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     

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     

Processor membership in asynchronous distributed systems

Presents protocols for determining processor membership in asynchronous distributed systems that are subject to processor and communication faults. These protocols depend on the placement of a total order on broadcast messages. The types of systems for which each of these protocols is applicable are characterized by the properties of the communication mechanisms and by the availability of stable storage. In the absence of stable storage or of a mechanism for distinguishing promptly delivered messages, the authors show that no membership protocol can exist. They also discuss their experience in implementing these membership protocols     

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     

Unicast-based multicast communication in wormhole-routed networks

Multicast communication, in which the same message is delivered from a source node to an arbitrary number of destination nodes, is being increasingly demanded in parallel computing. System supported multicast services can potentially offer improved performance, increased functionality, and simplified programming, and may in turn be used to support various higher-level operations for data movement and global process control. This paper presents efficient algorithms to implement multicast communication in wormhole-routed direct networks, in the absence of hardware multicast support, by exploiting the properties of the switching technology. Minimum-time multicast algorithms are presented for n-dimensional meshes and hypercubes that use deterministic, dimension-ordered routing of unicast messages. Both algorithms can deliver a multicast message to m-1 destinations in [log ₂ m] message passing steps, while avoiding contention among the constituent unicast messages. Performance results of implementations on a 64-node nCUBE-2 hypercube and a 168-node Symult 2010 2-D mesh are given     

Quantization effects in digitally behaving circuit implementationsof Kohonen networks

Implementing a neural network on a digital or mixed analog and digital chip yields the quantization of the synaptic weights dynamics. This paper addresses this topic in the case of Kohonen's self-organizing maps. We first study qualitatively how the quantization affects the convergence and the properties, and deduce from this analysis the way to choose the parameters of the network (adaptation gain and neighborhood). We show that a spatially decreasing neighborhood function is far more preferable than the usually rectangular neighborhood function, because of the weight quantization. Based on these results, an analog nonlinear network, integrated in a standard CMOS technology, and implementing this spatially decreasing neighborhood function is then presented. It can be used in a mixed analog and digital circuit implementation.     

On loop transformations for generalized cycle shrinking

This paper describes several loop transformation techniques for extracting parallelism from nested loop structures. Nested loops can then be scheduled to run in parallel so that execution time is minimized. One technique is called selective cycle shrinking, and the other is called true dependence cycle shrinking. It is shown how selective shrinking is related to linear scheduling of nested loops and how true dependence shrinking is related to conflict-free mappings of higher dimensional algorithms into lower dimensional processor arrays. Methods are proposed in this paper to find the selective and true dependence shrinkings with minimum total execution time by applying the techniques of finding optimal linear schedules and optimal and conflict-free mappings proposed by W. Shang and A.B. Fortes     

The fault-tolerant extension problem for complete multipartitenetworks

We develop a characterization for m-fault-tolerant extensions, and for optimal m-fault-tolerant extensions, of a complete multipartite graph. Our formulation shows that this problem is equivalent to an interesting combinatorial problem on the partitioning of integers. This characterization leads to a new procedure for constructing an optimal m-fault-tolerant extension of any complete multipartite graph, for any m⩾0. The proposed procedure is mainly useful when the size of the graph is relatively small, because the search time required is exponential. This exponential search, however, is not always necessary. We prove several necessary conditions that help us, in several cases, to identify some optimal m-fault-tolerant extensions without performing any search     

Allocating tree structured programs in a distributed system withuniform communication costs

Studies the complexity of the problem of allocating m modules to n processors in a distributed system to minimize total communication and execution costs. When the communication graph is a tree, Bokhari has shown that the optimum allocation can be determined in O(mn²) time. Recently, this result has been generalized by Fernandez-Baca, who has proposed an allocation algorithm in O(mn^k+1) when the communication graph is a partial k-tree. The author shows that in the case where communication costs are uniform, the module allocation problem can be solved in O(mn) time if the communication graph is a tree. This algorithm is asymptotically optimum     

Scheduling DAG's for asynchronous multiprocessor execution

A new approach is given for scheduling a sequential instruction stream for execution “in parallel” on asynchronous multiprocessors. The key idea in our approach is to exploit the fine grained parallelism present in the instruction stream. In this context, schedules are constructed by a careful balancing of execution and communication costs at the level of individual instructions, and their data dependencies. Three methods are used to evaluate our approach. First, several existing methods are extended to the fine grained situation. Our approach is then compared to these methods using both static schedule length analyses, and simulated executions of the scheduled code. In each instance, our method is found to provide significantly shorter schedules. Second, by varying parameters such as the speed of the instruction set, and the speed/parallelism in the interconnection structure, simulation techniques are used to examine the effects of various architectural considerations on the executions of the schedules. These results show that our approach provides significant speedups in a wide-range of situations. Third, schedules produced by our approach are executed on a two-processor Data General shared memory multiprocessor system. These experiments show that there is a strong correlation between our simulation results, and these actual executions, and thereby serve to validate the simulation studies. Together, our results establish that fine grained parallelism can be exploited in a substantial manner when scheduling a sequential instruction stream for execution “in parallel” on asynchronous multiprocessors