225,279 research outputs found
10181 Abstracts Collection -- Program Development for Extreme-Scale Computing
From May 2nd to May 7th, 2010, the Dagstuhl Seminar 10181
``Program Development for Extreme-Scale Computing \u27\u27
was held in Schloss Dagstuhl~--~Leibniz Center for Informatics.
During the seminar, several participants presented their current
research, and ongoing work and open problems were discussed. Abstracts of
the presentations given during the seminar as well as abstracts of
seminar results and ideas are put together in this paper.
Links to extended abstracts or full papers are provided, if available
10181 Executive Summary -- Program Development for Extreme-Scale Computing
From May 2nd to May 7th, 2010, the Dagstuhl Seminar 10181
``Program Development for Extreme-Scale Computing \u27\u27
was held in Schloss Dagstuhl~--~Leibniz Center for Informatics.
During the seminar, several participants presented their current
research, and ongoing work and open problems were discussed.
This paper provides an executive summary of the seminar
Exascale machines require new programming paradigms and runtimes
Extreme scale parallel computing systems will have tens of thousands of optionally accelerator-equiped nodes with hundreds of cores each, as well as deep memory hierarchies and complex interconnect topologies. Such Exascale systems will provide hardware parallelism at multiple levels and will be energy constrained. Their extreme scale and the rapidly deteriorating reliablity 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 optimisation efforts to achieve high efficiency on current supercomputers. Invariably, these efforts are platform-specific and non-portable. In this paper we will explore the shortcomings of existing programming models and runtime systems for large scale computing systems. We then propose and discuss important features of programming paradigms and runtime system to deal with large scale computing systems with a special focus on data-intensive applications and resilience. Finally, we also discuss code sustainability issues and propose several software metrics that are of paramount importance for code development for large scale computing systems
Bullfighting extreme scenarios in efficient hyper-scale cluster computing
Data centres are quickly evolving to support new demands for Cloud-Computing services. Extreme workload peaks
represent a challenge for the maintenance of the performance and service level agreements, even more when operation
costs need to be minimised. In this paper, we first present an extensive analysis of the impact of extreme workloads in
large-scale realistic Cloud-Computing data centres, including a comparison between the most relevant centralised resource managing models. Moreover, we extend our previous works by proposing a new energy-efficiency policy called Bullfighter
which is able to keep performance key performance indicators while reducing energy consumption in extreme scenarios.
This policy employs queue-theory distributions to foresee workload demands and adapt automatically to workload fluc tuations even in extreme environments, while avoiding the fine-tuning required for other energy policies. Finally, it is
shown through extensive simulation that Bullfighter can save more than 40% of energy in the aforementioned scenarios
without exerting any noticeable impact on data-centre performance.Ministerio de Ciencia e Innovación RTI2018-098062-A-I0
- …