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Information discovery for interoperable autonomous database systemsZisman, Andrea January 1998 (has links)
No description available.
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A steroid profiling expert systemDybowski, Richard January 1989 (has links)
No description available.
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Proof methods and pragmatics for parallel programmingTofts, Chris January 1990 (has links)
No description available.
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Fully abstract models of programming languagesStoughton, Allen January 1986 (has links)
No description available.
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Generative grammars and the computer-aided composition of musicHoltzman, Steven R. January 1980 (has links)
No description available.
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Content addressable memory : design and usage for general purpose computingBlair, Gerard M. January 1986 (has links)
No description available.
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Data abstraction and the correctness of modular programmingSchoett, Oliver January 1986 (has links)
No description available.
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Summarizing video for improved navigation and browsingMacer, Peter James January 1998 (has links)
No description available.
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Assessing the Suitability of Python as a Language for Parallel ProgrammingKohli, Manav S 01 January 2016 (has links)
With diminishing gains in processing power from successive generations of hardware development, there is a new focus on using advances in computer science and parallel programming to build faster, more efficient software. As computers trend toward including multiple and multicore processors, parallel computing serves as a promising option for optimizing the next generation of software applications. However, models for implementing parallel programs remain highly opaque due to their reliance on languages such as Fortran, C, and C++. In this paper I investigate Python an option for implementing parallel programming techniques in application development. I analyze the efficiency and accessibility of MPI for Python and IPython Parallel packages by calculating in parallel using a Monte Carlo simulation and comparing their speeds to the sequential calculation. While MPI for Python offers the core functionality of MPI and C-like syntax in Python, IPython Parallel's architecture provides a truly unique model.
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Orthogonal persistence : an abstract representation of persistent storage in Algol-like languagesCockshott, William Paul January 1982 (has links)
No description available.
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