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- W1971360512 abstract "In scientific computing, scaling issues frequently occur as more processors are utilized and/or the problem size is increased. Applications that run well on small problems and small machines, don't necessarily work well, or at all when executed at larger scale. It is desirable to avoid using expensive supercomputer time for discovering and correcting problems; instead, we would like to do this beforehand using analysis and/or testing.In this position paper, we discuss testing and problem and target platform specific static analyses of scientific programs developed using the Super Instruction Architecture, a parallel programming environment for computational chemistry. In particular, a set of tools which perform abstract interpretation, allow us to answer questions about resource usage and computation time for specific scaled-up inputs and machine configurations without needing to run the full program on the target platform." @default.
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- W1971360512 date "2014-11-01" @default.
- W1971360512 modified "2023-09-23" @default.
- W1971360512 title "Abstract Interpretation: Testing at Scale without Testing at Scale" @default.
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- W1971360512 doi "https://doi.org/10.1109/se-hpccse.2014.8" @default.
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