This document discusses supercomputing, including its applications across multiple domains like bioinformatics, computational materials science, and computational fluid dynamics. It notes that supercomputers can solve problems too small, large, fast, or slow for normal laboratories. The document also outlines some current challenges for supercomputing, such as developing new architectures for next generation supercomputers and processing large datasets to extract useful information.
4 Ways Artificial Intelligence Can Help Save the PlanetTyrone Systems
As the scale and urgency of the economic and human health impacts from our deteriorating natural environment grows, we have an opportunity to look at how AI can help transform traditional sectors and systems to address climate change, deliver food and water security, build sustainable cities, and protect biodiversity and human wellbeing.
Text mining analysis of wind turbine accidents: An ontology-based frameworkGurdal Ertek
As the global energy demand is increasing, the share of renewable energy and specifically wind energy in the supply is growing. While vast literature exists on the design and operation of wind turbines, there exists a gap in the literature with regards to the investigation and analysis of wind turbine accidents. This paper describes the application of text mining and machine learning techniques for discovering actionable insights and knowledge from news articles on wind turbine accidents. The applied analysis methods are text processing, clustering, and multidimensional scaling (MDS). These methods have been combined under a single analysis framework, and new insights have been discovered for the domain. The results of our research can be used by wind turbine manufacturers, engineering companies, insurance companies, and government institutions to address problem areas and enhance systems and processes throughout the wind energy value chain.
http://ieeexplore.ieee.org/document/8258305/
http://ertekprojects.com/gurdal-ertek-publications/
These slides use concepts from my (Jeff Funk) course entitled analyzing hi-tech opportunities to show how in improvements in printed electronics, wireless telecom, and the Internet are enabling the greater use of smart logistics. Logistics now represents 10% of global GDP thus representing a large percentage of expenditures. Improvements in printed electronics enables cheaper and better RFID tags and smart packaging; the latter can be accessed by logistic companies and consumers. All of this enables better monitoring of products throughout their journey to the marketplace, on ships, in warehouses, and in retail outlets. It also enables customers to more easily find products in retail outlets and for robots to find products in warehouses.
4 Ways Artificial Intelligence Can Help Save the PlanetTyrone Systems
As the scale and urgency of the economic and human health impacts from our deteriorating natural environment grows, we have an opportunity to look at how AI can help transform traditional sectors and systems to address climate change, deliver food and water security, build sustainable cities, and protect biodiversity and human wellbeing.
Text mining analysis of wind turbine accidents: An ontology-based frameworkGurdal Ertek
As the global energy demand is increasing, the share of renewable energy and specifically wind energy in the supply is growing. While vast literature exists on the design and operation of wind turbines, there exists a gap in the literature with regards to the investigation and analysis of wind turbine accidents. This paper describes the application of text mining and machine learning techniques for discovering actionable insights and knowledge from news articles on wind turbine accidents. The applied analysis methods are text processing, clustering, and multidimensional scaling (MDS). These methods have been combined under a single analysis framework, and new insights have been discovered for the domain. The results of our research can be used by wind turbine manufacturers, engineering companies, insurance companies, and government institutions to address problem areas and enhance systems and processes throughout the wind energy value chain.
http://ieeexplore.ieee.org/document/8258305/
http://ertekprojects.com/gurdal-ertek-publications/
These slides use concepts from my (Jeff Funk) course entitled analyzing hi-tech opportunities to show how in improvements in printed electronics, wireless telecom, and the Internet are enabling the greater use of smart logistics. Logistics now represents 10% of global GDP thus representing a large percentage of expenditures. Improvements in printed electronics enables cheaper and better RFID tags and smart packaging; the latter can be accessed by logistic companies and consumers. All of this enables better monitoring of products throughout their journey to the marketplace, on ships, in warehouses, and in retail outlets. It also enables customers to more easily find products in retail outlets and for robots to find products in warehouses.
BOGATE´S® – это торговая марка эффектных светильников для дома, в дизайне которых искусно соединились классика и новации. Отличительные особенности коллекции: индивидуальный дизайн и ручная работа, богатство декоративных элементов и утонченность стиля, глубинное сияние высококачественного хрусталя Strotskis®, красота природных материалов и современные технологии. Сегодня приобрести светильники под торговой маркой BOGATE´S® можно в салоне-иагазине "Delight", неизменно гарантирующий выгодные цены, высокое качество продукции и отличный сервис
Big data Mining Using Very-Large-Scale Data Processing PlatformsIJERA Editor
Big Data consists of large-volume, complex, growing data sets with multiple, heterogenous sources. With the
tremendous development of networking, data storage, and the data collection capacity, Big Data are now rapidly
expanding in all science and engineering domains, including physical, biological and biomedical sciences. The
MapReduce programming mode which has parallel processing ability to analyze the large-scale network.
MapReduce is a programming model that allows easy development of scalable parallel applications to process
big data on large clusters of commodity machines. Google’s MapReduce or its open-source equivalent Hadoop
is a powerful tool for building such applications.
The ever increasing demand of computing power has led to the development of extremely large systems that consist of millions of components. Sustainable large scale computing systems can extend themselves to extreme scales. Both extreme and exascale computing defy the common wisdom of HPC and are regarded as unorthodox, but they could turn out to be indispensable necessities in the near future 1 . This paper provides a primer on extreme computing. Matthew N. O. Sadiku | Adedamola A. Omotoso | Sarhan M. Musa ""Extreme Computing: A Primer"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd21723.pdf
Paper URL: https://www.ijtsrd.com/computer-science/other/21723/extreme-computing-a-primer/matthew-n-o-sadiku
Technical inovation in mechanical fieldKrishna Raj
ALL THE EXAMPLES OF RECENT INVENTION IN MECHANICAL FIELD .
BETTER DISCRIPTION WITH EXAMPLES AND THEIR IMAGES.
BEST EVER PPT OF TECHNICAL INOVATION IN MECHANICAL FIELD TOPIC.
U CAN EXPLORE IT
I am Tapas Kumar Palei. I am studying B.Tech CSE in Ajay Binay Institute Of Technology. Grid computing is my seminar presentation topic. I try to gather everything about the grid computing in this seminar presentation.
BOGATE´S® – это торговая марка эффектных светильников для дома, в дизайне которых искусно соединились классика и новации. Отличительные особенности коллекции: индивидуальный дизайн и ручная работа, богатство декоративных элементов и утонченность стиля, глубинное сияние высококачественного хрусталя Strotskis®, красота природных материалов и современные технологии. Сегодня приобрести светильники под торговой маркой BOGATE´S® можно в салоне-иагазине "Delight", неизменно гарантирующий выгодные цены, высокое качество продукции и отличный сервис
Big data Mining Using Very-Large-Scale Data Processing PlatformsIJERA Editor
Big Data consists of large-volume, complex, growing data sets with multiple, heterogenous sources. With the
tremendous development of networking, data storage, and the data collection capacity, Big Data are now rapidly
expanding in all science and engineering domains, including physical, biological and biomedical sciences. The
MapReduce programming mode which has parallel processing ability to analyze the large-scale network.
MapReduce is a programming model that allows easy development of scalable parallel applications to process
big data on large clusters of commodity machines. Google’s MapReduce or its open-source equivalent Hadoop
is a powerful tool for building such applications.
The ever increasing demand of computing power has led to the development of extremely large systems that consist of millions of components. Sustainable large scale computing systems can extend themselves to extreme scales. Both extreme and exascale computing defy the common wisdom of HPC and are regarded as unorthodox, but they could turn out to be indispensable necessities in the near future 1 . This paper provides a primer on extreme computing. Matthew N. O. Sadiku | Adedamola A. Omotoso | Sarhan M. Musa ""Extreme Computing: A Primer"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd21723.pdf
Paper URL: https://www.ijtsrd.com/computer-science/other/21723/extreme-computing-a-primer/matthew-n-o-sadiku
Technical inovation in mechanical fieldKrishna Raj
ALL THE EXAMPLES OF RECENT INVENTION IN MECHANICAL FIELD .
BETTER DISCRIPTION WITH EXAMPLES AND THEIR IMAGES.
BEST EVER PPT OF TECHNICAL INOVATION IN MECHANICAL FIELD TOPIC.
U CAN EXPLORE IT
I am Tapas Kumar Palei. I am studying B.Tech CSE in Ajay Binay Institute Of Technology. Grid computing is my seminar presentation topic. I try to gather everything about the grid computing in this seminar presentation.
These slides were presented in a session that we organized at the American Association for Advancement of Science (AAAS) meeting in Chicago, February 2009.
Abstract: New laboratory devices, sensor networks, high-throughput instruments, and numerical simulation systems are producing data at rates that are both without precedent and rapidly growing. The resulting increases in the size, number, and variety of data are revolutionizing scientific practice. These changes demand new computing infrastructures and tools. Until recently, most laboratories and collaborations managed their own data, operated their own computers, and used remote high-performance computers only when required. We are moving to a paradigm in which data will primarily be located and managed on remote clusters, grids, and data centers. In this symposium, we will examine the computing infrastructure designed to serve this emerging era of data-intensive computing from three perspectives: (1) that of grid computing, which enables the creation of virtual organizations that can share remote and distributed resources over the Internet; (2) that of data centers, which are transitioning to providers of integrated storage, data, compute, and collaboration services (the offering of one or more of these integrated services over the Internet is beginning to be called cloud computing); and (3) that of e-science, in which grids, Web 2.0 technologies, and new collaboration and analysis services are merging and changing the way science is conducted. Each speaker will focus on one perspective but also compare and contrast with the others.
An article exploring the parallels between human existence and resilience in data centres. Appearing in the Winter 2016 Edition of Data Centre Management Magazine.
Learning from Machine Intelligence: The Next Wave of Digital TransformationOrange Silicon Valley
This report from Orange Silicon Valley looks at the growing importance of machine learning and artificial intelligence as it relates to the changing digital landscape. Highlights include software's evolution in being used to apply context and probability in autonomous decision-making efforts, the growing use by machine intelligence in Big Data, and how enterprises are experimenting with the technology to enhance their value chain and scale at incredible speed.
Similar to applications-and-current-challenges-of-supercomputing-across-multiple-domains-of-computational-sciences (20)
2. 57
Applications and Current Challenges of Supercomputing across Multiple Domains
room.Thespeedofsupercomputersaremeasured
in FLOPS (Chinta, 2013). Simply put, Floating
pointoperationsmeanscomputationsthatinvolve
very large decimal numbers, usually 300 digits in
a single number. The ten fastest supercomputers
in the world are Titan, Sequoia, K Computer,
Mira, JUQueen, SuperMuc, Stampede, Tianhe-
1A, Fermi, Darpa Trial Subset (Chinta, 2013).
The first supercomputer was introduced by
Seymour Cray in the early 70’s. Supercomputers
have wide range of applications like constructing
weather maps, construction of nuclear weapons,
atom bombs, finding oil, earthquake prediction,
etc. They are also used in space exploration,
environmental simulations or global warming
effects, mathematics, physics, medicine, etc.
The contemporary supercomputer is a high
performance cluster with a tightly-coupled high-
speedinterconnectthatusesparallelapplications.
Supercomputing is currently in the middle of
large technological, architectural and application
changesthatgreatlyimpactthewayprogrammers
thinkaboutthesystem.Computationalmethodsfor
solving the problems has become very important
inmanyscientificandengineeringareaswherethe
calculations becomes limiting. Supercomputers
can help address these problems provided they
are developed with great functional architectures.
One of the alternatives in supercomputing
is GPU. GPUs are doing well and have the sole
dominance in the markets. GPUs are not a clear
option though (Fielden, 2013). Working with
GPU’s can be trickier than that of CPUs. It needs
modern software code to port to GPUs and ad-
ditionally more time and money (Fielden, 2013).
In data-intensive industries like life sciences,
manufacturing,earthsciences,materialssciences,
etc the volume and the speed of streaming data
that must be analyzed are pushing the boundar-
ies of hardware capabilities. It is very essential
at the moment to bring the power of cutting edge
supercomputingtechnologiestothetoughestdata
challenges that these industries face every day.
Most supercomputers are clusters of MIMD
multiprocessors,eachprocessorofwhichisSIMD.
A SIMD processor executes the same instruc-
tion on more than one set of data at the same
time. MIMD is employed to achieve parallelism,
by using a number of processors that function
asynchronously and independently. Currently,
the data is growing at a very rapid rate but most
of the data is stored and have not been used to
extractthemeaningfulinformation.So,thereisan
eminent need for developing proper mechanisms
ofprocessingtheselargedatasetstoextractuseful
knowledge for better decision making.
In recent years, supercomputers have become
essential tools for scientists and engineers who
has to quickly manipulate large amounts of data.
Nexttosupercomputersinspeedandsizearemini-
supercomputers. Apart from Mainframe comput-
ersandSupercomputers,IBMisdoingresearchin
a new stream called quantum computing which is
believed to be faster than supercomputing. This
computing uses computers whose transistors are
so small and the computer is working with atoms
andmolecules(MainframesandSupercomputers,
2012). A quantum computer would be capable of
solving millions of calculations at once- and able
tocrackanycomputercodeonEarth(Mainframes
and Supercomputers, 2012).
Supercomputers are so powerful that they
provide researchers with insight into phenomena
that are too small, too big, too fast or too slow to
observe in the normal laboratories (Karin, 2002).
For example, astrophysicists use supercomputers
as “time machines” to explore the past and the
future of our universe. A supercomputer simula-
tion was first created in 2000 that depicted the
collision of two galaxies: our Milky Way and
Andromeda (Karin, 2002). Although this colli-
sion is not allowed to happen for another three
billion years, the simulation allowed scientists to
run the experiments and see the results. A similar
simulation was also performed on Blue Horizon,
a parallel supercomputer at the San Diego Super-
computerCenter(Karin,2002).Using256ofBlue
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