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Tools for Scientific Computation

ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 1993
Scientific Computation (short: SC) denotes the use of computers for the modelling and simulation of complex scientific and technological processes. Its goal is to perform specified computer simulation related tasks more reliably, quickly and cheaply, and more conveniently for the user.
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Computers in Scientific Instrumentation

Science, 1982
The rapid evolution of computer applications in scientific instrumentation is briefly traced from early data processing to modern computer-based instruments. Computer and interface developments have both contributed to this evolution. The form of the computer used strongly affects the ease of instrument operation and the degree of functional ...
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Scientific Computing with MATLAB

2003
This textbook is an introduction to Scientific Computing, in which several numerical methods for the computer solution of certain classes of mathematical problems are illustrated. The authors show how to compute the zeros or the integrals of continuous functions, solve linear systems, approximate functions by polynomials and construct accurate ...
QUARTERONI, ALFIO MARIA   +1 more
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Scientific Computing

Computing Skills for Biologists, 2015
Timo Heister, Leo G. Rebholz
semanticscholar   +3 more sources

Scientific Grid computing

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2005
We introduce a definition of Grid computing which is adhered to throughout this Theme Issue. We compare the evolution of the World Wide Web with current aspirations for Grid computing and indicate areas that need further research and development before a generally usable Grid infrastructure becomes available. We discuss work that has been done in order
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Scientific Computing with GPUs

Computing in Science & Engineering, 2012
This special issue attests to the widespread use of GPUs in the scientific computing community. Here the guest editor discusses the articles selected for this issue, and considers how they represent the range of possibilities (and risks) for using GPUs in scientific applications.
openaire   +1 more source

Enabling Scientific Computing on Memristive Accelerators

International Symposium on Computer Architecture, 2018
Linear algebra is ubiquitous across virtually every field of science and engineering, from climate modeling to macroeconomics. This ubiquity makes linear algebra a prime candidate for hardware acceleration, which can improve both the run time and the ...
Ben Feinberg   +4 more
semanticscholar   +1 more source

Quantum Algorithms for Scientific Computing and Approximate Optimization

, 2018
Quantum computation appears to offer significant advantages over classical computation and this has generated a tremendous interest in the field. In this thesis we consider the application of quantum computers to scientific computing and combinatorial ...
Stuart Hadfield
semanticscholar   +1 more source

Integrating quantum computing resources into scientific HPC ecosystems

Future generations computer systems
Quantum Computing (QC) offers significant potential to enhance scientific discovery in fields such as quantum chemistry, optimization, and artificial intelligence.
Thomas Beck   +17 more
semanticscholar   +1 more source

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