Architectural Configuration - Explore the Science & Experts | ideXlab

Scan Science and Technology

Contact Leading Edge Experts & Companies

Architectural Configuration

The Experts below are selected from a list of 276 Experts worldwide ranked by ideXlab platform

Mairtin. O'droma – 1st expert on this subject based on the ideXlab platform

  • IEEE Conf. on Intelligent Systems – A service recommendation model for the Ubiquitous Consumer Wireless World
    2016 IEEE 8th International Conference on Intelligent Systems (IS), 2016
    Co-Authors: Haiyang Zhang, Ivan Ganchev, Nikola S. Nikolov, Mairtin. O'droma

    Abstract:

    This paper describes the general service recommendation process matched to the telecommunication service delivery characteristics of the Ubiquitous Consumer Wireless World (UCWW). The goal is to provide consumers with the ‘best’ service instances that match their dynamic, contextualized and personalized requirements and expectations, thereby aligning their usage of mobile services to the always best connected and best served (ABC&S) paradigm. A four-tiered Architectural Configuration of the UCWW service recommendation framework is proposed along with a suitable service recommendation model. Specific and generic smart-city application examples are outlined. Other relevant social impact of the proposed approach is highlighted at the conclusion of the paper.

  • A service recommendation model for the Ubiquitous Consumer Wireless World
    2016 IEEE 8th International Conference on Intelligent Systems (IS), 2016
    Co-Authors: Haiyang Zhang, Ivan Ganchev, Nikola S. Nikolov, Mairtin. O'droma

    Abstract:

    This paper describes the general service recommendation process matched to the telecommunication service delivery characteristics of the Ubiquitous Consumer Wireless World (UCWW). The goal is to provide consumers with the `best’ service instances that match their dynamic, contextualized and personalized requirements and expectations, thereby aligning their usage of mobile services to the always best connected and best served (ABC&S) paradigm. A four-tiered Architectural Configuration of the UCWW service recommendation framework is proposed along with a suitable service recommendation model. Specific and generic smart-city application examples are outlined. Other relevant social impact of the proposed approach is highlighted at the conclusion of the paper.

Yunji Chen – 2nd expert on this subject based on the ideXlab platform

  • ISCA – ArchRanker: a ranking approach to design space exploration
    ACM SIGARCH Computer Architecture News, 2014
    Co-Authors: Tianshi Chen, Ke Tang, Olivier Temam, Zhiwei Xu, Zhi-hua Zhou, Yunji Chen

    Abstract:

    Architectural Design Space Exploration (DSE) is a notoriously difficult problem due to the exponentially large size of the design space and long simulation times. Previously, many studies proposed to formulate DSE as a regression problem which predicts architecture responses (e.g., time, power) of a given Architectural Configuration. Several of these techniques achieve high accuracy, though often at the cost of significant simulation time for training the regression models. We argue that the information the architect mostly needs during the DSE process is whether a given Configuration will perform better than another one in the presences of design constraints, or better than any other one seen so far, rather than precisely estimating the performance of that Configuration. Based on this observation, we propose a novel rankingbased approach to DSE where we train a model to predict which of two architecture Configurations will perform best. We show that, not only this ranking model more accurately predicts the relative merit of two architecture Configurations than an ANN-based state-of-the-art regression model, but also that it requires much fewer training simulations to achieve the same accuracy, or that it can be used for and is even better at quantifying the performance gap between two Configurations We implement the framework for training and using this model, called ArchRanker, and we evaluate it on several DSE scenarios (unicore/multicore design spaces, and both time and power performance metrics). We try to emulate as closely as possible the DSE process by creating constraint-based scenarios, or an iterative DSE process. We find that ArchRanker makes 29:68% to 54:43% fewer incorrect predictions on pairwise relative merit of Configurations (tested with 79,800 Configuration pairs) than an ANN-based regression model across all DSE scenarios considered (values averaged over all benchmarks for each scenario). We also find that, to achieve the same accuracy as ArchRanker, the ANN often requires three times more training simulations

  • ArchRanker: A ranking approach to design space exploration
    2014 ACM IEEE 41st International Symposium on Computer Architecture (ISCA), 2014
    Co-Authors: Tianshi Chen, Ke Tang, Olivier Temam, Zhiwei Xu, Zhi-hua Zhou, Yunji Chen

    Abstract:

    Architectural Design Space Exploration (DSE) is a notoriously difficult problem due to the exponentially large size of the design space and long simulation times. Previously, many studies proposed to formulate DSE as a regression problem which predicts architecture responses (e.g., time, power) of a given Architectural Configuration. Several of these techniques achieve high accuracy, though often at the cost of significant simulation time for training the regression models.We argue that the information the architect mostly needs during the DSEprocess is whether a given Configuration will perform better than another one in the presences ofdesign constraints, or better than any other one seen so far, rather than precisely estimating the performance of that Configuration. Based on this observation, we propose a novel rankingbased approach to DSE where we train a model to predict which of two architecture Configurations will perform best. We show that, not only this ranking model more accurately predicts the relative merit of two architecture Configurations than an ANN-based state-of-the-art regression model, but also that it requires much fewer training simulations to achieve the same accuracy, or that it can be used for and is even better at quantifying the performance gap between two Configurations. We implement the framework for training and using this model, called ArchRanker, and we evaluate it on several DSE scenarios (unicore/multicore design spaces, and both time and power performance metrics). We try to emulate as closely as possible the DSE process by creating constraint-based scenarios, or an iterative DSEprocess. We find that ArchRanker makes 29.68% to 54.43% fewer incorrect predictions on pairwise relative merit of Configurations (tested with 79,800 Configuration pairs) than an ANN-based regression model across all DSE scenarios considered (values averaged over all benchmarks for each scenario). We also find that, to achieve the same accuracy as ArchRanker, the ANN often requires three times more training simulations.

Haiyang Zhang – 3rd expert on this subject based on the ideXlab platform

  • IEEE Conf. on Intelligent Systems – A service recommendation model for the Ubiquitous Consumer Wireless World
    2016 IEEE 8th International Conference on Intelligent Systems (IS), 2016
    Co-Authors: Haiyang Zhang, Ivan Ganchev, Nikola S. Nikolov, Mairtin. O'droma

    Abstract:

    This paper describes the general service recommendation process matched to the telecommunication service delivery characteristics of the Ubiquitous Consumer Wireless World (UCWW). The goal is to provide consumers with the ‘best’ service instances that match their dynamic, contextualized and personalized requirements and expectations, thereby aligning their usage of mobile services to the always best connected and best served (ABC&S) paradigm. A four-tiered Architectural Configuration of the UCWW service recommendation framework is proposed along with a suitable service recommendation model. Specific and generic smart-city application examples are outlined. Other relevant social impact of the proposed approach is highlighted at the conclusion of the paper.

  • A service recommendation model for the Ubiquitous Consumer Wireless World
    2016 IEEE 8th International Conference on Intelligent Systems (IS), 2016
    Co-Authors: Haiyang Zhang, Ivan Ganchev, Nikola S. Nikolov, Mairtin. O'droma

    Abstract:

    This paper describes the general service recommendation process matched to the telecommunication service delivery characteristics of the Ubiquitous Consumer Wireless World (UCWW). The goal is to provide consumers with the `best’ service instances that match their dynamic, contextualized and personalized requirements and expectations, thereby aligning their usage of mobile services to the always best connected and best served (ABC&S) paradigm. A four-tiered Architectural Configuration of the UCWW service recommendation framework is proposed along with a suitable service recommendation model. Specific and generic smart-city application examples are outlined. Other relevant social impact of the proposed approach is highlighted at the conclusion of the paper.