to accurately reproduce the interaction of fluids and solids in FDTD both time and spatial resolutions must be reduced compared with the set up used in acoustic FDTD problems. This aspect implies the use of bigger grids and hence more time and memory resources. For reducing the time simulation costs, FDTD code has been adapted in order to exploit the resources available in modern parallel architectures. For CPUs the implicit usage of the advanced vectorial extensions (AVX) in multi-core CPUs has been considered. In addition, the computation has been distributed along the different cores available by means of OpenMP directives. Graphic Processing Units have been also considered and the degree of improvement achieved by means of this parallel architecture has been compared with the highly-tuned CPU scheme by means of the relative speed up. The speed up obtained by the parallel versions implemented were up to 3 (AVX and OpenMP) and 40 (CUDA) times faster than the best sequential version for CPU that also uses OpenMP with auto-vectorization techniques, but non includes implicitely vectorial instructions. Results obtained with both parallel approaches demonstrate that massive parallel programming techniques are mandatory in solid-vibration problems with FDTD.     

A Prolog technology theorem prover

An extension of Prolog, based on the model elimination theorem-proving procedure, would permit production of a logically complete Prolog technology theorem prover capable of performing inference operations at a rate approaching that of Prolog itself.     

Design and simulation of a sequential Prolog machine

Prolog-X is an implemented portable interactive sequential Prolog system in which clauses are incrementally compiled for a virtual machine called the ZIP Machine. At present, the ZIP Machine is emulated by software, but it has been designed to permit easy implementation in microcode or hardware. Prolog-X running on the software-based emulator provides performance comparable with existing Prolog interpreters. To demonstrate its efficiency, compatibility, and comprehensiveness of implementation, Prolog-X has been used to compile and run several large applications programs. Several novel techniques are used in the implementation, particularly in the areas of the representation of therecordx database, the selection of clauses, and the compilation of arithmetic expressions.     

A Substitution Based Model for the Implementation of PROLOG——The Design and Implementation of LPROLOG

Since PROLOG has been chosen as the Fifth Generation Computer's Kernal Language,it ispresently one of the hottest topics among computer scientists all over the world.Recently,theimplementation technique and the application of PROLOG have been developed rapidly.In thispaper,a new implementation scheme for PROLOG is proposed.The scheme is based on thesubstitution of instantiated veriable values.It has many advantages,such as a higher runningspeed,less main memory requirement,and easier to be implemented.The scheme has beenimplemented by the authors on IBM4341.     

The occur-check problem in Prolog

We present a method for preprocessing Prolog programs so that their operational semantics will be given by the first-order predicate calculus. Most Prolog implementations do not use a full unification algorithm, for efficiency reasons. The result is that it is possible to create terms having loops in them, whose semantics is not adequately described by first-order logic. Our method finds places where such loops may be created, and adds tests to detect them. This should not appreciably slow down the execution of most Prolog programs.     

Multiwalled carbon nanotube-polyimide nanocomposite for MEMS piezoresistive pressure sensor applications

Multiwalled carbon nanotube (MWCNT)-polyimide (PI) nanocomposite was prepared with different MWCNT concentrations and characterized for their piezoresistive response. The morphology and mechanical behavior of the nanocomposite was investigated by scanning electron microscopy and force–displacement spectroscopy respectively. The surface conductivity of the nanocomposite was determined by atomic force microscopy in current mode. Studies reveal that this nanocomposite will be useful for strain-sensing element in micro electro mechanical system (MEMS)/nano electro mechanical system (NEMS) based piezoresistive pressure sensor applications. The study shows that the nanocomposite with 2 % MWCNT content is a unique piezoresistive sensing element for MEMS/NEMS pressure sensor.     

How to invent a Prolog machine

In this paper we study the compilation of Prolog by making visible hidden operations (especially unification), and then optimizing them using well-known partial evaluation techniques. Inspection of straightforward partially evaluated unification algorithms gives an idea how to design special abstract machine instructions which later form the target language of our compilation. We handle typical compiler problems like representation of terms explicitly. This work gives a logical reconstruction of abstract Prolog machine code, and represents an approach of constructing a correct compiler from Prolog to such a code. As an example, we are explaining the unification principles of Warren’s New Prolog Engine within our framework.     

Bounded-wait merge in Shapiro’s Concurrent Prolog

InA Subset of Concurrent Prolog and Its Interpreter (1983), E. Y. Shapiro introduces the language Concurrent Prolog. In his presentation, the problem of guaranteeing bounded-waiting during a merge operation is used as a programming example. Solutions are proposed for binary and n-ary merges. The solutions are, however, completely dependent on specific operational characteristics of a Concurrent Prolog machine or interpreter. This paper presents an alternate approach in which the property of bounded-waiting is incorporated into the semantics of the programs, demonstrable given only the computational model of the language. The solution strategy is to utilize the familiar systems programming techniques of block-on-input and busy-wait. This approach requires that the language be augmented with a metalogical predicate analogous to thevar(_) predicate of Sequential Prolog. The resultant programs are interesting and illustrative examples of Concurrent Prolog as a programming language.     

Peacock: a customizable MapReduce for multicore platform

MapReduce has been demonstrated to be a promising alternative to simplify parallel programming with high performance on single multicore machine. Compared to the cluster version, MapReduce does not have bottlenecks in disk and network I/O on single multicore machine, and it is more sensitive to characteristics of workloads. A single execution flow may be inefficient for many classes of workloads. For example, the fixed execution flow of the MapReduce program structure can impose significant overheads for workloads that inherently have only one emitted value per key, which are mainly caused by the unnecessary reduce phase. In this paper, we refine the workload characterization from Phoenix++ according to the attributes of key-value pairs, and give a demonstration that the refined workload characterization model covers all classes of MapReduce workloads. Based on the model, we propose a new MapReduce system with workload-customizable execution flow. The system, namely Peacock, is implemented on top of Phoenix++. Experiments with four different classes of benchmarks on a 16-core Intel-based server show that Peacock achieves better performance than Phoenix++ for workloads that inherently have only one emitted value per key (up to a speedup of \(3.6\times \) ) while identical for other classes of workloads.     

Translating production rules into a forward reasoning Prolog program

Several attempts have been made to design a production system using Prolog. To construct a forward reasoning system, the rule interpreter is often written in Prolog, but its execution is slow. To develop an efficient production system, we propose a rule translation method where production rules are translated into a Prolog program and forward reasoning is done by the translated program. To translate the rules, we adopted the technique developed in BUP, the bottom-up parsing system in Prolog. Man-machine dialogue functions were added to the production system and showed the potential of our method to be applied to expert systems.