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SUMMARY Performance engineering of parallel and distributed applications is a complex task that iterates through various phases, ranging from modeling and prediction, to performance measurement, experiment management, data collection, and bottleneck analysis. There is no evidence so far that all of these phases should/can be integrated in a single(More)
Grid workflow applications are emerging as one of the most interesting application classes for the Grid. In this paper 3 we present AGWL, a novel Grid workflow language to describe the workflow of Grid applications at a high level of abstraction. AGWL has been designed to allow the user to concentrate on describing scientific Grid applications. The user is(More)
HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt età la diffusion(More)
In this paper we introduce a novel approach for modeling performance oriented distributed and parallel applications based on the Unified Modeling Language (UML). We utilize the UML extension mechanisms to customize UML for the domain of performance oriented distributed and parallel computing. A set of UML building blocks is described that model some of the(More)
Performance is one of the key features of parallel and distributed computing systems. Therefore, in the past a significant research effort was invested in the development of approaches for performance modeling and prediction of parallel and distributed computing systems. In this paper we identify the trends, contributions, and drawbacks of the state of the(More)
At a high level of abstraction Grid applications are commonly specified based on the workflow paradigm. We consider that for the wide acceptance of Grid technology it is relevant that the user has the possibility to express requirements on Quality of Service (QoS) at workflow specification time. However, most of the existing workflow languages lack(More)
Heterogeneous many-core systems constitute a viable approach for coping with power constraints in modern computer architectures and can now be found across the whole computing landscape ranging from mobile devices, to desktop systems and servers, all the way to high-end supercomputers and large-scale data centers. While these systems promise to offer(More)
—Supervised learning of Convolutional Neural Networks (CNNs), also known as supervised Deep Learning, is a computationally demanding process. To find the most suitable parameters of a network for a given application, numerous training sessions are required. Therefore, reducing the training time per session is essential to fully utilize CNNs in practice.(More)