Conferences related to Scientific computing

Back to Top

2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting

The joint meeting is intended to provide an international forum for the exchange of information on state of the art research in the area of antennas and propagation, electromagnetic engineering and radio science


2020 IEEE Power & Energy Society General Meeting (PESGM)

The Annual IEEE PES General Meeting will bring together over 2900 attendees for technical sessions, administrative sessions, super sessions, poster sessions, student programs, awards ceremonies, committee meetings, tutorials and more


GLOBECOM 2020 - 2020 IEEE Global Communications Conference

IEEE Global Communications Conference (GLOBECOM) is one of the IEEE Communications Society’s two flagship conferences dedicated to driving innovation in nearly every aspect of communications. Each year, more than 2,900 scientific researchers and their management submit proposals for program sessions to be held at the annual conference. After extensive peer review, the best of the proposals are selected for the conference program, which includes technical papers, tutorials, workshops and industry sessions designed specifically to advance technologies, systems and infrastructure that are continuing to reshape the world and provide all users with access to an unprecedented spectrum of high-speed, seamless and cost-effective global telecommunications services.


2019 Winter Simulation Conference (WSC)

WSC is the premier international forum for disseminating recent advances in the field of system simulation. In addition to a technical program of unsurpassed scope and quality, WSC provides the central meeting for practitioners, researchers, and vendors.


2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)

Cluster Computing, Grid Computing, Edge Computing, Cloud Computing, Parallel Computing, Distributed Computing


More Conferences

Periodicals related to Scientific computing

Back to Top

Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Communications Magazine, IEEE

IEEE Communications Magazine was the number three most-cited journal in telecommunications and the number eighteen cited journal in electrical and electronics engineering in 2004, according to the annual Journal Citation Report (2004 edition) published by the Institute for Scientific Information. Read more at http://www.ieee.org/products/citations.html. This magazine covers all areas of communications such as lightwave telecommunications, high-speed data communications, personal communications ...


Communications Surveys & Tutorials, IEEE

Each tutorial reviews currents communications topics in network management and computer and wireless communications. Available tutorials, which are 2.5 to 5 hours in length contains the original visuals and voice-over by the presenter. IEEE Communications Surveys & Tutorials features two distinct types of articles: original articles and reprints. The original articles are exclusively written for IEEE Communications Surveys & Tutorials ...


Computational Biology and Bioinformatics, IEEE/ACM Transactions on

Specific topics of interest include, but are not limited to, sequence analysis, comparison and alignment methods; motif, gene and signal recognition; molecular evolution; phylogenetics and phylogenomics; determination or prediction of the structure of RNA and Protein in two and three dimensions; DNA twisting and folding; gene expression and gene regulatory networks; deduction of metabolic pathways; micro-array design and analysis; proteomics; ...


Computer

Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed technical content that covers all aspects of computer science, computer engineering, technology, and applications. Computer is a resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in the profession.


More Periodicals

Most published Xplore authors for Scientific computing

Back to Top

Xplore Articles related to Scientific computing

Back to Top

Automated Capture of Experiment Context for Easier Reproducibility in Computational Research

Computing in Science & Engineering, 2012

Published scientific research that relies on numerical computations is too often not reproducible. For computational research to become consistently and reliably reproducible, the process must become easier to achieve, as part of day-to-day research. A combination of best practices and automated tools can make it easier to create reproducible research.


Simplified Pseudopotential Problems for the Classroom

Computing in Science & Engineering, 2015

Ab initio methods have been used for many decades to accurately predict properties of solids such as the physical, electronic, optical, magnetic, and elastic. A generation ago, many research groups developed their own in-house codes to perform ab initio calculations. In doing so, research students were intimately involved in many aspects of the coding, such as developing the theoretical framework, ...


Intel Makes A Big Jump In Computer Math

IEEE Spectrum, 2008

With Intel's new crop of 45-nanometer processors, code-named Penryn, the company is making the first substantial upgrade in its processors' divider since the original Pentium came out in 1993. The speedup doubles the number of bits calculated with each tick of the processor's clock and will make a substantial difference to financial and scientific computing. And because Intel powers so ...


Pythran: Crossing the Python Frontier

Computing in Science & Engineering, 2018

Use of the Python language in scientific computing has always been characterized by the coexistence of interpreted Python code and compiled native code, written in languages like C or Fortran. This column takes a fresh look at the problem and introduces Pythran, a new optimization tool designed to efficiently handle unmodified Python code.


The Start of the Software Products Industry

IEEE Annals of the History of Computing, 2002

None


More Xplore Articles

Educational Resources on Scientific computing

Back to Top

IEEE.tv Videos

Spiking Network Algorithms for Scientific Computing - William Severa: 2016 International Conference on Rebooting Computing
DOE-ASCR Activities Towards Rebooting Computing - Kelley Perry: 2016 International Conference on Rebooting Computing
Q&A: Government Roundtable - ICRC 2018
EDOC 2010 - Sylvain Halle - Best Paper Presentation
OJ-EMB: Dual format scientific and technical publishing - Paolo Bonato
Government Roundtable - ICRC 2018
Vladimir Cherkassky - Predictive Learning, Knowledge Discovery and Philosophy of Science
Brain Panelist - Jan Rabaey: 2016 Technology Time Machine
IROS TV 2019- Rutgers University- Center for Accelerated Real Time Analytics
My Ideas Were Challenged - Dr. Theodore Sizer - Why I Joined
Rebooting Computing: Parallelism in Computing
2011 IEEE Awards John von Neumann Medal - Tony Hoare
The Fundamentals of Compressive Sensing, Part I: Introduction
How to Write Papers for MTT
Rebooting Computing: Changing Computing
DOE Vision and Programmatic Activities in Advanced Computing Technologies: IEEE Rebooting Computing 2017
An Energy-efficient Reconfigurable Nanophotonic Computing Architecture Design: Optical Lookup Table - IEEE Rebooting Computing 2017
Energy Efficient Single Flux Quantum Based Neuromorphic Computing - IEEE Rebooting Computing 2017
A Unified Hardware/Software Co-Design Framework for Neuromorphic Computing Devices and Applications - IEEE Rebooting Computing 2017
Removing The Golden Handcuffs: Computing At The End of Moore's Scaling - IEEE Rebooting Computing Industry Summit 2017

IEEE-USA E-Books

  • Automated Capture of Experiment Context for Easier Reproducibility in Computational Research

    Published scientific research that relies on numerical computations is too often not reproducible. For computational research to become consistently and reliably reproducible, the process must become easier to achieve, as part of day-to-day research. A combination of best practices and automated tools can make it easier to create reproducible research.

  • Simplified Pseudopotential Problems for the Classroom

    Ab initio methods have been used for many decades to accurately predict properties of solids such as the physical, electronic, optical, magnetic, and elastic. A generation ago, many research groups developed their own in-house codes to perform ab initio calculations. In doing so, research students were intimately involved in many aspects of the coding, such as developing the theoretical framework, and algorithmic and programming details. Over time, however, collaborations between various research groups within academia and in industry have resulted in the creation of more than 50 large, open source, and commercial electronic structure packages. These software packages are widely used today for condensed matter research by students who, unfortunately, often have little understanding of the fundamental aspects of these codes. To address this shortcoming, a program at the University of Pretoria aims to devise a range of simplified, easily programmable computational problems appropriate for the classroom, which can be used to teach advanced undergraduate students about particular theoretical and computational aspects of the electronic structure method. This article focuses on the pseudopotential, which is a centrally important concept in many modern ab initio methods. Whereas the full implementation of the pseudopotential construct in a real electronic structure code requires complex numerical methods--for example, accelerated convergence to self-consistency including the interactions between all the electrons in the system--the essential principles of the pseudopotential can, nevertheless, be presented in a simpler class of problems, which students can readily code.

  • Intel Makes A Big Jump In Computer Math

    With Intel's new crop of 45-nanometer processors, code-named Penryn, the company is making the first substantial upgrade in its processors' divider since the original Pentium came out in 1993. The speedup doubles the number of bits calculated with each tick of the processor's clock and will make a substantial difference to financial and scientific computing. And because Intel powers so much of the computer market, the development could tempt programmers to retreat from the less accurate but faster software tricks they've used as a substitute for division.

  • Pythran: Crossing the Python Frontier

    Use of the Python language in scientific computing has always been characterized by the coexistence of interpreted Python code and compiled native code, written in languages like C or Fortran. This column takes a fresh look at the problem and introduces Pythran, a new optimization tool designed to efficiently handle unmodified Python code.

  • The Start of the Software Products Industry

    None

  • Solving graph partitioning problem using genetic algorithms

    The graph partitioning problem (GPP) is one of the fundamental multimodal, combinatorial problems that has many applications in computer science. Many deterministic algorithms have been devised to obtain a good solution for the GPP. This paper presents new techniques for discovering more than one solution to this problem using genetic algorithms. The techniques used are based upon applying niching methods to obtain multiple good solutions instead of only one solution. The paper also presents in detail a comparison between the results of a traditional method, simple genetic algorithm (SGA), and two niching methods, fitness sharing and deterministic crowding when applied to the graph partitioning problem.

  • A transformation approach to derive efficient parallel implementations

    The construction of efficient parallel programs usually requires expert knowledge in the application area and a deep insight into the architecture of a specific parallel machine. Often, the resulting performance is not portable, i.e., a program that is efficient on one machine is not necessarily efficient on another machine with a different architecture. Transformation systems provide a more flexible solution. They start with a specification of the application problem and allow the generation of efficient programs for different parallel machines. The programmer has to give an exact specification of the algorithm expressing the inherent degree of parallelism and is released from the low-level details of the architecture. We propose such a transformation system with an emphasis on the exploitation of the data parallelism combined with a hierarchically organized structure of task parallelism. Starting with a specification of the maximum degree of task and data parallelism, the transformations generate a specification of a parallel program for a specific parallel machine. The transformations are based on a cost model and are applied in a predefined order, fixing the most important design decisions like the scheduling of independent multitask activations, data distributions, pipelining of tasks, and assignment of processors to task activations. We demonstrate the usefulness of the approach with examples from scientific computing.

  • Heterogeneous Hardware and Software for Remote Monitoring and Control

    We have developed an application where different technology platforms (hardware and software) are used taking into account specific functional requirements. We take advantage of current state of the art technologies, some of which being currently used in different applications areas. We present a specific real system and, also, the way in which we use a number of devices (sensors, actuators, IP camera) via standard interfaces and protocols. Simple, out-of-the-box devices are combined with some application specific (e. g. embedded) hardware and/or software in order to solve a monitoring and control application. Furthermore, the system is interoperable and extensible, being a proof of concept on how current technologies (with different goals and origins) can be successfully combined.

  • WIP: Generating Sequence Diagrams for Modern Fortran

    Fortran finds widespread use in scientific and engineering communities that embraced computing early, including weather and climate science and mechanical, nuclear, and aerospace engineering. Over its lifetime, Fortran has evolved to support multiple programming paradigms, including Object-Oriented Programming (OOP). Despite the recently burgeoning ecosystem of tools and libraries supporting modern Fortran, there remains limited support for generating common Object-Oriented Design (OOD) diagrams from Fortran source code. ForUML partially fills this need by reverse engineering Unified Modeling Language (UML) class diagrams from object-oriented (OO) Fortran programs. Class diagrams provide useful information about class structures and inter- relationships, but class diagrams do not convey the temporal information required to understand runtime class behavior and interactions. UML sequence diagrams provide such important algorithmic details. This paper proposes to extend ForUML to extract UML sequence diagrams from Fortran code and to offer this capability via a widely used open-source platform. The paper argues that the proposed capability can raise the level of abstraction at which the computational science community discusses modern Fortran.

  • Praxis of Reproducible Computational Science

    Among the top challenges of reproducible computational science are the following: 1) creation, curation, usage, and publication of research software; 2) acceptance, adoption, and standardization of open-science practices; and 3) misalignment with academic incentive structures and institutional processes for career progression. I will mainly address the first two here, proposing a praxis of reproducible computational science.



Standards related to Scientific computing

Back to Top

No standards are currently tagged "Scientific computing"


Jobs related to Scientific computing

Back to Top