By Topic

Computational Science & Engineering, IEEE

Issue 2 • Date Summer 1994

Filter Results

Displaying Results 1 - 6 of 6
  • Imaging the universe at radio wavelengths

    Publication Year: 1994 , Page(s): 39 - 49
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1451 KB)  

    Computerized image processing is crucial for the large arrays of radio telescopes that are advancing astronomy. A new project will help relieve the computational bottleneck that hinders this field. The National Science Foundation (NSF) has funded a 5-year Grand Challenge High-Performance Computing and Communications project to (a) allow astronomers to use upgraded NSF supercomputers; (b) develop network links to widely-used observatories; and (c) develop digital data archives over national high-speed networks. We plan to prototype the next generation of astronomical telescope systems. These will be remotely located telescopes connected by high-speed networks to very high performance, scalable-architecture computers and online data archives. Astronomers will access these systems via gigabit-per-second networks, and use advanced visualization tools to comprehend and analyze the very large multidimensional images being generated.<> View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Searching in parallel for similar strings [biological sequences]

    Publication Year: 1994 , Page(s): 60 - 75
    Cited by:  Papers (6)  |  Patents (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2455 KB)  

    Distributed computation, probabilistic indexing and hashing techniques combine to create a novel approach to processing very large biological-sequence databases. Other data-intensive tasks could also benefit. Our indexing-based approach enables fast similarity searching through a large database of strings. Thanks to a redundant table-lookup scheme, recovering database items that match a test sequence requires minimal data access. We have implemented a uniprocessor version of this approach called Flash (Fast Lookup Algorithm for String Homology) as well as a distributed version, dFlash, using a cluster of seven non-dedicated workstations connected through a local area network. In this article, we present an approach for retrieving homologies in databases of proteins.<> View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Computational methods in transient electromagnetics. A selective survey

    Publication Year: 1994 , Page(s): 50 - 59
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (845 KB)  

    We can now solve real-life problems in electromagnetics at all levels of complexity. Several popular algorithms are available to deal with the transient-scattering problem. They all solve either differential or integral equations in one form or another. No one method is best in all situations. Since only differential or integral equations are involved in the final solution, the methods described in this paper should be of considerable interest to other areas of science as well. Each of the methods available for predicting transient behaviors and responses has certain advantages and disadvantages, so an approach must be chosen carefully, depending on the problem complexity.<> View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Parallel analysis of clusters in landscape ecology

    Publication Year: 1994 , Page(s): 24 - 38
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1761 KB)  

    When ecosystems are fragmented into patches, the whole can be worth less than the sum of its parts. Parallel methods can greatly speed up statistical analysis of clusters, in landscape ecology or other fields. The term 'landscape ecology' refers to the analysis of patterns and heterogeneity in natural landscapes and ecosystems. Computer modeling is used in landscape ecology applications to assess habitat fragmentation and its implications. Researchers in the Environmental Sciences Division at Oak Ridge National Laboratory developed a model called Noyelp that simulates the search, movement, and foraging activities of free-ranging elk and bison on winter range in northern Yellowstone National Park. The model helps to explore how the scale and patterns of fire affect winter foraging and survival of ungulate populations in the diverse, multihabitat landscape of the park. This model, written in Fortran-77, analyzes maps (2D grids) to determine the number, size, and geometry of habitat regions, or clusters, representing landscape patterns, resources, and animals.<> View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Computer as thinker/doer: problem-solving environments for computational science

    Publication Year: 1994 , Page(s): 11 - 23
    Cited by:  Papers (46)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2054 KB)  

    During the early 1960s, scientists began to envision problem-solving computing environments not only powerful enough to solve complex problems but also able to interact with users on human terms. While many tried to create PSEs over the next few years, by the early 1970s they had abandoned almost all of these attempts. Technology could not yet support PSEs in computational science. But the dream of the 1960s can be the reality of the 1990s: high-performance computers combined with better understanding of computing and computational science have put PSEs well within our reach. The term 'problem-solving environment' means different things to different people. A PSE is a computer system that provides all the computational facilities necessary to solve a target class of problems. These features include advanced solution methods, automatic or semi-automatic selection of solution methods, and ways to easily incorporate novel solution methods. Simple PSEs appeared early in computing without being recognized as such. Some of the capabilities of future problem-solving environments seem like science fiction, but whatever form they eventually take, their scientific and economic impact will be enormous.<> View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • The Army High Performance Computing Research Center

    Publication Year: 1994 , Page(s): 6 - 8
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (325 KB)  

    The US Army High Performance Computing Research Center (AHPCRC) provides nationwide leadership in high performance computing (HPC) research. Its supercomputing resources are maintained and operated by the Minnesota Supercomputer Center, Inc. AHPCRC researchers are developing novel techniques and advanced algorithms and applying them to physical problems, as well as evaluating and using advanced computing platforms for HPC applications. The Center trains future scientists and engineers by sponsoring computer science educational research at the undergraduate, MS, PhD, and postdoctoral levels. It provides a framework for HPC technology transfer and infrastructure support to Army laboratories by conducting joint research projects between Army scientists and Center researchers; by jointly supervising the staff scientists placed by the Center at the Army laboratories; and by encouraging visits between Army scientists and Center researchers. Finally, the AHPCRC provides a state-of-the-art HPC environment to its academic partners, to Army and Defense Department scientists, and to industrial and international collaborators.<> View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

Aims & Scope

This Periodical ceased publication in 1998. The current retitled publication is IEEE Computing in Science and Engineering.

Full Aims & Scope