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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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Parallel multischeme computation
Journal of Scientific Computing, 1988zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yi-ling F. Chiang +3 more
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Pedagogy and tools for teaching parallel computing at the sophomore undergraduate level
J. Parallel Distributed Comput., 2017As the need for multicore-aware programmers rises in both science and industry, Computer Science departments in universities around the USA are having to rethink their parallel computing curriculum.
M. Grossman +5 more
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Parallel computing on personal computers
Proceedings of the 1986 ACM SIGSMALL/PC symposium on Small systems - SIGSMALL '86, 1986A set of Personal Computers is connected to form a ring-structured parallel system. Each computer has access to its local memory and can communicate with its two neighbours in the ring.This network of asynchronous processors is used to solve in parallel combinatorial optimization problems that are too time- and space-consuming to be handled on a single
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Responsive Parallel Computation
2021Multicore processors are becoming increasingly prevalent, blurring the lines between traditional parallel programs, which use cooperative threading to reduce executiontime, and interactive programs which use competitive threading to increase responsiveness.
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Complex Syst., 1996
Summary: Evolution is applied to the development of parallel digital computer programs. The environment is a shared memory virtual computer containing a population of parallel computer programs. Although the digital computer is a very different environment than the ecology of Earth, evolution is shown to work effectively in the digital environment and ...
Kurt H. Thearling, Thomas S. Ray
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Summary: Evolution is applied to the development of parallel digital computer programs. The environment is a shared memory virtual computer containing a population of parallel computer programs. Although the digital computer is a very different environment than the ecology of Earth, evolution is shown to work effectively in the digital environment and ...
Kurt H. Thearling, Thomas S. Ray
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Optimization with Parallel Computing
2001Complexity Engineering deals with harnessing the power of Cellular Automata (CA) like simple models to solve real life difficult and complex engineering problems, dealing with systems that have very simple components that collectively exhibit complex behaviors.
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Parallel computation model for parallel prolog
1992A new parallel computation model for logic programs is described. A parallel logic programming language Parallel Prolog has been considered as a high level language. A data-flow model is a theoretical background of our computation model. Owing to this the model is asynchronous and utilizes innate kinds of parallelism for a highly parallel all solution ...
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Proceedings of the 1st international workshop on Multicore software engineering, 2008
Many problems require parallel solutions and implementations and how to extract and specify parallelism has been the focus of Research during the last few decades. While there has been a significant progress in terms of (a)automatically deriving implicit parallelism from functional and logic programs, (b) using parallelizing compilers to extract ...
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Many problems require parallel solutions and implementations and how to extract and specify parallelism has been the focus of Research during the last few decades. While there has been a significant progress in terms of (a)automatically deriving implicit parallelism from functional and logic programs, (b) using parallelizing compilers to extract ...
openaire +1 more source
Parallel Computing with Mathematica
2001The MathLink communication protocol can be used to control several Mathematica kernel processes from within Mathematica. This feature allows the implementation of an environment for parallel programming, the Parallel Computing Toolkit, using processes with distributed memory. The toolkit is written completely in Mathematica in a machine-independent way,
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