The Experts below are selected from a list of 29622 Experts worldwide ranked by ideXlab platform

Qingxu Deng - One of the best experts on this subject based on the ideXlab platform.

  • minimizing multi resource energy for real time systems with Discrete Operation modes
    Euromicro Conference on Real-Time Systems, 2010
    Co-Authors: Fanxin Kong, Yiqun Wang, Qingxu Deng
    Abstract:

    Energy conservation is an important issue in the design of embedded systems. Dynamic Voltage Scaling (DVS) and Dynamic Power Management (DPM) are two widely used techniques for saving energy in such systems. In this paper, we address the problem of minimizing multi-resource energy consumption concerning both CPU and devices. A system is assumed to contain a fixed number of real-time tasks scheduled to run on a DVS-enabled processor, and a fixed number of off-chip devices used by the tasks during their executions. We will study the non-trivial time and energy overhead of device state transitions between active and sleep states. Our goal is to find optimal schedules providing not only the execution order and CPU frequencies of tasks, but also the time points for device state transitions. We adopt the frame-based real-time task model, and develop optimization algorithms based on 0-1 Integer Non-Linear Programming (0-1 INLP) for different system configurations. Simulation results indicate that our approach can significantly outperform existing techniques in terms of energy savings.

Fanxin Kong - One of the best experts on this subject based on the ideXlab platform.

  • minimizing multi resource energy for real time systems with Discrete Operation modes
    Euromicro Conference on Real-Time Systems, 2010
    Co-Authors: Fanxin Kong, Yiqun Wang, Qingxu Deng
    Abstract:

    Energy conservation is an important issue in the design of embedded systems. Dynamic Voltage Scaling (DVS) and Dynamic Power Management (DPM) are two widely used techniques for saving energy in such systems. In this paper, we address the problem of minimizing multi-resource energy consumption concerning both CPU and devices. A system is assumed to contain a fixed number of real-time tasks scheduled to run on a DVS-enabled processor, and a fixed number of off-chip devices used by the tasks during their executions. We will study the non-trivial time and energy overhead of device state transitions between active and sleep states. Our goal is to find optimal schedules providing not only the execution order and CPU frequencies of tasks, but also the time points for device state transitions. We adopt the frame-based real-time task model, and develop optimization algorithms based on 0-1 Integer Non-Linear Programming (0-1 INLP) for different system configurations. Simulation results indicate that our approach can significantly outperform existing techniques in terms of energy savings.

Yiqun Wang - One of the best experts on this subject based on the ideXlab platform.

  • minimizing multi resource energy for real time systems with Discrete Operation modes
    Euromicro Conference on Real-Time Systems, 2010
    Co-Authors: Fanxin Kong, Yiqun Wang, Qingxu Deng
    Abstract:

    Energy conservation is an important issue in the design of embedded systems. Dynamic Voltage Scaling (DVS) and Dynamic Power Management (DPM) are two widely used techniques for saving energy in such systems. In this paper, we address the problem of minimizing multi-resource energy consumption concerning both CPU and devices. A system is assumed to contain a fixed number of real-time tasks scheduled to run on a DVS-enabled processor, and a fixed number of off-chip devices used by the tasks during their executions. We will study the non-trivial time and energy overhead of device state transitions between active and sleep states. Our goal is to find optimal schedules providing not only the execution order and CPU frequencies of tasks, but also the time points for device state transitions. We adopt the frame-based real-time task model, and develop optimization algorithms based on 0-1 Integer Non-Linear Programming (0-1 INLP) for different system configurations. Simulation results indicate that our approach can significantly outperform existing techniques in terms of energy savings.

M. M. Faruque Hasan - One of the best experts on this subject based on the ideXlab platform.

  • Optimal synthesis of periodic sorption enhanced reaction processes with application to hydrogen production
    Computers & Chemical Engineering, 2018
    Co-Authors: Akhil Arora, Ishan Bajaj, Shachit S. Iyer, M. M. Faruque Hasan
    Abstract:

    Abstract A systematic design and synthesis framework for multi-step, multi-mode and periodic sorption-enhanced reaction processes (SERP) is presented. The formulated nonlinear algebraic and partial differential equation (NAPDE)-based model simultaneously identifies optimal SERP cycle configurations, design specifications and operating conditions. Key modeling contributions include a generalized boundary-condition formulation and a representation that enables the selection of Discrete Operation modes and flow directions using continuous pressure variables. A simulation-based constrained grey-box optimization strategy is employed to obtain optimal cycles and design parameters. The framework has been used for designing two SERP systems, namely sorption-enhanced steam methane reforming (SE-SMR) and sorption-enhanced water gas shift reaction (SE-WGSR), for maximizing hydrogen productivity and minimizing hydrogen-production cost. Specifically, a cyclic SE-SMR process is designed that obtains 95% pure hydrogen from natural gas with 35% higher productivity and 10.86% lower cost compared to existing small-scale, distributed systems. The developed synthesis framework can also be applied for other applications.

Majid Sarrafzadeh - One of the best experts on this subject based on the ideXlab platform.

  • energy minimization for real time systems with non convex and Discrete Operation modes
    Design Automation and Test in Europe, 2009
    Co-Authors: Foad Dabiri, Alireza Vahdatpour, Miodrag Potkonjak, Majid Sarrafzadeh
    Abstract:

    We present an optimal methodology for dynamic voltage scheduling problem in the presence of realistic assumption such as leakage-power and intra-task overheads. Our contribution is an optimal algorithm for energy minimization that concurrently assumes the presence of (1) non-convex energy-speed models as opposed to previously studied convex models, (2) Discrete set of Operational modes (voltages) and (3) intra-task energy and delay overhead. We tested our algorithm on MediaBench and task sets used in previous papers. Our simulation results show an average of 22% improvement in energy reduction in comparison with optimal algorithms for convex models without switching overhead and on average of 24% with consideration for energy and delay overheads. This analysis lays the groundwork for improving functionality in CAD design through non-convex techniques for Discrete models.