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Translational process: Mathematical software perspective
DOI:10.1016/j.jocs.2020.101216.png)
Abstract
En 中文
Each successive generation of computer architecture has brought new challenges to achieving high performance mathematical solvers, necessitating development and analysis of new algorithms, which are then embodied in software libraries. These libraries hide architectural details from applications, allowing them to achieve a level of portability across platforms from desktops to world-class high performance computing (HPC) systems. Thus there has been an informal translational computer science process of developing algorithms and distributing them in open source software libraries for adoption by applications and vendors. With the move to exascale, increasing intentionality about this process will benefit the long-term sustainability of the scientific software stack.
Keywords:
DATAFLOW scheduling runtimes
Hardware accelerators
Communication avoiding algorithms
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