Preparing applications for a transition from petascale to exascale systems will require a very large investment in several areas of software research and development. The introduction of manycore nodes, the abundance ...
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Preparing applications for a transition from petascale to exascale systems will require a very large investment in several areas of software research and development. The introduction of manycore nodes, the abundance of parallelism, an increase in system faults (including soft errors) and a complicated, multi-component software environment are some of the most challenging issues we face. In this paper we address four topics we believe to be the most the challenging issues and therefore the greatest opportunities for making effective next-generation scalable applications. First and foremost is the need to transform existing applications to run on manycore platforms and properly design new applications. This is particularly challenging in the absence of a standard, portable manycore programming environment, but we can make progress in this direction while manycore programming models are developed. Second is promoting advanced modeling and simulation capabilities such as embedded optimization and uncertainty quantification that lead to higher quality results and orders of magnitude more parallelism. Third is progress toward fault resilience in applications, a critical need as system reliability degrades. Fourth and finally is a qualitative improvement in software design, including the social aspects, as exascale software systems will be increasingly multi-team and multi-faceted efforts.
advanced modeling and simulation has enabled the design of a variety of innovative products and the analysis of numerous complex phenomenon. However, significant barriers exist to widespread adoption of these tools. I...
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ISBN:
(纸本)9781467395601
advanced modeling and simulation has enabled the design of a variety of innovative products and the analysis of numerous complex phenomenon. However, significant barriers exist to widespread adoption of these tools. In particular, advanced modeling and simulation: (1) is considered complex to use;(2) needs in-house expertise;and (3) requires high capital costs. In this paper, we describe the development of an end-to-end, advanced modeling and simulation cloud platform that encapsulates best practices for scientific computing in the cloud, and demonstrate using Hydra-TH as a prototypical application. As an alternative to traditional advanced modeling and simulation workflows, our Web-based approach simplifies the processes, decreases the need for in-house computational science and engineering experts, and lowers the capital investments. In addition to providing significantly improved, intuitive software, the environment offers reproducible workflows where the full lifecycle of data from input to final analyzed results can be saved, shared, and even published.
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