Demand-driven logic simulation using a network of loosely coupled processors

Logic simulation is used extensively in the design of digital systems for the purpose of studying the behaviour of circuits under various conditions and for verifying the required performance of circuits. There is considerable interest in methods which reduce the simulation time during the design process. In this paper, we investigate how this can be achieved by simulating the action of logic circuits using a network of loosely coupled processors. Circuits modelled as directed graphs comprising clocked sequential components and (unclocked) arbitrary combinational logic gates can be partitioned into separate tasks each consisting of a sequential component with an associated network of combinational components. We present cost functions for evaluating a task subject to probabilistic assumptions about the functioning of the circuits. The circuit evaluation method used in the simulation process is significant. We apply lazy evaluation, a demand-driven evaluation strategy in which signals in the circuit are evaluated on a ‘need to do' basis, resulting in a considerable saving in circuit simulation time. We achieve distributed logic simulation using a network of workstations and show from experimental results that by using such a configuration, we essentially obtain a single computation engine which can be used to obtain speedups in circuit simulation when compared with uniprocessor simulation systems. Interprocess communications between tasks on different workstations proceed via remote procedure calls while local communications between tasks take place via shared memory. The method of partitioning used in the circuit model ensures that communications between tasks take place only at defined times in the simulation sequence.     

应用需求驱动的多层作业成本模型设计制造业成本管理系统

首先介绍了作业成本法的基本概念和应用情况 ,随后描述和分析了需求驱动的多层次作业成本模型 ,并探讨了以作业成本法为基础对企业制造成本进行优化的方法 ,同时详细介绍了基于此模型设计和开发的某铸造厂作业成本管理系统的具体功能和系统架构     

Primitives for resource management in a demand-driven reduction model

Graph reduction has recently become well-known as a suitable technique for implementing applicative languages. However, its use hitherto has been primarily in implementing determinate programs. This paper is concerned with extensions to a demand-driven graph reduction language for performing resource management, and entail indeterminate operations. Our focus is on primitives for programming the synchronization and scheduling of resources, as found, for example, in operating systems. We propose queueing operators and operators for controlling the order of execution of operations. We show that demand-driven graph reduction simplifies the implementation of resource management, especially in obviating explicit protocols for task creation and deletion, and for busy waiting. The language FGL (Function Graph Language) is first introduced, and the primitives are presented in this language. A number of examples are then presented to show the versatility of these primitives. The paper concludes with a brief sketch of a higher-level notation, calledresource expressions, for specifying synchronization properties.This research was undertaken while the authors were at the University of Utah, Salt Lake City, and was supported by a grant MCS77-09369 A01 from the National Science Foundation.     

A PARALLEL DEMAND-DRIVEN SIMULATION ALGORITHM FOR SIMD COMPUTERS

Abstract

This paper describes nPSA, a parallel algorithm for distributed asynchronous simulation of digital circuits with nominal delays in a massively parallel SIMD environment. Glitch detection and suppression are included, together with a discussion of other factors, such as recon-vergent fan-out and feedback lines. A new set of metrics is also proposed for evaluation purposes. nPSA combines demand-driven and deadlock avoidance protocols in order to deliver high performance compared to typical synchronous parallel simulators. Although its performance greatly depends on the quality of circuit embedding on the host machine, nPSA is independent of the computer architecture and communication protocol used.     

A new hybrid algorithm for university course timetabling problem using events based on groupings of students

In this paper, a new hybrid algorithm (NHA) combining genetic algorithm with local search and using events based on groupings of students is described to solve the university course timetabling problem. A list of events such as lectures, tutorials, laboratories and seminars are ordered and mutually disjoint groups of students taking them are formed in such a way that once a student is selected in any group, he is excluded from further selection in other groups. The union of all the events taken by all the students of each group is formed. The number of events in each group is termed as its group size whose upper bound is restricted by the total number of timeslots and can be reduced to the maximum number of events per student. The above process of forming groups is repeated till the size of each group is reduced within this bound by not choosing those events which are common for all the students in the group. Now, the genetic algorithm with local search (GALS) is applied on a number of benchmark problems. The experimental results show that our algorithm, NHA, is able to produce promising results when compared with the results obtained by using GALS and other existing algorithms.     

基于需求驱动的雷达参数测试软件开发方法研究

为了提高雷达参数测试软件的开发效率及测试仪器的互换性,通过对雷达参数测试进行详尽的用例需求分析,在归纳总结测试需求的基础上使用UML语言建立了基于需求驱动的雷达参数测试软件开发模型,并详细介绍了模型中的类图设计方法;实践表明该模型能够在雷达参数测试中完成雷达装备天线增益、天线方向图及灵敏度等相应测试项目的 组合配置,大大提高了测试软件的开发效率及仪器的互换性,对于其他装备参数软件开发也具备一定的参考、借鉴价值.     

Modelling errors, entropy and the hydraulic reliability of water distribution systems

This paper reports on an investigation of the possible influence of modelling errors on the relationship between the entropy and hydraulic reliability of water distribution systems. The errors are due to minor differences between the design optimisation and subsequent simulation models, which lead to small discrepancies between the capacity of the network and the required supply. Pressure-dependent analysis was used for the hydraulic simulations. It is shown that any correlation between the redundancy or undercapacity due to the modelling errors and the hydraulic reliability is insignificant. The results, therefore, provide yet more evidence that the entropy-reliability relationship is strong.     

Heuristics for demand-driven disassembly planning

Remanufacturing of used products has become accepted as an advantageous disposition option within the field of reverse logistics. Remanufacturing, where a firm takes returned products at the end of their life and disassembles them to obtain parts which are reassembled into “good as new” products, may require so-called demand-driven- disassembly, where a specific amount of returned products must be disassembled to yield parts which are either demanded externally, or used in the remanufacturing operation. While in its simplest form, the solution can be merely calculated, more realistically complex product structures require a more powerful solution method. The first choice, integer programming (IP) can be used to arrive at an optimal solution, with the disadvantage that the time required to solve the problem explodes with increasingly complex product structures and longer time horizons. Another possible method, heuristics which were presented in a previous work on this problem [Taleb and Gupta (Computers & Industrial Engineering 1997; 32(4): 949–61], offer a faster, easier solution with the disadvantage that it is not necessarily optimal, and under certain circumstances may deliver an infeasible result. In this work, this problem was corrected and the heuristic was extended in several important ways to deal with holding costs and external procurement of items. The methodology is illustrated by an example. Another advantage of the heuristic is that it can be programmed into code and executed via spreadsheet application, which will facilitate its application. A performance study reveals that the new heuristic performs quite well for a wide spectrum of randomly generated problem test instances.     

Determining Conditions of Intermittently Fed Digesters from Biogas Production Rate Data

As the contribution from renewable energy to the power grid increases, biogas plants could profit from on-demand production. Flexible feeding can supplement gas storage for further benefits. Changing to flexible feeding introduces transient events to the feeding, and by monitoring the system response to the feeding transients it is possible to gain information about the system stability. Testing was performed at the laboratory and pilot scale to investigate the response characteristics. A statistical analysis was carried out to assess the response to feeding events and make an estimate of the system stability. This analysis was then used as the input to a proportional integral derivative controller for controlling the feeding rate for an anaerobic digestion model No. 1 simulation.     

Peaking demand factor-based reliability analysis of water distribution systems

Water demands vary and consideration of the probabilistic nature of the variations should lead to more instructive assessments of the performance of water distribution systems. Water consumption data for several households were analysed using the chi-square technique and it was found that distributions worth considering under certain circumstances include the normal and lognormal.Reliability values were calculated for a range of critical demand values and the corresponding confidence levels determined from the probability distributions. Water consumption was assumed to be pressure dependent and the modelling of the water distribution system was carried out accordingly. This peaking factor approach coupled with the statistical modelling of demands provides a more realistic way of incorporating variations in demands in the evaluation and reporting of system performance than the traditional single demand value approach in that the extent to which a network can satisfy any demand and the probability that the demand will occur can be recognized explicitly. The method is illustrated by an example.