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About 10,000 papers for “Parallel processing”

Instruction-Level Parallel Processing

Joseph A. Fisher, B. Ramakrishna Rau · Science · 1991

The performance of microprocessors has increased steadily over the past 20 years at a rate of about 50% per year. This is the cumulative result of architectural improvements as well as increases in circuit speed. Moreover, this improvement has been obtained in a transparent fashion, that is, without requiring programmers to rethink their algorithms and programs, thereby enabling the tremendous proliferation of computers that we see today. To continue this performance growth, microprocessor designers have incorporated instruction-level parallelism (ILP) into new designs. ILP utilizes the parallel execution ofthe lowest level computer operations-adds, multiplies, loads, and so on-to increase performance transparently. The use of ILP promises to make possible, within the next few years, microprocessors whose performance is many times that of a CRAY-IS. This article provides an overview of ILP, with an emphasis on ILP architectures-superscalar, VLIW, and dataflow processors-and the compiler techniques necessary to make ILP work well.

Cited by 16

Complexity and parallel processing

Karen A. Frenkel · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 1986

This article is an interview with Richard Karp which discusses the relation of his work to leading-edge computing topics like parallel processing and artificial intelligence. Tracing his experience as a pioneer in highly theoretical computer science, Karp describes how the decision to go against established wisdom led to the work for which he is best known and how a colleague's findings led him to see links between two previously unrelated areas.

Cited by 5

Introduction to Parallel Processing

Behrooz Parhami, M Leoncini, M Flynn et al. · Kluwer Academic Publishers eBooks · 2002

THE CONTEXT OF PARALLEL PROCESSING The field of digital computer architecture has grown explosively in the past two decades. Through a steady stream of experimental research, tool-building efforts, an

Cited by 7Open access

PARALLEL PROCESSING OF RESOLUTION

Takahira Yamaguch, Yoshikazu Tezuka, Osamu Kakusho · 2008

In this paper, PArallel Resolution Algorithm (PARA) is described to improve the execution efficiency in resolution process. PARA consists of two parts: parallel unification and generation of a resolvent. The first part is characteristic of PARA, which partitions whole set of expressions W into independent clusters as pre-processing and unifies each cluster in parallel. The efficient implementation for the processing peculiar to PARA is presented and checked by means of the experiment in comparison of execution efficiency of resolution. Experimental results show PARA is very effective in occurrence of many clusters.

Cited by 0

Parallel processing XML documents

Kevin Lü, Yuanling Zhu, Wenjun Sun et al. · Proceedings - International Database Engineering and Applications Symposium · 2003

As Web applications are time vulnerable, the increasing size of XML documents and the complexity of evaluating XML queries pose new performance challenges to existing information retrieval technologies. This paper introduces a new approach for developing a purpose-built XML data management system to improve the system performance of a Web site with XML support by using parallel data processing techniques. To improve the system performance, we propose a parallelisation model for XML data processing, where the data storage strategies, data placement methods and query evaluation techniques have been studied. Other related issues are also presented.

Cited by 19

A parallel processing tutorial

David Davidson · IEEE Antennas and Propagation Magazine · 1990

An overview of parallel computing is provided, with reference to numerical analysis and, in particular, to computational electromagnetics. The history of parallelism is reviewed, and the general principles are provided. The two main types of parallelism encountered, pipelining and replication are discussed, and an example of each is described. A parallel algorithm for forming a matrix-vector product is presented and analyzed. This is then used as the core of a parallel conjugate gradient algorithm. The theoretically predicted efficiency and the measured efficiency are compared. A glossary and a brief discussion of the available literature on parallel processing are included.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cited by 22

Parallel Processing in Statistics

J. D. Sylwestrowicz · 1982

Many statistical calculations can be made more efficient when performed on a parallel processor. Since early 1980 the ICL Distributed Array Processor has been in operation at the Queen Mary College, London. In this paper a brief description of the ICL DAP and its programming language DAP-FORTRAN, is given. Elementary examples of statistical applications are also discussed.

Cited by 4

Special parallel processing workshop

University of North Texas Digital Library (University of North Texas) · 1994

This report contains viewgraphs from the Special Parallel Processing Workshop. These viewgraphs deal with topics such as parallel processing performance, message passing, queue structure, and other basic concept detailing with parallel processing.

Cited by 0Open access

Scalable parallel seismic processing

Charles C. Mosher, Calvin L. Joyner, Siamak Hassanzadeh · The Leading Edge · 1996

Seismic methods, the primary tool in the search for oil and gas, are used to produce images of the earth’s subsurface that explorationists can analyze for geologic structures with hydrocarbon potential.

Cited by 4