The gurevich’s thesis stipulates that sequential abstract state machines (asms) capture the essence of sequential algorithms. On another hand, the bulk-synchronous parallel (bsp) bridging model is a well known model for hpc algorithm design. It provides a conceptual bridge between the physical implementation of the machine and the abstraction available to a programmer of that machine. The assumptions of the bsp model are thus provide portable and scalable performance predictions on most hpc systems. We follow gurevich’s thesis and extend the sequential postulates in order to intuitively and realistically capture bsp algorithms.
CITATION STYLE
Marquer, Y., & Gava, F. (2018). An axiomatization for BSP algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11336 LNCS, pp. 72–88). Springer Verlag. https://doi.org/10.1007/978-3-030-05057-3_6
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