Exascale Machines Require New Programming Paradigms and

c © The Authors 2015. This paper is published with open access at SuperFri.org Extreme scale parallel computing systems will have tens of thousands of optionally accelerator-equipped nodes with hundreds of cores each, as well as deep memory hierarchies and complex interconnect topologies. Such exascale systems will provide hardware parallelism at multi-ple levels and will be energy constrained. Their extreme scale and the rapidly deteriorating reliabil-ity of their hardware components means that exascale systems will exhibit low mean-time-between-failure values. Furthermore, existing programming models already require heroic programming and optimization efforts to achieve high efficiency on current supercomputers. Invariably, these efforts are platform-specific and non-portable. In this article, we explore the shortcomings of existing programming models and runtimes for large-scale computing systems. We propose and discuss important features of programming paradigms and runtimes to deal with exascale computing sys-tems with a special focus on data-intensive applications and resilience. Finally, we discuss code sustainability issues and propose several software metrics that are of paramount importance for code development for ultrascale computing systems