An Axiomatization for BSP Algorithms

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.

[1]  Torsten Suel,et al.  BSPlib: The BSP programming library , 1998, Parallel Comput..

[2]  Klaus-Dieter Schewe,et al.  A Simplified Parallel ASM Thesis , 2012, ABZ.

[3]  Rob H. Bisseling,et al.  Parallel scientific computation - a structured approach using BSP and MPI , 2004 .

[4]  Jin-Soo Kim,et al.  HAMA: An Efficient Matrix Computation with the MapReduce Framework , 2010, 2010 IEEE Second International Conference on Cloud Computing Technology and Science.

[5]  Matthew Felice Pace,et al.  BSP vs MapReduce , 2012, ICCS.

[6]  Yoann Marquer.  Algorithmic Completeness of Imperative Programming Languages , 2019, Fundam. Informaticae.

[7]  Klaus-Dieter Schewe,et al.  Concurrent abstract state machines , 2016, Acta Informatica.

[8]  Franck Cappello,et al.  On Communication Determinism in Parallel HPC Applications , 2010, 2010 Proceedings of 19th International Conference on Computer Communications and Networks.

[9]  Elvinia Riccobene,et al.  A formal model for the parallel semantics of P3L , 2000, SAC '00.

[10]  Yuri Gurevich,et al.  Sequential abstract-state machines capture sequential algorithms , 2000, TOCL.

[11]  Horacio González-Vélez,et al.  A survey on statistical disclosure control and micro-aggregation techniques for secure statistical databases , 2010 .

[12]  Luc Bougé.  The Data Parallel Programming Model: A Semantic Perspective , 1996, The Data Parallel Programming Model.

[13]  Klaus-Dieter Schewe,et al.  A new thesis concerning synchronised parallel computing - simplified parallel ASM thesis , 2015, Theor. Comput. Sci..

[14]  Aart J. C. Bik,et al.  Pregel: a system for large-scale graph processing , 2010, SIGMOD Conference.

[15]  Frédéric Gava,et al.  An ASM Thesis for BSP , 2018 .

[16]  Leslie G. Valiant,et al.  A bridging model for parallel computation , 1990, CACM.

[17]  Leslie G. Valiant,et al.  A bridging model for multi-core computing , 2008, J. Comput. Syst. Sci..

[18]  Andreas Blass,et al.  Abstract state machines capture parallel algorithms , 2003, TOCL.

[19]  David B. Skillicorn,et al.  Questions and Answers about BSP , 1997, Sci. Program..

[20]  Andreas Prinz,et al.  Distributed ASM - Pitfalls and Solutions , 2014, ABZ.

[21]  Rob H. Bisseling,et al.  Parallel Scientific Computation , 2004 .

[22]  Sergei Gorlatch,et al.  Send-receive considered harmful: Myths and realities of message passing , 2004, TOPL.