Covering the basic techniques used in the latest research work, the author consolidates progress made so far, including some very recent and promising results, and conveys the beauty and excitement of work in the field. He gives clear, lucid explanations of key results and ideas, with intuitive proofs, and provides critical examples and numerous illustrations to help elucidate the algorithms. Many of the results presented have been simplified and new insights provided. Of interest to theoretical computer scientists, operations researchers, and discrete mathematicians.

Approximation Algorithms

The success of the von Neumann model of sequential computation is attributable to the fact that it is an efficient bridge between software and hardware: high-level languages can be efficiently compiled on to this model; yet it can be effeciently implemented in hardware. The author argues that an analogous bridge between software and hardware in required for parallel computation if that is to become as widely used. This article introduces the bulk-synchronous parallel (BSP) model as a candidate for this role, and gives results quantifying its efficiency both in implementing high-level language features and algorithms, as well as in being implemented in hardware.

A bridging model for parallel computation

We survey the current techniques to cope with the problem of string matching that allows errors. This is becoming a more and more relevant issue for many fast growing areas such as information retrieval and computational biology. We focus on online searching and mostly on edit distance, explaining the problem and its relevance, its statistical behavior, its history and current developments, and the central ideas of the algorithms and their complexities. We present a number of experiments to compare the performance of the different algorithms and show which are the best choices. We conclude with some directions for future work and open problems.

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A guided tour to approximate string matching

An edited volume containing data structures and algorithms for information retrieved including a disk with examples written in C. For programmers and students interested in parsing text, automated indexing, its the first collection in book form of the basic data structures and algorithms that are critical to the storage and retrieval of documents.

https://hornad.fei.tuke.sk/~genci/Vyucba/OOBDS/Archiv/Podklady/TExtoveIS&IR/Information%20Retrieval%20Data%20Structures%20&%20Algorithms.PDF

Information Retrieval: Data Structures and Algorithms

Often, in the real world, entities have two or more representations in databases. Duplicate records do not share a common key and/or they contain errors that make duplicate matching a difficult task. Errors are introduced as the result of transcription errors, incomplete information, lack of standard formats, or any combination of these factors. In this paper, we present a thorough analysis of the literature on duplicate record detection. We cover similarity metrics that are commonly used to detect similar field entries, and we present an extensive set of duplicate detection algorithms that can detect approximately duplicate records in a database. We also cover multiple techniques for improving the efficiency and scalability of approximate duplicate detection algorithms. We conclude with coverage of existing tools and with a brief discussion of the big open problems in the area

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Duplicate Record Detection: A Survey

The sudden shift from single-processor computer systems to many-processor parallel computing systems requires reinventing much of Computer Science (CS): how to actually build and program the new parallel systems. CS urgently requires convergence to a robust parallel general-purpose platform that provides good performance and is easy to program. Unfortunately, this same objective has eluded decades of parallel computing research. Now, continued delays and uncertainty could start affecting important sectors of the economy. This paper advocates a minimalist stepping-stone: settle first on a simple abstraction that encapsulates the new interface between programmers, on one hand, and system builders, on the other hand. This paper also makes several concrete suggestions: (i) the Immediate Concurrent Execution (ICE) abstraction as a candidate for the new abstraction, and (ii) the Explicit Multi-Threaded (XMT) general-purpose parallel platform, under development at the University of Maryland, as a possible embodiment of ICE. ICE and XMT build on a formidable body of knowledge, known as PRAM (for parallel randomaccess machine, or model) algorithmics, and a latent, though not widespread, familiarity with it. Ease-of-programming, strong speedups and other attractive properties of the approach suggest that we may be much better prepared for the challenges ahead than many realize.

Using Simple Abstraction to Guide the Reinvention of Computing for Parallelism

Consider the serial emulation of a parallel algorithm. The thesis presented in this informal paper is rather broad. It suggests that such a serial emulation has the potential advantage of running on a serial machine faster than a standard serial algorithm for the same problem.The main concrete observation is very simple: just before the serial emulation of a round of the parallel algorithm begins, the whole list of memory addresses needed during this round is readily available; and, we can start fetching these addresses from secondary memories.This enables to prefetch the data that will be needed in the next "time window", perhaps by means of pipelining and have them ready at the fast memories when requested by the CPU. Thereby, utilization of commonly used memory management systems will be theoretically enhanced. Another (considerably less orthodox) implementation approach will result in abandoning locality of references, in favor of a drastically different approach: distribute memory addresses at random over memory modules, as has been proposed in the context of implementing the parallel-random-access machine (PRAM) design space.It is too early to reach conclusions regarding the significance of the thesis of this paper. Serious attempts to follow it up are needed to determine its usefulness. Parts of this paper are intentionally written in an informal way, suppressing issues that will have to be resolved in the context of a concrete implementation. My general intention is to encourage colleagues to: (i) suggest other specific approaches, and (ii) explore opportunities for taking advantage of the fine structure of parallel programs well beyond concrete suggestions made in the paper.The full paper is available as UMIACS TR 91-145, from the Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland 20742--3251.

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Can parallel algorithms enhance serial implementation

Parallel Dictionaries in 2-3 Trees

The paper advocates that the PRAM model of parallel computation will be a standard (but not exclusive) programmer's model for computers whose hardware features various kinds of parallelism.

A Case for the PRAM As a Standard Programmer's Model

The linear time serial algorithm for planarity testing of [LEC-67] uses the linear time serial algorithm of [ET-76] for st-numbering. This st-numbering algorithm is based on depth-first search (DFS). A known conjecture states that DFS, which is a key technique in designing serial algorithms, is not amenable to poly-log time parallelism using "around linearly" (or even polynomially) many processors. The first contribution of this paper is a general method for searching efficiently in parallel undirected graphs, called ear-decomposition search (EDS).

Uzi Vishkin

Papers

Using Simple Abstraction to Guide the Reinvention of Computing for Parallelism

Can parallel algorithms enhance serial implementation

Parallel Dictionaries in 2-3 Trees

A Case for the PRAM As a Standard Programmer's Model

Parallel ear decomposition search (EDS) and st-numbering in graphs