Fast algorithm for data exchange in reconfigurable tree structures

This paper presents a fast algorithm for data exchange in a network of processors organized as a reconfigurable tree structure. For a given data exchange table, the algorithm generates a sequence of tree configurations in which the data exchanges are to be executed. A significant feature of the algorithm is that each exchange is executed in a tree configuration in which the source and destination nodes are adjacent to each other. It has been proved in a theorem that for every pair of nodes in the reconfigurable tree structure, there always exists two and only two configurations in which these two nodes are adjacent to each other. The algorithm utilizes this fact and determines the solution so as to optimize both the number of configurations required and the time to perform the data exchanges. Analysis of the algorithm shows that it has linear time complexity, and provides a large reduction in run-time as compared to a previously proposed algorithm. This is well-confirmed from the experimental results obtained by executing a large number of randomly-generated data exchange tables. Another significant feature of the algorithm is that the bit-size of the routing information code is always two bits, irrespective of the number of nodes in the tree. This not only increases the speed of the algorithm but also results in simpler hardware inside each node.

Pipelined ring algorithm for matrix multiplication on transputer networks: performance analysis and estimation

A parallel matrix multiplication algorithm is presented, and studies of its performance and estimation are discussed. The algorithm is implemented on a network of transputers connected in a ring topology. An efficient scheme for partitioning the input matrices is introduced which enables overlapping computation with communication. This makes the algorithm achieve near-ideal speed-up for reasonably large matrices. Analytical expressions for the execution time of the algorithm have been derived by analysing its computation and communication characteristics. These expressions are validated by comparing the theoretical results of the performance with the experimental values obtained on a four-transputer network for both square and irregular matrices. The analytical model is also used to estimate the performance of the algorithm for a varying number of transputers and varying problem sizes. Although the algorithm is implemented on transputers, the methodology and the partitioning scheme presented in this paper are quite general and can be implemented on other processors which have the capability of overlapping computation with communication. The equations for performance prediction can also be extended to other multiprocessor systems.

Effect of Short Duration of Load increment on the Compressibility of Soils

This study concerns the effect of duration of load increment (up to 24 h) on the consolidation properties of expansive black cotton soil (liquid limit = 81%) and nonexpansive kaolinite (liquid limit = 49%). It indicates that the amount and rate of compression are not noticeably affected by the duration of loading for a standard sample of 25 mm in height and 76.2 mm in diameter with double drainage. Hence, the compression index and coefficient of consolidation can be obtained with reasonable accuracy even if the duration of each load increment is as short as 4 h. The secondary compression coefficient (C-alpha epsilon) for kaolinite can be obtained for any pressure range with 1/2 h of loading, which, however, requires 4 h for black cotton soil. This is because primary consolidation is completed early in the case of kaolinite. The paper proves that the conventional consolidation test can be carried out with much shorter duration of loading (less than 4 h) than the standard specification of 24 h or more even for remolded fine-grained soils.

Multi-installment load distribution in tree networks with delays

This paper presents a new strategy for load distribution in a single-level tree network equipped with or without front-ends. The load is distributed in more than one installment in an optimal manner to minimize the processing time. This is a deviation and an improvement over earlier studies in which the load distribution is done in only one installment. Recursive equations for the general case, and their closed form solutions for a special case in which the network has identical processors and identical links, are derived. An asymptotic analysis of the network performance with respect to the number of processors and the number of installments is carried out. Discussions of the results in terms of some practical issues like the tradeoff relationship between the number of processors and the number of installments are also presented.

Vibration Signature Analysis Using Artificial Neural Networks

Damage detection by measuring and analyzing vibration signals in a machine component is an established procedure in mechanical and aerospace engineering. This paper presents vibration signature analysis of steel bridge structures in a nonconventional way using artificial neural networks (ANN). Multilayer perceptrons have been adopted using the back-propagation algorithm for network training. The training patterns in terms of vibration signature are generated analytically for a moving load traveling on a trussed bridge structure at a constant speed to simulate the inspection vehicle. Using the finite-element technique, the moving forces are converted into stationary time-dependent force functions in order to generate vibration signals in the structure and the same is used to train the network. The performance of the trained networks is examined for their capability to detect damage from unknown signatures taken independently at one, three, and five nodes. It has been observed that the prediction using the trained network with single-node signature measurement at a suitability chosen location is even better than that of three-node and five-node measurement data.

An Efficient Robust Algorithm for the Surface-Potential Calculation of Independent DG MOSFET

Although the recently proposed single-implicit-equation-based input voltage equations (IVEs) for the independent double-gate (IDG) MOSFET promise faster computation time than the earlier proposed coupled-equations-based IVEs, it is not clear how those equations could be solved inside a circuit simulator as the conventional Newton-Raphson (NR)-based root finding method will not always converge due to the presence of discontinuity at the G-zero point (GZP) and nonremovable singularities in the trigonometric IVE. In this paper, we propose a unique algorithm to solve those IVEs, which combines the Ridders algorithm with the NR-based technique in order to provide assured convergence for any bias conditions. Studying the IDG MOSFET operation carefully, we apply an optimized initial guess to the NR component and a minimized solution space to the Ridders component in order to achieve rapid convergence, which is very important for circuit simulation. To reduce the computation budget further, we propose a new closed-form solution of the IVEs in the near vicinity of the GZP. The proposed algorithm is tested with different device parameters in the extended range of bias conditions and successfully implemented in a commercial circuit simulator through its Verilog-A interface.

Studies on age-hardening characteristics of ceramic particle/matrix interfaces in Al-Cu-SiCp composites using ultra low-load-dynamic microhardness measurements

Ultra low-load-dynamic microhardness testing facilitates the hardness measurements in a very low volume of the material and thus is suited for characterization of the interfaces in MMC's. This paper details the studies on age-hardening behavior of the interfaces in Al-Cu-5SiC(p) composites characterized using this technique. Results of hardness studies have been further substantiated by TEM observations. In the solution-treated condition, hardness is maximum at the particle/matrix interface and decreases with increasing distance from the interface. This could be attributed to the presence of maximum dislocation density at the interface which decreases with increasing distance from the interface. In the case of composites subjected to high temperature aging, hardening at the interface is found to be faster than the bulk matrix and the aging kinetics becomes progressively slower with increasing distance from the interface. This is attributed to the dislocation density gradient at the interface, leading to enhanced nucleation and growth of precipitates at the interface compared to the bulk matrix. TEM observations reveal that the sizes of the precipitates decrease with increasing distance from the interface and thus confirms the retardation in aging kinetics with increasing distance from the interface.

The actor-critic algorithm as multi-time-scale stochastic approximation

The actor-critic algorithm of Barto and others for simulation-based optimization of Markov decision processes is cast as a two time Scale stochastic approximation. Convergence analysis, approximation issues and an example are studied.

Modelling electricity demand with representative load curves

Models for electricity planning require inclusion of demand. Depending on the type of planning, the demand is usually represented as an annual demand for electricity (GWh), a peak demand (MW) or in the form of annual load-duration curves. The demand for electricity varies with the seasons, economic activities, etc. Existing schemes do not capture the dynamics of demand variations that are important for planning. For this purpose, we introduce the concept of representative load curves (RLCs). Advantages of RLCs are demonstrated in a case study for the state of Karnataka in India. Multiple discriminant analysis is used to cluster the 365 daily load curves for 1993-94 into nine RLCs. Further analyses of these RLCs help to identify important factors, namely, seasonal, industrial, agricultural, and residential (water heating and air-cooling) demand variations besides rationing by the utility. (C) 1999 Elsevier Science Ltd. All rights reserved.

A fault-tolerant distributed deadlock detection algorithm

In this paper, we propose a new fault-tolerant distributed deadlock detection algorithm which can handle loss of any resource release message. It is based on a token-based distributed mutual exclusion algorithm. We have evaluated and compared the performance of the proposed algorithm with two other algorithms which belong to two different classes, using simulation studies. The proposed algorithm is found to be efficient in terms of average number of messages per wait and average deadlock duration compared to the other two algorithms in all situations, and has comparable or better performance in terms of other parameters.

In-situ power monitoring scheme and its application in dynamic voltage and threshold scaling for digital CMOS integrated circuits

An in-situ power monitoring technique for Dynamic Voltage and Threshold scaling (DVTS) systems is proposed which measures total power consumed by load circuit using sleep transistor acting as power sensor. Design details of power monitor are examined using simulation framework in UMC 90nm CMOS process. Experimental results of test chip fabricated in AMS 0.35µm CMOS process are presented. The test chip has variable activity between 0.05 and 0.5 and has PMOS VTH control through nWell contact. Maximum resolution obtained from power monitor is 0.25mV. Overhead of power monitor in terms of its power consumption is 0.244 mW (2.2% of total power of load circuit). Lastly, power monitor is used to demonstrate closed loop DVTS system. DVTS algorithm shows 46.3% power savings using in-situ power monitor.

A reinforcement learning approach to automatic generation control

This paper formulates the automatic generation control (AGC) problem as a stochastic multistage decision problem. A strategy for solving this new AGC problem formulation is presented by using a reinforcement learning (RL) approach This method of obtaining an AGC controller does not depend on any knowledge of the system model and more importantly it admits considerable flexibility in defining the control objective. Two specific RL based AGC algorithms are presented. The first algorithm uses the traditional control objective of limiting area control error (ACE) excursions, where as, in the second algorithm, the controller can restore the load-generation balance by only monitoring deviation in tie line flows and system frequency and it does not need to know or estimate the composite ACE signal as is done by all current approaches. The effectiveness and versatility of the approaches has been demonstrated using a two area AGC model. (C) 2002 Elsevier Science B.V. All rights reserved.

A token-based distributed algorithm for total order atomic broadcast

In this paper, we propose a new token-based distributed algorithm for total order atomic broadcast. We have shown that the proposed algorithm requires lesser number of messages compared to the algorithm where broadcast servers use unicasting to send messages to other broadcast servers. The traditional method of broadcasting requires 3(N - 1) messages to broadcast an application message, where N is the number of broadcast servers present in the system. In this algorithm, the maximum number of token messages required to broadcast an application message is 2N. For a heavily loaded system, the average number of token messages required to broadcast an application message reduces to 2, which is a substantial improvement over the traditional broadcasting approach.

Identification of delamination in composite beams using spectral estimation and a genetic algorithm

An efficient strategy for identification of delamination in composite beams and connected structures is presented. A spectral finite-element model consisting of a damaged spectral element is used for model-based prediction of the damaged structural response in the frequency domain. A genetic algorithm (GA) specially tailored for damage identification is derived and is integrated with finite-element code for automation. For best application of the GA, sensitivities of various objective functions with respect to delamination parameters are studied and important conclusions are presented. Model-based simulations of increasing complexity illustrate some of the attractive features of the strategy in terms of accuracy as well as computational cost. This shows the possibility of using such strategies for the development of smart structural health monitoring softwares and systems.