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- W118772227 abstract "Performance modeling and analysis is essential to assess the effectiveness of parallel and pipelined architectures in scientific computing applications. Traditional performance analysis has focused on separate levels of computation (e.g. instruction, loop, algorithm, or application) but such approaches often do not a provide a complete picture of the performance behavior. New multilevel performance models which integrate these various levels are necessary to adequately evaluate distributed and shared memory systems. Our study focuses on four computing systems, each representing the major parallel architecture classes: a distributed memory SIMD system (the Connection Machine CM-2), a shared memory MIMD system (Evans & Sutherland ES-1), a shared/distributed memory hybrid system (Myrias SPS-2), and a distributed MIMD system (Intel iPSC/860.) Using an integrated multilevel approach we can accurately describe the behavior of matrix/vector operations, relaxation techniques, and PDE applications on these architectures. To demonstrate the usefulness of these models, we utilize a concrete example of a 2D fluid code describing atmospheric and oceanic systems and show how such models can predict application performance to within ten percent error." @default.
- W118772227 created "2016-06-24" @default.
- W118772227 creator A5076605665 @default.
- W118772227 date "1992-01-01" @default.
- W118772227 modified "2023-09-23" @default.
- W118772227 title "Performance modeling of parallel architectures for scientific computing" @default.
- W118772227 hasPublicationYear "1992" @default.
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