
	Where results make sense

Topic: Scientific computing

Related Topics

Computational physics

Numerical stability

List of numerical analysis topics

Condition number

Propagation of errors resulting from algebraic manipulations

Elementary matrix transformations

In the News (Sat 5 Dec 09)

Northern Trust

Marvin Harrison

Peter Chernin

Gary Locke

Match Play

Penelope Cruz

Mickey Rourke

AR Rahman

Danny Boyle

Hugh Jackman

	Scientific computing - Wikipedia, the free encyclopedia
		Scientific computing (or computational science) is the field of study concerned with constructing mathematical models and numerical solution techniques and using computers to analyze and solve scientific and engineering problems.
		The scientific computing approach is to gain understanding, mainly through the analysis of mathematical models implemented on computers.
		Scientific computation is most often studied through an applied mathematics or computer science program, or within a standard mathematics, sciences, or engineering program.
	en.wikipedia.org /wiki/Scientific_computing (525 words)

	Deep scientific computing requires deep data
		High-performance computing is now being integrated directly into some experiments, analyzing data while the experiment is in progress, to allow real-time adaptation and refinement of the experiment and to allow the insertion of human intuition into the process, thus making it very dynamic.
		Computational steering requires that a control channel to the executing service be open, that the execution process be interruptible, and that a new or modified plan can be submitted.
		However, in many of the scientific cases listed in the introduction, the data is not at the same location as the computing servers, or the results have to be moved to a different location.
	www.research.ibm.com /journal/rd/482/kramer.html (14874 words)

	Department of Mathematics
		Scientific Computing is the area of research that provides better simulation tools aimed at many different applications.
		Scientific Computing also tries to provide tools for handling the current data explosion caused by the output of numerous experimental devices, such as sensors, sequencing machines, and many more.
		The aim of the Master's programme in Scientific Computing is to produce experts on numerical simulation who can work in multidisciplinary teams, can communicate with colleagues from different application areas, and who can identify common features in computations from very different applications.
	www.math.uu.nl /Masters/SC (336 words)

	[No title]
		In general, for a language to qualify as a platform for producing scientific computational code, it must provide a rich set of tools that can be used for measuring performance and must allow developers to express the problem domain easily and effectively, among other criteria.
		Complex numbers are widely used in scientific applications for studying physical phenomena, such as electrical current, wavelengths, and liquid flow in relation to obstacles, analysis of stress on beams, movement of shock absorbers in cars, the design of dynamos and electric motors, and the manipulation of large matrices used in modeling.
		However, this should not affect scientific programmers who intend to run code in a fully trusted environment, unless the intention is to write a network application or one used by the general public.
	msdn.microsoft.com /msdnmag/issues/04/03/ScientificC (6587 words)

	Scientific Computing (LaSC)
		The Scientific Computing master's is not recommended for students who lack extensive experience or a conventional master's degree; such students will emerge with a master's level knowledge of computing methodology but only a bachelor's level grasp of engineering.
		The purpose of the Master of Science in Scientific Computing is to offer such engineers a chance to return to school for a year to acquire the necessary skills in scientific computing.
		The goal of the related doctoral program in Scientific Computing is to teach mastery of both a particular branch of engineering or applied science, as represented by the student's "home" department, as well as the interdisciplinary skills of numerical computation.
	www.umich.edu /~bhlumrec/acad_unit/rackham/degree_req/www.rackham.umich.edu/Programs/physical.sci/scicomputing.html (1602 words)

	Master of Science - Nada, KTH
		In Scientific Computing numerical methods are designed, analysed and applied for the purpose of insight in and solution of mathematical models.
		The scientific course program gives profound knowledge in Scientific Computing for large industrial processes and comprises a number of areas: Numerical methods, matematical modeling, object oriented program construction, algorithms for parallel programming and applications in fluid dynamics, electro-magnetics, financial mathematics, computational physics and chemistry.
		PDC the Center for Parallel Computers, and PSCI,Parallel and Scientific Computing Institute are both subdivisions of Nada located in the same building.
	www.nada.kth.se /kurser/master/index-eng.html (760 words)

	Scientific Computing Laboratory
		Scientific computing has become a tool as vital as experimentation and theory for dealing with scientific challenges of the twenty-first century.
		The Scientific Computing Laboratory (SCL) at the Institute of Physics in Belgrade has as its aim to be on the forefront of the development of scientific computing as a novel research tool.
		Scientific computing has been nurtured in physics, in particular in fields such as high energy physics, condensed matter physics, cosmology and astrophysics.
	scl.phy.bg.ac.yu (279 words)

	The Masters Degree Program in Scientific Computing
		The program, which began in the fall 1995 semester, is designed to provide a broad yet rigorous training in areas related to scientific computing, including modern computing tools and methods, and numerical and mathematical analysis as arises in various applications.
		Scientific computing is an indispensable part of almost all scientific investigation and technological development at universities, government laboratories, and within the private sector.
		The two elective courses may be taken in mathematics or computer science, and are subject to approval by the student's faculty advisor or the Director of the Program.
	www.math.nyu.edu /degree/scicomp.html (1698 words)

	Latest Scientific Computing Tools
		During the week-long conference of the nation's leaders in computing and networking, members of Berkeley Lab's Computing Sciences organization will be presenting leading-edge computer simulations, demonstrating the latest tools for enhancing scientific research, and sharing their expertise with hundreds of other attendees by leading tutorial sessions.
		The Laboratory is home to the National Energy Research Scientific Computing Center (NERSC), which serves researchers at national labs, universities and industry, and the Information and Computing Sciences Division, which conducts computing and networking research.
		Although fluid flow and resulting turbulence are central to many scientific and engineering problems, such as building more efficient and less polluting internal combustion engines, it's a field that is difficult to understand and even harder to accurately simulate using a computer.
	www.lbl.gov /Computing-Sciences/Archive/othernews11-5-98.html (1043 words)

	Indiana University Scientific Computing Program (Site not responding. Last check: 2007-09-07)
		The increasing availability of high performance computers has led to a method of scientific inquiry based on mathematical models solved by means of numerical computations, analyzed and viewed by means of advanced computer graphics.
		Scientific computing courses are generally organized into four categories: numerical analysis, scientific applications, scientific visualization, and high performance computing.
		Students wanting to minor in Scientific Computing should initially meet with an advisor in their home department, and then contact a member of the Graduate Committee on Scientific Computing.
	www.indiana.edu /~scicomp/minor.html (542 words)

	Scientific & Parallel Computing
		From x-ray crystallography to the design of the Boeing 777, today's scientific and technological advances would be impossible without the combination of powerful computers and powerful algorithms running on those computers.
		The scientific computing group at Cornell develops the algorithms that underlie simulation and optimization.
		This core faculty group in scientific computing is also active in the Applied Mathematics Ph.D. program, which is part of Cornell's Center for Applied Mathematics.
	www.cs.cornell.edu /Research/scientif/index.htm (491 words)

	Scientific Computing (SCI) \| EECS at UC Berkeley (Site not responding. Last check: 2007-09-07)
		Scientific users, from plasma physicists to earthquake engineers, depend on numerical simulations to explore physical phenomena that may not be accessible to experimental verification.
		Berkeley is ideally situated amongst a wealth of resources for scientific computing, including Lawrence Berkeley National Laboratory (LBNL), the National Energy Research Scientific Computing Center (NERSC, located at LBNL), the Lawrence Livermore National Laboratory, and NPACI, an NSF-funded supercomputer center.
		Other important computational resources are Berkeley's own campus-wide Millenium project, built upon a cluster of clusters of tightly-coupled Pentium-based computers.
	www.eecs.berkeley.edu /Research/Areas/CS/SCI (130 words)

	Scientific Computing
		Scientific Computing is the use of computers to solve problems from Science and Engineering such as Weather Forecast, Satellite Imaging, Wind Energy, Medical Imaging, among others.
		The problems are very challenging and their solution requires sophisticated methods or Numerical Algorithms and the use of state-of-the-art computers, so-called High-Performance Computers.
		Our group's expertise and interests include most of the aspects of Scientific Computing: from modelling the physical phenomenon, designing, analysing, and implementing the solution methods to applying the methods to the solution of real problems.
	www.imm.dtu.dk /English/Research/Scientific_Computing.aspx (84 words)

	Scientific Computing (Site not responding. Last check: 2007-09-07)
		The Master’s programme in Scientific Computing is given by the CSC School (Computer Sciences and Communication) at KTH, Stockholm, Sweden.
		Scientific computing is a multidisciplinary subject created by the need for making computer simulations in science and engineering.
		A great deal of time is spent on training in computer labs where excersises and projects are prepared using modern, high-performance computer tools for programming, simulation and visulization.
	www.kth.se /eng/education/programmes/master_english/scientific_computing.html (448 words)

	Developing Scientific Applications Using Eclipse
		The mission of Computing in Science and Engineering is to support the development of computing tools and methods as well as their effective use in both computational and experimental science and engineering.
		Although parallel computers provide significant performance improvements over conventional systems, there is little commonality in the way users interact with and run applications on these machines.
		He is a member of the IEEE Computer Society, past president of the Internet Society of Australia, and former chair of the Domain administration.
	www.computer.org /portal/site/cise/menuitem.92a12adebee18778161489108bcd45f3/index.jsp?&pName=cise_level1_article&TheCat=1001&path=cise/2006/v8n4&file=sci.xml& (5236 words)

	Computing and Computational Sciences
		Oak Ridge National Laboratory's Computing and Computational Sciences Directorate conducts state-of-the-art research and development in computer and computational sciences in support of DOE's missions and programs.
		We develop and deploy leading edge computing and information technology capabilities to keep computational sciences at a level comparable to experimental sciences in the pursuit of scientific discovery and technical innovation.
		Many new scientific and technical staff are needed now in specific initiatives or strategic research areas in the Computing and Computational Sciences Directorate.
	computing.ornl.gov (282 words)

	Idaho National Laboratory - Advanced Computing & Collaboration
		The Advanced Scientific Computing and Collaboration Initiative has been established to enable the INL to develop and apply the revolutionary computing tools needed to perform leading-edge scientific research, engineering, and operations to address critical national needs.
		The Advanced Scientific Computing and Collaboration Initiative is a concerted effort to develop the next-generation computing infrastructure and capabilities at the INL.
		In order to form an integrated solution for advanced computing, the Advanced Scientific Computing and Collaboration Initiative will work with all other INL initiatives to systematically identify the scientific challenges faced, and the resulting computing requirements and strategies needed to coordinate investments from a laboratory-wide standpoint.
	www.inl.gov /computing (642 words)

	Scientific Programming
		Scientific Programming provides a meeting ground for research in and practical experience with software engineering environments, tools, languages, and models of computation aimed specifically at supporting scientific and engineering computing.
		Scientific Programming welcomes papers on language, compiler, and support environment issues for these and other languages used for scientific computing.
		Scientific Programming is a reporting forum for research and practical experience within software engineering environments, tools, languages and models of computation, aimed specifically at supporting scientific and engineering programming.
	www.wiley.com /legacy/compbooks/compjournals/sciprog.html (565 words)

	The Scientific Computing Group
		The SCG is a place where cross-cutting trends in computational sciences and scientific computing meet, fertilize and materialize.
		The SCG ultimate goal is to advance scientific computing by developing and enhancing applications in key disciplines, as well as developing tools and libraries for addressing general problems in computational science.
		Therefore, with our diverse scientific background and complementary research skills, we strive to excel in computational science, enabling and accelerating new scientific discoveries, and providing an intellectually stimulating and educational environment that attracts both researchers and graduate students from the best institutions in the world.
	hpcrd.lbl.gov /SCG (220 words)

	Scientific Computing with Python
		In this paper, I describe the process of adding a scripting language to a scientific computing project by focusing on the use of Python with a large-scale molecular dynamics code developed for materials science research at Los Alamos National Laboratory.
		As a developer of scientific software, one of the biggest obstacles is the problem of how to make scientific software flexible, easy to use, simple to maintain, and easy to adapt to the increased size and complexity of new problems.
		Object-oriented programming techniques are becoming increasingly common in scientific projects because they provide programming abstractions that make it easier for developers to think about organization of data and the manner in which different subsystems interface with each other.
	www.adass.org /adass/proceedings/adass99/O3-02 (4291 words)

	Scientific Computing course home page
		This is a one semester graduate course covering the basics of practical scientific computing for mathematicians, computer scientists, physical scientists, and finance.
		The prerequisites are linear algebra, multivariate calculus, some computer literacy, and (for the Monte Carlo part) some exposure to elementary probability theory.
		For the scientific computing software we build in this class, the distinction between C and C++ is monor.
	www.math.nyu.edu /faculty/goodman/teaching/SciComp2006 (703 words)

	Amazon.com: Scientific Computing: Books: Michael T Heath,Michael Heath (Site not responding. Last check: 2007-09-07)
		Heath 2/e, presents a broad overview of numerical methods for solving all the major problems in scientific computing, including linear and nonlinear equations, least squares, eigenvalues, optimization, interpolation, integration, ordinary and partial differential equations, fast Fourier transforms, and random number generators.
		If you are interested in Scientific computing from the viewpoint of the end user that is the guy who uses the method to solve practical engineering problems then this book is lacking.
		He does talk about interesting issues such as conditioning and error analysis and computer precision and memory issues but it is done from such a superficial viewpoint that one cannot use anything to improve ones code.
	www.amazon.com /Scientific-Computing-Michael-T-Heath/dp/0072399104 (1800 words)

	Scientific Computing
		Sandia's computational sciences program creates technologies for all of Sandia's strategic business units.
		The program develops numerical methods for solving scientific and engineering problems, a software infrastructure for parallel computing, and techniques for distributed computing.
		Computational technologies are playing an important role in a wide range of Sandia programs.
	www.sandia.gov /eesector/bessc.html (248 words)

	P573: Introduction to Scientific Computing (Site not responding. Last check: 2007-09-07)
		Matrix Computations by Golub and van Loan is a more definitive but higher-level reference work, with numerical linear algebra algorithms clearly stated in an implementable form.
		Open to students from all scientific, engineering, and mathematical disciplines, this course provides an overview of computer hardware, software, and numerical methods that are useful on scientific workstations and supercomputers.
		Although numerical analysis is an important component of scientific computing, it is only a part of the field.
	www.cs.indiana.edu /classes/p573 (1238 words)

	Solutions for Scientific Computing in Engineering and Science
		Ch is an ideal computing environment for engineers and scientists to solve their challenging problems productively.
		Ch is the only computing environment in existence that can perform numerical computing with consistent numerical results under the IEEE floating-point arithmetic in the entire real domain and complex domain using an extended complex plane for a Riemman sphere.
		Computational arrays allow matrices to be manipulated as first-class objects so that mathematical formulas such as linear equation b = A*x can be written verbatim in Ch.
	www.softintegration.com /solution/engineering (562 words)

Try your search on: Qwika (all wikis)