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     

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     

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.     

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.     

Bounded disorder file organization

The bounded disorder file organization proposed by W. Litwin and D.B. Lomet (1987) uses a combination of hashing and tree indexing. Lomet provided an approximate analysis with the mention of the difficulty involved in exact modeling of data nodes, which motivated this work. In an earlier paper (M.V. Ramakrishna and P. Mukhopadhyay, 1988) we provided an exact model and analysis of the data nodes, which is based on the solution of a classical sequential occupancy problem. After summarizing the analysis of data nodes, an alternate file growth method based on repeated trials using universal hashing is proposed and analyzed. We conclude that the alternate file growth method provides simplicity and significant improvement in storage utilization     

Volcano-an extensible and parallel query evaluation system

To investigate the interactions of extensibility and parallelism in database query processing, we have developed a new dataflow query execution system called Volcano. The Volcano effort provides a rich environment for research and education in database systems design, heuristics for query optimization, parallel query execution, and resource allocation. Volcano uses a standard interface between algebra operators, allowing easy addition of new operators and operator implementations. Operations on individual items, e.g., predicates, are imported into the query processing operators using support functions. The semantics of support functions is not prescribed; any data type including complex objects and any operation can be realized. Thus, Volcano is extensible with new operators, algorithms, data types, and type-specific methods. Volcano includes two novel meta-operators. The choose-plan meta-operator supports dynamic query evaluation plans that allow delaying selected optimization decisions until run-time, e.g., for embedded queries with free variables. The exchange meta-operator supports intra-operator parallelism on partitioned datasets and both vertical and horizontal inter-operator parallelism, translating between demand-driven dataflow within processes and data-driven dataflow between processes. All operators, with the exception of the exchange operator, have been designed and implemented in a single-process environment, and parallelized using the exchange operator. Even operators not yet designed can be parallelized using this new operator if they use and provide the interator interface. Thus, the issues of data manipulation and parallelism have become orthogonal, making Volcano the first implemented query execution engine that effectively combines extensibility and parallelism     

Machine independent AND and OR parallel execution of logicprograms. I. The binding environment

We describe a binding environment for the AND and OR parallel execution of logic programs that is suitable for both shared and nonshared memory multiprocessors. The binding environment was designed with a view of rendering a compiler using this binding environment machine independent. The binding environment is similar to closed environments proposed by J. Conery. However, unlike Conery's scheme, it supports OR and independent AND parallelism on both types of machines. The term representation, the algorithms for unification and the join algorithms for parallel AND branches are presented in this paper. We also detail the differences between our scheme and Conery's scheme. A compiler based on this binding environment has been implemented on a platform for machine independent parallel programming called the Chare Kernel     

E-kernel: an embedding kernel on the IBM victor V256 multiprocessorfor program mapping and network reconfiguration

We present the design of E-kernel, an embedding kernel on the Victor V256 message-passing partitionable multiprocessor, developed for the support of program mapping and network reconfiguration. E-kernel supports the embedding of a new network topology onto Victor's 2D mesh and also the embedding of a task graph onto the 2D mesh network or the reconfigured network. In the current implementation, the reconfigured network can be a line or an even-size ring, and the task graphs meshes or tori of a variety of dimensions and shapes or graphs with similar topologies. For application programs having these task graph topologies and that are designed according to the communication model of E-kernel, they can be run without any change on partitions connected by the 2D mesh, line, or ring. Further, E-kernel attempts the communication optimization of these programs on the different networks automatically, thus making both the network topology and the communication optimization attempt completely transparent to the application programs. Many of the embeddings used in E-kernel are optimal or asymptotically optimal (with respect to minimum dilation cost). The implementation of E-kernel translated some of the many theoretical results in graph embeddings into practical tools for program mapping and network reconfiguration in a parallel system. E-kernel is functional on Victor V256. Measurements of E-kernel's performance on V256 are also included