A virtual bus architecture for dynamic parallel processing

To support parallel processing of data-intensive applications, the interconnection network of a parallel/distributed machine must provide high end-to-end communication bandwidth and handle the bursty and concentrated communication patterns generated by dynamic load balancing and data collection operations. A large-scale interconnection network architecture called a virtual bus is proposed. The virtual bus can scale to terabits-per-second end-to-end communication bandwidth with low queuing delay for nonuniform traffic. A terabit virtual bus architecture can be efficiently implemented for less than 5% of the total cost of an eight-thousand-node system. In addition, the virtual bus has an open system parallel interface that is flexible enough to support up to gigabytes per second data transfer rates, different grades of services, and broadcast operation. Such flexibility makes the virtual bus a plausible open system communication backbone for a broad range of applications     

Parallel discrete event simulation with SIMULA

The area of Discrete Event Simulation (DES) is the least impacted by parallel processing even though most of its applications require tremendous amounts of processing time. The common approach of parallelizing individually special purpose programs leads to very limited improvements in performance. We propose here the parallelization of general DES applications written in SIMULA, as a part of an ongoing project that aims towards developing methodologies and architectures for parallel DES. SIMULA is a general purpose process oriented language whose structure allows the creation of processes which can participate in a quasi-parallel execution according to an interleaved fashion. Problems related to the process interference representation, parallel scheduling and process synchronization are defined and solved. To test and verify the theoretical results the parallel execution of experimental and real DES applications has been simulated. The results show that significant improvement in performance can be expected.     

Experimental results from parallel backward-chained expert systems

There are many applications which may be done by an expert system in real time, if the system is capable of real time response. the first Lisp- and Prolog-based expert systems have typically been too slow for real time response. This has lead to an effort to use other languages, the development of fast pattern matching techniques, and other methods of improving the speed of expert systems. Another approach to developing faster expert systems is to make use of the emerging parallel processing computer technology. A further use for parallelism is to allow reasonable response time for large knowledge bases. the size of knowledge bases may become as large as 20,000 chunks of knowledge (and more) in the near future in medical and space applications. This article describes the use of parallel processing in the EMYCIN backward chained rule-based model. Performance on two examples of shared memory multiprocessors is presented and contrasted with earlier simulations.     

CAD／CAM集成系统中轴类零件CAPP专家系统的研制

当代在推进ＣＩＭＳ中，专家系统日益受到重视，本文论述了专家系统方法在自动生成零件加工工艺文件中的应用进行了研究和讨论，研制了一种创成式轴类零件ＣＡＰＰ专家系统－ＧＳＣＡＰＰ。该系统通过人机图形选单对话或与ＣＡＤ系统连接输入的方式输入少量信息（如零件结构，尺寸，精度及热处理方式等），即可在知识库的支持下自动生成完整的零件的加工工艺文件，系统运行简捷，可编工艺范围广，维护方便，输出的工艺文件符合工厂要     

文本处理中的MapReduce技术

用于文本处理的很多数据集已经达到TB、PB甚至更大规模,传统的单机方法难以对这些数据进行有效处理。近年来出现的MapReduce计算框架能够以简洁的形式和分布式的方案来解决大规模数据的并行处理问题,得到了学术界和工业界的广泛认可和使用。目前,MapReduce已经被用于自然语言处理、机器学习及大规模图处理等领域。该文首先对MapReduce做了简单的介绍,并分析了其特点、优势还有不足;然后对MapReduce近年来在文本处理各个方面的应用进行分类总结和整理;最后对MapReduce的系统和性能方面的研究也做了一些介绍与展望。     

Visualization of large data sets with the Active Data Repository

We implement ray-casting-based volume rendering and isosurface rendering methods using the Active Data Repository (ADR) for visualizing out-of-core data sets. We have developed the ADR object-oriented framework to provide support for applications that employ range queries with user-defined mapping and aggregation operations on large-scale multidimensional data. ADR targets distributed-memory parallel machines with one or more disks attached to each node. It is designed as a set of modular services implemented in C++, which can be customized for application-specific processing. The ADR runtime system supports common operations such as memory management, data retrieval, and scheduling of processing across a parallel machine     

MACSYM: A hierarchical parallel image processing system for event-driven pattern understanding of documents

MACSYM is a hierarchical parallel processing system for pattern understanding applications. It features event-driven parallel processing for knowledge-based understanding of document images. The system is composed of a master processor, slave processors and a large shared memory, and is equipped with versatile communication facilities. The parallel processing software system M.UM has been developed on MACSYM. It supplies a parallel processing language MacC, an extended version of C, and supports the programming for document image understanding. The Japanese newspaper layout understanding system EXPRESS is being developed on MACSYM. It analyzes a newspaper image and extracts articles in a few seconds.     

Supporting parallel programming in a distributed UNIX environment

A distributed processing system based on UNIX (trademark of Bell Laboratories) is currently operational at New Mexico State University. The system which is composed of a variety of PDP-11 and LSI-11 processing elements allows users to schedule tasks to run totally or in parallel on its satellite units. A UNIX-like kernel is run on the satellite processors and this allows virtually any process to run on any processing element. The architecture of the system is a star configuration with a PDP-11/34a as the central or host node. To support experiments in parallel processing, a parallel version of the C programming language has been developed which allows users to write programs as a collection of functional units which can be automatically scheduled to run on the satellite processors. In this paper the structure of the system is described in terms of hardware and software, and our implementation of pc, a parallel C language, is discussed.     

Pc-based Shared Memory Architecture and Language

The Image Processing applications require both computing and communication power. The object of the GFLOPS project was to study all aspects concerning the design of such computers. The project's aim was to develop a parallel architecture as well as its software environment to implement these applications efficiently. A development environment, especially a C data-parallel language, has been built for this purpose. The C parallel language presented here, simplifies the use of such architectures by providing the programmer with a global name space and a control mechanism to exploit fine and medium grain parallelism of its applications. The main advantage of our paradigm is that it allows a unique framework to express both data and control parallelism. We have implemented this programming environment on the GFLOPS machine which supports up to 512 processor nodes, which are PC mother boards, connected over a scaleable and cost-effective network, via the PCI-bus, at a constant cost per node. The aim is to obtain at low cost a scaleable virtually shared memory machine. In this paper we discuss the design of the GFLOPS machine and its C parallel language, and evaluate the effectiveness of the mechanisms incorporated. The analysis of the architecture's behaviour was conducted with microbenchmarks and image processing algorithms, written in C.     

Machine analysis of acoustical signals

Research toward machine analysis of acoustical signals is described. The approach is that of the expert system, where knowledge about the physical world that produced the signals is used by the system in the interpretation process. Expert systems have already matched human capabilities in applications such as chemical structure analysis and certain areas of medical diagnosis, suggesting that acoustical signal analysis will meet with similar success. The paper describes aspects of knowledge representation and signal processing methods of an experimental computer program that is being used as a vehicle for development of AI techniques in the processing of acoustic signals.     

Adam: An Ada-based language for multiprocessing

Adam is a high-level language for parallel processing. It is intended for programming resource scheduling applications, in particular supervisory packages for run-time scheduling of multiprocessing systems. An important design goal was to provide support for implementation of Ada and its run-time environment. Adam has been used to implement Ada task supervision and also as a high-level target language for compilation of Ada tasking. Adam provides facilities corresponding to the Ada sequential constructs (including subprograms, packages, exceptions, generics). In addition, it provides specialized module constructs for implementation of packages that may be shared between parallel processes, and new predefined types for scheduling. The parallel processing constructs of Adam are more primitive than Ada tasking. Strong restrictions are enforced on the ways in which parallel processes can interact. A compiler for Adam has been implemented in MacLisp on DEC PDP-10 computers. Runtime support packages in Adam for scheduling (on a single CPU) and I/O are also provided. The compiler contains a library manipulation facility for separate compilation. The Adam compiler has been used to build an Ada compiler for most of the July 1980 Ada, including task types and rendezvous constructs. This was achieved by implementing the translation of Ada tasking into Adam parallel processing as a preprocessor to the Adam compiler. This present Ada compiler, which has been operational since December 1980, uses a procedure call implementation of tasking. It can be easily modified to other implementations. Compilation of Ada tasking into a high-level target language such as Adam facilitates studying questions of correctness and efficiency of various compilation algorithms, and code optimizations specific to tasking, e.g. elimination of unnecessary threads of control. This paper gives an overview of Adam and examples of its use. Emphasis is placed on the differences from Ada. Experience using Adam to build the experimental Ada system is evaluated. Design of a run-time supervisor in Adam is discussed in detail.     

Data management and control-flow aspects of an SIMD/SPMD parallellanguage/compiler

Features of an explicitly parallel programming language targeted for reconfigurable parallel processing systems, where the machine's N processing elements (PEs) are capable of operating in both the SIMD and SPMD modes of parallelism, are described. The SPMD (single program-multiple data) mode of parallelism is a subset of the MIMD mode where all processors execute the same program. By providing all aspects of the language with an SIMD mode version and an SPMD mode version that are syntactically and semantically equivalent, the language facilitates experimentation with and exploitation of hybrid SIMD/SPMD machines. Language constructs (and their implementations) for data management, data-dependent control-flow, and PE-address-dependent control-flow are presented. These constructs are based on experience gained from programming a parallel machine prototype and are being incorporated into a compiler under development. Much of the research presented is applicable to general SIMD machines and MIMD machines     

Evaluating the performance of a SISAL implementation of the abingdon cross image processing benchmark

There are many paradigms being promoted and explored for programming parallel computers, including modified sequential languages, new imperative languages and applicative languages. SISAL is an applicative language which has been designed by a consortium of industrial and research organizations for the specification and execution of parallel programs. It allows programs to be written with little concern for the structure of the underlying machine, thus the programmer is free to explore different ways of expressing the parallelism. A major problem with applicative languages has been their poor efficiency at handling large data structures. To counter this problem SISAL includes some advanced memory management techniques for reducing the amount of data copying that occurs. In this paper we discuss the implementation of some image processing benchmarks in SISAL and C to evaluate the effectiveness of the memory management code. In general, the SISAL program was easier to code than the C (augmented with the PARMACS macros) because we were not concerned with the parallel implementation details. We found that the SISAL performance was in general comparable to C, and that it could be brought in line with an efficient parallel C implementation by some programmer-specified code transformations.     

A case study of parallel execution of a rule-based expert system

We report on a case study of the potentials for parallel execution of the inference engine of EMYCIN, a rule-based expert system. Multilisp, which supports parallel execution of tasks by means of thefuture construct, is used to implement the parallel version of the backwards-chaining inference engine. The study uses explicit specification of parallel execution and synchronization to attain parallel execution. It suggests some general techniques for obtaining parallel execution in expert systems and other applications.     

The parallel corpus for information extraction based on natural language processing and machine translation

In conventional algorithms, the lack of entity information, reference, and semantic relations in the current corpus leads to a low rate of precision and efficiency in constructing cross‐language bilingual mapping. According to natural language processing and machine translation technology, to solve the problem, this paper aims to establish a parallel corpus for information extraction based on the OntoNotes corpus by combining automatic extraction and manual adjustment. To verify the validity of the parallel corpus constructed in this paper, a comparative experiment was carried out on the corpus. The corpus entity alignment rate, anaphora absence, and syntactic structure were analysed in detail based on statistics. The data set is well performed in language processing and machine translation. The parallel corpus for information extraction constructed in this paper can produce highly precise, stable, and efficient information in the process of bilingual mapping, which provides an effective parallel corpus for the study in machine translation of bilingual mapping.     

Mayfly: A general-purpose, scalable, parallel processing architecture

TheMayfly is a scalable general-purpose parallel processing system being designed at HP Laboratories, in collaboration with colleagues at the University of Utah. The system is intended to efficiently support parallel variants of modern programming languages such as Lisp, Prolog, and Object Oriented Programming models. These languages impose a common requirement on the hardware platform to supportdynamic system needs such as runtime type checking and dynamic storage management. The main programming language for the Mayfly is a concurrent dialect of Scheme. The system is based on a distributed-memory model, and communication between processing elements is supported by message passing. The initial prototype of Mayfly will consist of 19 identical processing elements interconnected in a hexagonal mesh structure. In order to achieve the goal of scalable performance, each processing element is a parallel processor as well, which permits the application code, runtime operating system, and communication to all run in parallel. A 7 processing element subset of the prototype is presently operational. This paper describes the hardware architecture after a brief background synopsis of the software system structure.     

基于Internet和多传感器融合的工厂自动化专家网络

本文介绍了在未来网络化时代工业自动化中的一种基本技术框架－基于Ｉｎｔｅｒｎｅｔ环境和多传感器融合的专家网络。基于模糊逻辑和要素空间理论，我们试图开发适于各种工业应用的通用软件平台和硬件结构。系统是一种适合于工业自动化中的专家系统的专家机。人们使用ＨＴＭＬ和ｓｍａｒｔ ａｐｐｌｅｔｓ（用Ｊａｖａ语言编写的模糊逻辑算法小应用程序）来实现知识的获取，知识库的建立，知识的共享以及实时问题的解决。