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Books : Computers & Internet : Hardware : Supercomputers
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Will the Geeks inherit the earth?
If computers become twice as fast and twice as capable every two years, how long is it before they’re as intelligent as humans? More intelligent? And then in two more years, twice as intelligent? How long before you won’t be able to tell if you are texting a person or an especially ingenious chatterbot program designed to simulate intelligent human conversation?
According to Richard Dooling in Rapture for the Geeks—maybe not that long. It took humans millions of years to develop opposable thumbs (which we now use to build computers), but computers go from megabytes to gigabytes in five years; from the invention of the PC to the Internet in less than fifteen. At the accelerating rate of technological development, AI should surpass IQ in the next seven to thirty-seven years (depending on who you ask). We are sluggish biological sorcerers, but we’ve managed to create whiz-bang machines that are evolving much faster than we are.
In this fascinating, entertaining, and illuminating book, Dooling looks at what some of the greatest minds have to say about our role in a future in which technology rapidly leaves us in the dust. As Dooling writes, comparing human evolution to technological evolution is “worse than apples and oranges: It’s appliances versus orangutans.” Is the era of Singularity, when machines outthink humans, almost upon us? Will we be enslaved by our supercomputer overlords, as many a sci-fi writer has wondered? Or will humans live lives of leisure with computers doing all the heavy lifting?
With antic wit, fearless prescience, and common sense, Dooling provocatively examines nothing less than what it means to be human in what he playfully calls the age of b.s. (before Singularity)—and what life will be like when we are no longer alone with Mother Nature at Darwin’s card table. Are computers thinking and feeling if they can mimic human speech and emotions? Does processing capability equal consciousness? What happens to our quaint beliefs about God when we’re all worshipping technology? What if the human compulsion to create ever more capable machines ultimately leads to our own extinction? Will human ingenuity and faith ultimately prevail over our technological obsessions? Dooling hopes so, and his cautionary glimpses into the future are the best medicine to restore our humanity.
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This text evolved from a new curriculum in scientific computing that was developed to teach undergraduate science and engineering majors how to use high-performance computing systems (supercomputers) in scientific and engineering applications.
Designed for undergraduates, An Introduction to High-Performance Scientific Computing assumes a basic knowledge of numerical computation and proficiency in Fortran or C programming and can be used in any science, computer science, applied mathematics, or engineering department or by practicing scientists and engineers, especially those associated with one of the national laboratories or supercomputer centers.
The authors begin with a survey of scientific computing and then provide a review of background (numerical analysis, IEEE arithmetic, Unix, Fortran) and tools (elements of MATLAB, IDL, AVS). Next, full coverage is given to scientific visualization and to the architectures (scientific workstations and vector and parallel supercomputers) and performance evaluation needed to solve large-scale problems. The concluding section on applications includes three problems (molecular dynamics, advection, and computerized tomography) that illustrate the challenge of solving problems on a variety of computer architectures as well as the suitability of a particular architecture to solving a particular problem.
Finally, since this can only be a hands-on course with extensive programming and experimentation with a variety of architectures and programming paradigms, the authors have provided a laboratory manual and supporting software via anonymous ftp.
Scientific and Engineering Computation series
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This book contains 27 edited papers presented at the Fifth International Conference on Applications of High-performance Computers in Engineering, which was held in Santiago de Compostela, Spain, July 2-4, 1997. The papers present advances in the application of supercomputing to numerically intensive problems in engineering.
Early high-performance computers (supercomputers) were huge, expensive, and located in computer centers, and thus limited to use by a few researchers. The increase of power and decrease in the cost of computer processors have led to a reduction in the cost of single high-performance computers, but they are still used by few organizations. On the other hand, the low cost of personal computers and workstations today enables each researcher to have his or her own computer facility, limited only by the capacity of the equipment. Such machines are often networked together, so that users can do remote log-ins and share files and public facilities in various ways.
The concept of virtual machine, a dynamic collection of (potentially heterogeneous) computational resources managed as a single parallel computer, has revolutionized distributed computers by allowing their use as a high-performance system. Nowadays portable parallel distributed software systems are available that enable a collection of heterogeneous computers to be used as a coherent and flexible concurrent computational resource. This software can integrate these machines and utilize their unused cycles to obtain a reasonably powerful computer system.
As the power of computers has grown, the complexity of the problems which can be solved by them as grown. The application of high-performance computing to numerically intensive problems in engineering raises several new issues that did not arise with standard computing. New algorithms and codes are required in order to exploit effectively the power of these new computer architectures, as programs suitable for conventional computers are likely to achieve very modest improvement of performance on high-performance computers. Some of these new techniques are addressed in the papers within this book, in particular those related to the concept of virtual machines.
The field of high-performance computing is continuously changing. Although there are still changes being made in the hardware of high-performance computers, it is evident that the future of high-performance computing in engineering and science is in massively parallel computing. Therefore, engineers and scientists need to parallelize their numerical computer codes to be able to take advantage of the changes in high-performance computers. In that regard, the possible antagonism between algorithm and hardware, showing that there is a change of spending too much time on programming different computer topologies versus think time, i.e., the time spent on the mathematical physics of the problem and numerical analysis in designing algorithms. Often a more natural mathematical algorithm founded on physical principles can lead to a better parallel computing formulations.
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Proceedings of the Second International Conference on Applications of Supercomputers in Engineering, ASE/91, Massachusetts Institute of Technology, Cambridge, MA, USA, August 1991
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Siewiorek and Koopman's book describes the architecture of the first member of a new class of computers, the giant supercomputer workstation. The authors concentrate on the motivation for defining a new class of computer architectures as well as on the form of the architecture that responds to the specifications for this new class.
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Coordination, considered abstractly, is an ubiquitous notion in computer science: for example, programming languages coordinate elementary instructions; operating systems coordinate accesses to hardware resources; database transaction schedulers coordinate accesses to shared data; etc. All these situations have some common features, which can be identified at the abstract level as "coordination mechanisms". This book focuses on a class of coordination models where multiple pieces of software coordinate their activities through some shared dataspace. The book has three parts. Part 1 presents the main coordination models studied in this book (Gamma, LO, TAO, LambdaN). Part 2 focuses on various semantics aspects of coordination, applied mainly to Gamma. Part 3 presents actual implementations of coordination models and an application.
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Building a computer ten times more powerful than all the networked computing capability in the United States is the subject of this book by leading figures in the high performance computing community. It summarizes the near-term initiatives, including the technical and policy agendas for what could be a twenty-year effort to build a petaFLOP scale computer. (A FLOP—Floating Point OPeration—is a standard measure of computer performance and a PetaFLOP computer would perform a million billion of these operations per second.)
Chapters focus on four interrelated areas: applications and algorithms, device technology, architecture and systems, and software technology.
While a petaFLOPS machine is beyond anything within contemporary experience, early research into petaFLOPS system design and methodologies is essential to U.S. leadership in all facets of computing into the next century. The findings reported here explore new and fertile ground. Among them: construction of an effective petaFLOPS computing system will be feasible in two decades, although effectiveness and applicability will depend on dramatic cost reductions as well as innovative approaches to system software and programming methodologies; a mix of technologies such as semiconductors, optics, and possibly cryogenics will be required; and while no fundamental paradigm shift in system architecture is expected, active latency management will be essential, requiring a high degree of fine-grain parallelism and the mechanisms to exploit it.
Scientific and Engineering Computation series
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This uniquely comprehensive book brings together the vast amount of technical, economic, and political information and the analyses of supercomputing that have hitherto been buried in the frequently inaccessible "gray literature." Seventy-nine distinguished participants in the second Frontiers of Supercomputing conference offer perceptive and often controversial views on the emerging computing environment in the United States.
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Designed to show how programming will be changed by the concepts of parallel systems and how these concepts relate to the ideas of functions and objects, and demonstrates the kind of programming that can be done on these systems.
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The book contains reports about the most significant projects from science and engineering of the Federal High Performance Computing Center Stuttgart (HLRS). They were carefully selected in a peer-review process and are showcases of an innovative combination of state-of-the-art modeling, novel algorithms and the use of leading-edge parallel computer technology. The projects of HLRS are using supercomputer systems operated jointly by university and industry and therefore a special emphasis has been put on the industrial relevance of results and methods.
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This comprehensive volume presents the refereed proceedings of the International Conference and Exhibition on High-Performance Computing and Networking, HPCN Europe 1996, held in Brussels, Belgium, in April 1996 under the sponsorship of the CEC. The 175 papers and posters included address all relevant theoretical aspects of HPCN and computational sciences as well as a variety of applicational aspects in numerous fields. The volume is organized in four tracks; industrial applications, general applications, computational science, and computer science aspects of HPCN.
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High-performance computing and networking (HPCN) is driven by several initiatives in Europe, the United States, and Japan. In Europe several groups encouraged the Commission of the European Communities to start an HPCN programme. This two-volume work presents the proceedings of HPCN Europe 1994. Volume 1 includes sections on: keynote talks, HPCN and visualization in industry, algorithms for engineering applications, electrical computer-aided engineering, computational fluid dynamics, computational chemistry, materials science, weather simulations, environmental applications and climate, high-energy physics and astrophysics, neuroscience and neural networks, and database applications.
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