The Experts below are selected from a list of 27 Experts worldwide ranked by ideXlab platform
Wolfgang Karl - One of the best experts on this subject based on the ideXlab platform.
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a Profiling Tool for detecting cache critical Data structures
European Conference on Parallel Processing, 2007Co-Authors: Tobias Gaugler, Wolfgang KarlAbstract:A poor cache behavior can significantly prohibit achieving high speedup and scalability of parallel applications. This means optimizing a program with respect to cache locality can potentially introduce considerable performance gain. As a consequence, programmers usually perform cache locality optimization for acquiring the expected performance of their applications. Within this work, we developed a Data Profiling Tool dprof with the goal of supporting the users in this task by allowing them to detect the optimization targets in their programs. In contrast to similar Tools which mostly focus on code regions, we address Data structures because they are the direct objects that programmers have to work with. Based on the Performance Monitoring Unit (PMU) provided by modern processors, dprof is capable of finding cache-critical variables, arrays, or even a segment of an array. It can also locate theses access hotspots to the most concrete position such as individual functions and code lines. This feature allows the user to apply dprof for efficient cache optimization.
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Euro-Par - A Profiling Tool for detecting cache-critical Data structures
Euro-Par 2007 Parallel Processing, 2007Co-Authors: Tobias Gaugler, Wolfgang KarlAbstract:A poor cache behavior can significantly prohibit achieving high speedup and scalability of parallel applications. This means optimizing a program with respect to cache locality can potentially introduce considerable performance gain. As a consequence, programmers usually perform cache locality optimization for acquiring the expected performance of their applications. Within this work, we developed a Data Profiling Tool dprof with the goal of supporting the users in this task by allowing them to detect the optimization targets in their programs. In contrast to similar Tools which mostly focus on code regions, we address Data structures because they are the direct objects that programmers have to work with. Based on the Performance Monitoring Unit (PMU) provided by modern processors, dprof is capable of finding cache-critical variables, arrays, or even a segment of an array. It can also locate theses access hotspots to the most concrete position such as individual functions and code lines. This feature allows the user to apply dprof for efficient cache optimization.
Kari A Stephens - One of the best experts on this subject based on the ideXlab platform.
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applying a participatory design approach to define objectives and properties of a Data Profiling Tool for electronic health Data
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2016Co-Authors: Hossein Estiri, Terri Lovins, Nader Afzalan, Kari A StephensAbstract:: We applied a participatory design approach to define the objectives, characteristics, and features of a "Data Profiling" Tool for primary care Electronic Health Data (EHD). Through three participatory design workshops, we collected input from potential Tool users who had experience working with EHD. We present 15 recommended features and characteristics for the Data Profiling Tool. From these recommendations we derived three overarching objectives and five properties for the Tool. A Data Profiling Tool, in Biomedical Informatics, is a visual, clear, usable, interactive, and smart Tool that is designed to inform clinical and biomedical researchers of Data utility and let them explore the Data, while conveniently orienting the users to the Tool's functionalities. We suggest that developing scalable Data Profiling Tools will provide new capacities to disseminate knowledge about clinical Data that will foster translational research and accelerate new discoveries.
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CRI - Applying a Participatory Design Approach to Define Objectives and Properties of a "Data Profiling" Tool for Electronic Health Data.
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2016Co-Authors: Hossein Estiri, Terri Lovins, Nader Afzalan, Kari A StephensAbstract:: We applied a participatory design approach to define the objectives, characteristics, and features of a "Data Profiling" Tool for primary care Electronic Health Data (EHD). Through three participatory design workshops, we collected input from potential Tool users who had experience working with EHD. We present 15 recommended features and characteristics for the Data Profiling Tool. From these recommendations we derived three overarching objectives and five properties for the Tool. A Data Profiling Tool, in Biomedical Informatics, is a visual, clear, usable, interactive, and smart Tool that is designed to inform clinical and biomedical researchers of Data utility and let them explore the Data, while conveniently orienting the users to the Tool's functionalities. We suggest that developing scalable Data Profiling Tools will provide new capacities to disseminate knowledge about clinical Data that will foster translational research and accelerate new discoveries.
Tobias Gaugler - One of the best experts on this subject based on the ideXlab platform.
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a Profiling Tool for detecting cache critical Data structures
European Conference on Parallel Processing, 2007Co-Authors: Tobias Gaugler, Wolfgang KarlAbstract:A poor cache behavior can significantly prohibit achieving high speedup and scalability of parallel applications. This means optimizing a program with respect to cache locality can potentially introduce considerable performance gain. As a consequence, programmers usually perform cache locality optimization for acquiring the expected performance of their applications. Within this work, we developed a Data Profiling Tool dprof with the goal of supporting the users in this task by allowing them to detect the optimization targets in their programs. In contrast to similar Tools which mostly focus on code regions, we address Data structures because they are the direct objects that programmers have to work with. Based on the Performance Monitoring Unit (PMU) provided by modern processors, dprof is capable of finding cache-critical variables, arrays, or even a segment of an array. It can also locate theses access hotspots to the most concrete position such as individual functions and code lines. This feature allows the user to apply dprof for efficient cache optimization.
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Euro-Par - A Profiling Tool for detecting cache-critical Data structures
Euro-Par 2007 Parallel Processing, 2007Co-Authors: Tobias Gaugler, Wolfgang KarlAbstract:A poor cache behavior can significantly prohibit achieving high speedup and scalability of parallel applications. This means optimizing a program with respect to cache locality can potentially introduce considerable performance gain. As a consequence, programmers usually perform cache locality optimization for acquiring the expected performance of their applications. Within this work, we developed a Data Profiling Tool dprof with the goal of supporting the users in this task by allowing them to detect the optimization targets in their programs. In contrast to similar Tools which mostly focus on code regions, we address Data structures because they are the direct objects that programmers have to work with. Based on the Performance Monitoring Unit (PMU) provided by modern processors, dprof is capable of finding cache-critical variables, arrays, or even a segment of an array. It can also locate theses access hotspots to the most concrete position such as individual functions and code lines. This feature allows the user to apply dprof for efficient cache optimization.
Hossein Estiri - One of the best experts on this subject based on the ideXlab platform.
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applying a participatory design approach to define objectives and properties of a Data Profiling Tool for electronic health Data
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2016Co-Authors: Hossein Estiri, Terri Lovins, Nader Afzalan, Kari A StephensAbstract:: We applied a participatory design approach to define the objectives, characteristics, and features of a "Data Profiling" Tool for primary care Electronic Health Data (EHD). Through three participatory design workshops, we collected input from potential Tool users who had experience working with EHD. We present 15 recommended features and characteristics for the Data Profiling Tool. From these recommendations we derived three overarching objectives and five properties for the Tool. A Data Profiling Tool, in Biomedical Informatics, is a visual, clear, usable, interactive, and smart Tool that is designed to inform clinical and biomedical researchers of Data utility and let them explore the Data, while conveniently orienting the users to the Tool's functionalities. We suggest that developing scalable Data Profiling Tools will provide new capacities to disseminate knowledge about clinical Data that will foster translational research and accelerate new discoveries.
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CRI - Applying a Participatory Design Approach to Define Objectives and Properties of a "Data Profiling" Tool for Electronic Health Data.
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2016Co-Authors: Hossein Estiri, Terri Lovins, Nader Afzalan, Kari A StephensAbstract:: We applied a participatory design approach to define the objectives, characteristics, and features of a "Data Profiling" Tool for primary care Electronic Health Data (EHD). Through three participatory design workshops, we collected input from potential Tool users who had experience working with EHD. We present 15 recommended features and characteristics for the Data Profiling Tool. From these recommendations we derived three overarching objectives and five properties for the Tool. A Data Profiling Tool, in Biomedical Informatics, is a visual, clear, usable, interactive, and smart Tool that is designed to inform clinical and biomedical researchers of Data utility and let them explore the Data, while conveniently orienting the users to the Tool's functionalities. We suggest that developing scalable Data Profiling Tools will provide new capacities to disseminate knowledge about clinical Data that will foster translational research and accelerate new discoveries.
Nader Afzalan - One of the best experts on this subject based on the ideXlab platform.
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applying a participatory design approach to define objectives and properties of a Data Profiling Tool for electronic health Data
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2016Co-Authors: Hossein Estiri, Terri Lovins, Nader Afzalan, Kari A StephensAbstract:: We applied a participatory design approach to define the objectives, characteristics, and features of a "Data Profiling" Tool for primary care Electronic Health Data (EHD). Through three participatory design workshops, we collected input from potential Tool users who had experience working with EHD. We present 15 recommended features and characteristics for the Data Profiling Tool. From these recommendations we derived three overarching objectives and five properties for the Tool. A Data Profiling Tool, in Biomedical Informatics, is a visual, clear, usable, interactive, and smart Tool that is designed to inform clinical and biomedical researchers of Data utility and let them explore the Data, while conveniently orienting the users to the Tool's functionalities. We suggest that developing scalable Data Profiling Tools will provide new capacities to disseminate knowledge about clinical Data that will foster translational research and accelerate new discoveries.
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CRI - Applying a Participatory Design Approach to Define Objectives and Properties of a "Data Profiling" Tool for Electronic Health Data.
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2016Co-Authors: Hossein Estiri, Terri Lovins, Nader Afzalan, Kari A StephensAbstract:: We applied a participatory design approach to define the objectives, characteristics, and features of a "Data Profiling" Tool for primary care Electronic Health Data (EHD). Through three participatory design workshops, we collected input from potential Tool users who had experience working with EHD. We present 15 recommended features and characteristics for the Data Profiling Tool. From these recommendations we derived three overarching objectives and five properties for the Tool. A Data Profiling Tool, in Biomedical Informatics, is a visual, clear, usable, interactive, and smart Tool that is designed to inform clinical and biomedical researchers of Data utility and let them explore the Data, while conveniently orienting the users to the Tool's functionalities. We suggest that developing scalable Data Profiling Tools will provide new capacities to disseminate knowledge about clinical Data that will foster translational research and accelerate new discoveries.