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Dynamic parallelization of computations [PDF]
Cybernetics and Systems Analysis, 1997 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Parallelism in Matrix Computations
2016This book is primarily intended as a research monograph that could also be used in graduate courses for the design of parallel algorithms in matrix computations. It assumes general but not extensive knowledge of numerical linear algebra, parallel architectures, and parallel programming paradigms.
Philippe, Bernard +2 more
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IEEE Transactions on Services Computing, 2021
Today's large-scale parallel workflows are often processed on heterogeneous distributed computing platforms. From an economic perspective, computing resource providers should minimize the cost while offering high service quality.
Biao Hu, Zhengcai Cao, Mengchu Zhou
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Today's large-scale parallel workflows are often processed on heterogeneous distributed computing platforms. From an economic perspective, computing resource providers should minimize the cost while offering high service quality.
Biao Hu, Zhengcai Cao, Mengchu Zhou
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Parallel multischeme computation
Journal of Scientific Computing, 1988zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chia-Yo Chang +3 more
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Parallel Scientific Computation
Science, 1993Massively 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. Daniel Hillis, Bruce M. Boghosian
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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
Dana H. Ballard +2 more
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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
Dana H. Ballard +2 more
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Parallelism in Seismic Computing
Surveys in Geophysics, 1989This 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 ...
P. Sguazzero, Manuel Kindelan, A. Kamel
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IEEE International Solid-State Circuits Conference, 2020
Non-volatile memory (NVM) based computing-in-memory (CIM) shows significant advantages in handling deep learning tasks for artificial intelligence (AI) applications.
Qi Liu +14 more
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Non-volatile memory (NVM) based computing-in-memory (CIM) shows significant advantages in handling deep learning tasks for artificial intelligence (AI) applications.
Qi Liu +14 more
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2015
Scientific computing has become an indispensable tool in numerous fields, such as physics, mechanics, biology,finance and industry. For example, it enables us, thanks to efficient algorithms adapted to current computers, tosimulate, without the help of models or experimentations, the deflection of beams in bending, the sound level in a theater room or ...
Magoules, F., Roux, F.-X., Houzeaux, G.
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Scientific computing has become an indispensable tool in numerous fields, such as physics, mechanics, biology,finance and industry. For example, it enables us, thanks to efficient algorithms adapted to current computers, tosimulate, without the help of models or experimentations, the deflection of beams in bending, the sound level in a theater room or ...
Magoules, F., Roux, F.-X., Houzeaux, G.
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Parallel Computing, 1993
GF11 is a parallel computer currently nearing completion at the IBM Yorktown Research Center. The machine will have a peak arithmetic rate of 11.4 Gflops and a total memory of 1.14 Gbytes. The computational power and memory are uniformly distributed among 566 floating-point processors which communicate through a switching network. At each machine cycle
Manoj Kumar +2 more
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GF11 is a parallel computer currently nearing completion at the IBM Yorktown Research Center. The machine will have a peak arithmetic rate of 11.4 Gflops and a total memory of 1.14 Gbytes. The computational power and memory are uniformly distributed among 566 floating-point processors which communicate through a switching network. At each machine cycle
Manoj Kumar +2 more
openaire +3 more sources