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Computational biology on parallel computers

2003 European Control Conference (ECC), 2003
Several applications in computational biology have large runtime and memory requirements either because of large data sizes or the inherent time and memory complexity of the underlying algorithms. Parallel computing is an effective way to address both these concerns — run-time can be reduced by the use of multiple processors to solve the same problem ...
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Large Parallel Computers

Journal of the ACM, 1966
Various classes of machines incorporating parallelism are considered. A general class of large-scale multiprocessors is outlined, and some problems of hardware and software implementation for computers of this class are discussed.
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Parallel computing with CUDA

2010 IEEE International Symposium on Parallel & Distributed Processing (IPDPS), 2010
NVIDIA's CUDA architecture provides a powerful platform for writing highly parallel programs. By providing simple abstractions for hierarchical thread organization, memories, and synchronization, the CUDA programming model allows programmers to write scalable programs without the burden of learning a multitude of new programming constructs.
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Parallelism in Seismic Computing

Surveys in Geophysics, 1989
This paper describes a vectorized and parallelized implementation of a two-dimensional pseudo-spectral seismic elastic model and of a (frequency-domain) seismic migration algorithm on the (tightly-coupled) vector multiprocessor IBM 3090 VF. Performance data of alternative parallel implementations on an LCAP (loosely coupled system of array processors ...
M. Kindelan, P. Sguazzero, A. Kamel
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Parallel visual computation

Nature, 1983
The functional abilities and parallel architecture of the human visual system are a rich source of ideas about visual processing. Any visual task that we can perform quickly and effortlessly is likely to have a computational solution using a parallel algorithm. Recently, several such parallel algorithms have been found that exploit information implicit
D H, Ballard   +2 more
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Parallel Scientific Computation

Science, 1993
Massively parallel computers offer scientists a new tool for computation, with capabilities and limitations that are substantially different from those of traditional serial computers. Most categories of large-scale scientific computations have proven remarkably amenable to parallel computation, but often the algorithms involved are different from ...
W D, Hillis, B M, Boghosian
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Parallel computing in Russia

1995
Due to restricted size of the paper we needed to limit our overview to short summaries of the above topics. However, there are other Russian works in the field of parallel computing which we would like also distinguish.
Yakov I. Fet, Dmitri A. Pospelov
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On the parallel computation thesis

Logic Journal of IGPL, 2016
We develop a generic programming language for parallel algorithms, one that works for all data structures and control structures. We show that any parallel algorithm satisfying intuitively-appealing postulates can be modeled by a collection of cells, each of which is an abstract state machine, augmented with the ability to spawn new cells.
Nachum Dershowitz   +1 more
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The Pax parallel computer

IEEE Micro, 1990
Some aspects of a long-term parallel-processing research project (PACS, Pax, and Qcd Pax) begun in 1977 at Kyoto University and Hitachi Corporation's Nuclear Power Division are discussed. The discussion is based on an analysis of a number of papers, a book detailing this work, several visits to the project laboratory in Japan, and an examination of ...
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Challenges for parallel computing

Proceedings of the 2009 Conference of the Center for Advanced Studies on Collaborative Research - CASCON '09, 2009
There has been an overwhelming trend in recent years to move towards parallel computing. Hardware manufacturers are increasing the amount of parallelism on a single chip in several ways, including adding more processing cores and accelerators to execute the same instructions on many data items simultaneously.
Kit Barton   +2 more
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