Low-truncation-error finite difference equations for photonicssimulation. II. Vertical-cavity surface-emitting lasers

For part I see, ibid., p. 134, 1998. The basic approach outlined in the previous article is applied to the difficult problem of computing the optical modes of a vertical-cavity surface-emitting laser. The formulation utilizes a finite difference equation based upon the lowest order term of an infinite series solution of the scalar Helmholtz equation in a local region. This difference equation becomes exact in the one-dimensional (1-D) limit, and is thus ideally suited for nearly 1-D devices such as vertical-cavity lasers. The performance of the resulting code is tested on both a simple cylindrical cavity with known solutions and an oxide-confined vertical-cavity laser structure, and the results compared against second-order-accurate code based upon Crank-Nicolson differencing     

Function materialization in object bases: design, realization, andevaluation

View materialization is a well-known optimization technique of relational database systems. We present a similar, yet more powerful, optimization concept for object-oriented data models: function materialization. Exploiting the object-oriented paradigm-namely, classification, object identity, and encapsulation-facilitates a rather easy incorporation of function materialization into (existing) object-oriented systems. Only those types (classes) whose instances are involved in some materialization are appropriately modified and recompiled, thus leaving the remainder of the object system invariant. Furthermore, the exploitation of encapsulation (information hiding) and object identity provides for additional performance tuning measures that drastically decrease the invalidation and rematerialization overhead incurred by updates in the object base. First, it allows us to cleanly separate the object instances that are irrelevant for the materialized functions from those that are involved in the materialization of some function result, and this to penalize only those involved objects upon update. Second, the principle of information hiding facilitates fine-grained control over the invalidation of precomputed results. Based on specifications given by the data type implementor, the system can exploit operational semantics to better distinguish between update operations that invalidate a materialized result and those that require no rematerialization. The paper concludes with a quantitative analysis of function materialization based on two sample performance benchmarks obtained from our experimental object base system GOM     

RAPS: a rule-based language for specifying resource allocation andtime-tabling problems

A general language for specifying resource allocation and time-tabling problems is presented. The language is based on an expert system paradigm that was developed previously by the authors and that enables the solution of resource allocation problems by using experts' knowledge and heuristics. The language enables the specification of a problem in terms of resources, activities, allocation rules, and constraints, and thus provides a convenient knowledge acquisition tool. The language syntax is powerful and allows the specification of rules and constraints that are very difficult to formulate with traditional approaches, and it also supports the specification of various control and backtracking strategies. We constructed a generalized inference engine that runs compiled resource allocation problem specification language (RAPS) programs and provides all necessary control structures. This engine acts as an expert system shell and is called expert system for resource allocation (ESRA). The performance of RAPS combined with ESRA is demonstrated by analyzing its solution of a typical resource allocation problem     

Partial indexing for nonuniform data distributions in relationalDBMS's

It is well known that the effectiveness of relational database systems is greatly dependent on the efficiency of the data access strategies. For this reason, much work has been devoted to the development of new access techniques, supported by adequate access structures such as the B⁺trees. The effectiveness of the B ⁺tree also depends on the data distribution characteristics; in particular, poor performance results when the data show strong key value distribution unbalancing. The aim of this paper is to present the partial index: a new access structure that is useful in such cases of unbalancing, as an alternative to the B⁺tree unclustered indexes. The access structures are built in the physical design phase, and at execution (or compilation) time, the optimizer chooses the most efficient access path. Thus, integration of the partial indexing technique in the design and in the optimization process are also described     

Sort vs. hash revisited

Efficient algorithms for processing large volumes of data are very important both for relational and new object-oriented database systems. Many query-processing operations can be implemented using sort- or hash-based algorithms, e.g. intersections, joins, and duplicate elimination. In the early relational database systems, only sort-based algorithms were employed. In the last decade, hash-based algorithms have gained acceptance and popularity, and are often considered generally superior to sort-based algorithms such as merge-join. In this article, we compare the concepts behind sort- and hash-based query-processing algorithms and conclude that (1) many dualities exist between the two types of algorithms, (2) their costs differ mostly by percentages rather than by factors, (3) several special cases exist that favor one or the other choice, and (4) there is a strong reason why both hash- and sort-based algorithms should be available in a query-processing system. Our conclusions are supported by experiments performed using the Volcano query execution engine     

Evaluation of a parallel branch-and-bound algorithm on a class ofmultiprocessors

We propose and evaluate a parallel “decomposite best-first” search branch-and-bound algorithm (dbs) for MIN-based multiprocessor systems. We start with a new probabilistic model to estimate the number of evaluated nodes for a serial best-first search branch-and-bound algorithm. This analysis is used in predicting the parallel algorithm speed-up. The proposed algorithm initially decomposes a problem into N subproblems, where N is the number of processors available in a multiprocessor. Afterwards, each processor executes the serial best-first search to find a local feasible solution. Local solutions are broadcasted through the network to compute the final solution. A conflict-free mapping scheme, known as the step-by-step spread, is used for subproblem distribution on the MIN. A speedup expression for the parallel algorithm is then derived using the serial best-first search node evaluation model. Our analysis considers both computation and communication overheads for providing realistic speed-up. Communication modeling is also extended for the parallel global best-first search technique. All the analytical results are validated via simulation. For large systems, when communication overhead is taken into consideration, it is observed that the parallel decomposite best-first search algorithm provides better speed-up compared to other reported schemes     

Unstructured tree search on SIMD parallel computers

We present new methods for load balancing of unstructured tree computations on large-scale SIMD machines, and analyze the scalability of these and other existing schemes. An efficient formulation of tree search on an SIMD machine consists of two major components: a triggering mechanism, which determines when the search space redistribution must occur to balance the search space over processors, and a scheme to redistribute the search space. We have devised a new redistribution mechanism and a new triggering mechanism. Either of these can be used in conjunction with triggering and redistribution mechanisms developed by other researchers. We analyze the scalability of these mechanisms and verify the results experimentally. The analysis and experiments show that our new load-balancing methods are highly scalable on SIMD architectures. Their scalability is shown to he no worse than that of the best load-balancing schemes on MIMD architectures. We verify our theoretical results by implementing the 15-puzzle problem on a CM-2 SIMD parallel computer     

Parallel architecture for fast transforms with trigonometric kernel

We present an unified parallel architecture for four of the most important fast orthogonal transforms with trigonometric kernel: Complex Valued Fourier (CFFT), Real Valued Fourier (RFFT), Hartley (FHT), and Cosine (FCT). Out of these, only the CFFT has a data flow coinciding with the one generated by the successive doubling method, which can be transformed on a constant geometry flow using perfect unshuffle or shuffle permutations. The other three require some type of hardware modification to guarantee the constant geometry of the successive doubling method. We have defined a generalized processing section (PS), based on a circular CORDIC rotator, for the four transforms. This PS section permits the evaluation of the CFFT and FCT transforms in n data recirculations and the RFFT and FHT transforms in n-1 data recirculations, with n being the number of stages of a transform of length N=rⁿ. Also, the efficiency of the partitioned parallel architecture is optimum because there is no cycle loss in the systolic computation of all the butterflies for each of the four transforms     

The classification, fusion, and parallelization of array languageprimitives

We present a classification scheme for array language primitives that quantifies the variation in parallelism and data locality that results from the fusion of any two primitives. We also present an algorithm based on this scheme that efficiently determines when it is beneficial to fuse any two primitives. Experimental results show that five LINPACK routines report 50% performance improvement from the fusion of array operators     

Comments on “Can backpropagation error surface not have localminima?”

in the above paper Yu (IEEE Trans. Neural Networks, vol.3, no.6, p.1019-21 (1992)) claims to prove that local minima do not exist in the error surface of backpropagation networks being trained on data with t distinct input patterns when the network is capable of exactly representing arbitrary mappings on t input patterns. The commenter points out that the proof presented is flawed, so that the resulting claims remain unproved. In reply, Yu points out that the undesired phenomenon that was sited can be avoided by simply imposing the arbitrary mapping capacity of the network on lemma 1 in the article.