The Experts below are selected from a list of 5922 Experts worldwide ranked by ideXlab platform
Arnaud Giersch - One of the best experts on this subject based on the ideXlab platform.
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dynamic frequency scaling for energy consumption reduction in synchronous distributed applications
International Symposium on Parallel and Distributed Processing and Applications, 2014Co-Authors: Jean-claude Charr, Ahmed Fanfakh, Raphael Couturier, Arnaud GierschAbstract:Dynamic Voltage Frequency Scaling (DVFS) can be applied to modern CPUs. This technique is usually used to reduce the energy consumed by a CPU while computing. Thus, decreasing the frequency reduces the power consumed by the CPU. However, it can also significantly affect the performance of the Executed Program if it is compute bound and if a low CPU frequency is selected. Therefore, the chosen scaling factor must give the best possible trade-off between energy reduction and performance. In this paper we present an algorithm that predicts the energy consumed with each frequency gear and selects the one that gives the best ratio between energy consumption reduction and performance. This algorithm works online without training or profiling and has a very small overhead. It also takes into account synchronous communications between the nodes that are executing the distributed algorithm. The algorithm has been evaluated over the SimGrid simulator while being applied to the NAS parallel benchmark Programs. The results of the experiments show that it outperforms other existing scaling factor selection algorithms.
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ISPA - Dynamic Frequency Scaling for Energy Consumption Reduction in Synchronous Distributed Applications
2014 IEEE International Symposium on Parallel and Distributed Processing with Applications, 2014Co-Authors: Jean-claude Charr, Ahmed Fanfakh, Raphael Couturier, Arnaud GierschAbstract:Dynamic Voltage Frequency Scaling (DVFS) can be applied to modern CPUs. This technique is usually used to reduce the energy consumed by a CPU while computing. Thus, decreasing the frequency reduces the power consumed by the CPU. However, it can also significantly affect the performance of the Executed Program if it is compute bound and if a low CPU frequency is selected. Therefore, the chosen scaling factor must give the best possible trade-off between energy reduction and performance. In this paper we present an algorithm that predicts the energy consumed with each frequency gear and selects the one that gives the best ratio between energy consumption reduction and performance. This algorithm works online without training or profiling and has a very small overhead. It also takes into account synchronous communications between the nodes that are executing the distributed algorithm. The algorithm has been evaluated over the SimGrid simulator while being applied to the NAS parallel benchmark Programs. The results of the experiments show that it outperforms other existing scaling factor selection algorithms.
Mario Bravetti - One of the best experts on this subject based on the ideXlab platform.
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WS-FM - Formalizing RESTful Services and Web-OS Middleware
Lecture Notes in Computer Science, 2014Co-Authors: Mario BravettiAbstract:Web Operating Systems can be seen as an extension of traditional Operating Systems where the addresses used to manage files and execute Programs (via the basic load/execution mechanism) are extended from local filesystem path-names to URLs. A first consequence is that, similarly as in traditional web technologies, executing a Program at a given URL, can be done in two modalities: either the execution is performed client-side at the invoking machine (and relative URL addressing in the Executed Program set to refer to the invoked URL) or it is performed server-side at the machine addressed by the invoked URL (as, e.g., for a web service). Moreover in this context, user identification for access to Programs and files and workflow-based composition of service Programs is naturally based on token/session-like mechanisms. We propose a middleware based on client-server protocols and on a set primitives, for managing files/resources and executing Programs (in the form of client-side/server-side components/services) in Web Operating Systems, based on (an extension of) the REST architecture. We formally define the semantics of such middleware by first introducing a process algebra for standard REST and then extending it to the whole middleware.
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File Managing and Program Execution in Web Operating Systems
arXiv: Software Engineering, 2010Co-Authors: Mario BravettiAbstract:Web Operating Systems can be seen as an extension of traditional Operating Systems where the addresses used to manage files and execute Programs (via the basic load/execution mechanism) are extended from local filesystem path-names to URLs. A first consequence is that, similarly as in traditional web technologies, executing a Program at a given URL, can be done in two modalities: either the execution is performed client-side at the invoking machine (and relative URL addressing in the Executed Program set to refer to the invoked URL) or it is performed server-side at the machine addressed by the invoked URL (as, e.g., for a web service). Moreover in this context, user identification for access to Programs and files and workflow-based composition of service Programs is naturally based on token/session-like mechanisms. We propose a middleware based on client-server protocols and on a set primitives, for managing files/resources and executing Programs (in the form of client-side/server-side components/services) in Web Operating Systems. We formally define the semantics of such middleware via a process algebraic approach.
Nirupa R. Ghai - One of the best experts on this subject based on the ideXlab platform.
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The Cancer Research Network: a platform for epidemiologic and health services research on cancer prevention, care, and outcomes in large, stable populations
Cancer Causes & Control, 2016Co-Authors: Jessica Chubak, Rebecca Ziebell, Robert T. Greenlee, Stacey Honda, Mark C. Hornbrook, Mara Epstein, Larissa Nekhlyudov, Pamala A. Pawloski, Debra P. Ritzwoller, Nirupa R. GhaiAbstract:Purpose The ability to collect data on patients for long periods prior to, during, and after a cancer diagnosis is critical for studies of cancer etiology, prevention, treatment, outcomes, and costs. We describe such data capacities within the Cancer Research Network (CRN), a cooperative agreement between the National Cancer Institute (NCI) and organized health care systems across the United States. Methods Data were extracted from each CRN site’s virtual data warehouse using a centrally written and locally Executed Program. We computed the percent of patients continuously enrolled ≥1, ≥5, and ≥10 years before cancer diagnosis in 2012–2015 (year varied by CRN site). To describe retention after diagnosis, we computed the cumulative percentages enrolled, deceased, and disenrolled each year after the diagnosis for patients diagnosed in 2000. Results Approximately 8 million people were enrolled in ten CRN health plans on December 31, 2014 or 2015 (year varied by CRN site). Among more than 30,000 recent cancer diagnoses, 70 % were enrolled for ≥5 years and 56 % for ≥10 years before diagnosis. Among 25,274 cancers diagnosed in 2000, 28 % were still enrolled in 2010, 45 % had died, and 27 % had disenrolled from CRN health systems. Conclusions Health plan enrollment before cancer diagnosis was generally long in the CRN, and the proportion of patients lost to follow-up after diagnosis was low. With long enrollment histories among cancer patients pre-diagnosis and low post-diagnosis disenrollment, the CRN provides an excellent platform for epidemiologic and health services research on cancer incidence, outcomes, and costs.
Jean-claude Charr - One of the best experts on this subject based on the ideXlab platform.
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dynamic frequency scaling for energy consumption reduction in synchronous distributed applications
International Symposium on Parallel and Distributed Processing and Applications, 2014Co-Authors: Jean-claude Charr, Ahmed Fanfakh, Raphael Couturier, Arnaud GierschAbstract:Dynamic Voltage Frequency Scaling (DVFS) can be applied to modern CPUs. This technique is usually used to reduce the energy consumed by a CPU while computing. Thus, decreasing the frequency reduces the power consumed by the CPU. However, it can also significantly affect the performance of the Executed Program if it is compute bound and if a low CPU frequency is selected. Therefore, the chosen scaling factor must give the best possible trade-off between energy reduction and performance. In this paper we present an algorithm that predicts the energy consumed with each frequency gear and selects the one that gives the best ratio between energy consumption reduction and performance. This algorithm works online without training or profiling and has a very small overhead. It also takes into account synchronous communications between the nodes that are executing the distributed algorithm. The algorithm has been evaluated over the SimGrid simulator while being applied to the NAS parallel benchmark Programs. The results of the experiments show that it outperforms other existing scaling factor selection algorithms.
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ISPA - Dynamic Frequency Scaling for Energy Consumption Reduction in Synchronous Distributed Applications
2014 IEEE International Symposium on Parallel and Distributed Processing with Applications, 2014Co-Authors: Jean-claude Charr, Ahmed Fanfakh, Raphael Couturier, Arnaud GierschAbstract:Dynamic Voltage Frequency Scaling (DVFS) can be applied to modern CPUs. This technique is usually used to reduce the energy consumed by a CPU while computing. Thus, decreasing the frequency reduces the power consumed by the CPU. However, it can also significantly affect the performance of the Executed Program if it is compute bound and if a low CPU frequency is selected. Therefore, the chosen scaling factor must give the best possible trade-off between energy reduction and performance. In this paper we present an algorithm that predicts the energy consumed with each frequency gear and selects the one that gives the best ratio between energy consumption reduction and performance. This algorithm works online without training or profiling and has a very small overhead. It also takes into account synchronous communications between the nodes that are executing the distributed algorithm. The algorithm has been evaluated over the SimGrid simulator while being applied to the NAS parallel benchmark Programs. The results of the experiments show that it outperforms other existing scaling factor selection algorithms.
James K. Drennen - One of the best experts on this subject based on the ideXlab platform.
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Innovation in Pharmaceutical Experimentation Part 1: Review of Experimental Designs Used in Industrial Pharmaceutics Research and Introduction to Bayesian D-Optimal Experimental Design
Journal of Pharmaceutical Innovation, 2008Co-Authors: Phillip D. Lunney, Robert P. Cogdill, James K. DrennenAbstract:The concept of design space, as described in the ICH Harmonized Tripartite Guideline Q8 for Pharmaceutical Development (Q8 Pharmaceutical development, ICH harmonized tripartite guidelines, in International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use , 2005 ), was introduced to justify regulatory flexibility in pharmaceutical manufacturing operations. The basis for this concept is that advanced understanding of variables affecting product quality, obtained either through historical operation or demonstrated through process modeling, justifies replacement of traditional process targets with acceptable operational ranges. Process adjustments that allow operation within the region defined by the design space do not require regulatory oversight. Whereas there are many advantages to having the flexibility to operate within such ranges, the concept is only valid when the design space has been adequately described by appropriate experimentation. Given the complexity of pharmaceutical processes and the number of variables to consider in developing operational ranges, only a well-Executed Program of experiments, supported by appropriate statistical analyses, could provide the necessary information to truly capture a design space. Thus, the risk of employing a design space is that the model will be applied to a region outside of the approved design space, either through a false statistical inference or by omitting some important factor effects. This article presents a review of the experimental strategies typically employed to develop pharmaceutical processes with special emphasis on the assumptions and limitations of the approaches. An alternative strategy that provides an opportunity to build on previous information efficiently without requiring extraordinary skill in statistics, Bayesian optimal design , is introduced as an alternative to the classical approaches.