摘要 :
This chapter reviews methods for the assessment and comparison of Pareto set approximations. Existing set quality measures from the literature are critically evaluated based on a number of orthogonal criteria, including invariance...
展开
This chapter reviews methods for the assessment and comparison of Pareto set approximations. Existing set quality measures from the literature are critically evaluated based on a number of orthogonal criteria, including invariance to scaling, monotonicity and computational effort. Statistical aspects of quality assessment are also considered in the chapter. Three main methods for the statistical treatment of Pareto set approximations deriving from stochastic generating methods are reviewed. The dominance ranking method is a generalization to partially-ordered sets of a standard non-parametric statistical test, allowing collections of Pareto set approximations from two or more stochastic optimizers to be directly compared statistically. The quality indicator method - the dominant method in the literature - maps each Pareto set approximation to a number, and performs statistics on the resulting distribution(s) of numbers. The attainment function method estimates the probability of attaining each goal in the objective space, and looks for significant differences between these probability density functions for different optimizers. All three methods are valid approaches to quality assessment, but give different information. We explain the scope and drawbacks of each approach and also consider some more advanced topics, including multiple testing issues, and using combinations of indicators. The chapter should be of interest to anyone concerned with generating and analysing Pareto set approximations.
收起
摘要 :
The reduced feature size of electronic systems and the demand for high performance lead to increased power densities and high chip temperatures, which in turn reduce the system reliability. Thermal-aware task allocation and schedu...
展开
The reduced feature size of electronic systems and the demand for high performance lead to increased power densities and high chip temperatures, which in turn reduce the system reliability. Thermal-aware task allocation and scheduling algorithms are promising approaches to reduce the peak temperature of multi-core systems with real-time constraints. However, as long as the worst-case chip temperature is not incorporated into system analysis, no guarantees on the performance can be given. This paper explores thermal-aware task assignment strategies for real-time applications with non-deterministic workload that are running on a multi-core system. In particular, tasks are assigned to the multi-core system so that the worst-case chip temperature is minimized and all real-time deadlines are met. Each core has its own clock domain and the static assigned frequency corresponds to the minimum operation frequency such that no real-time deadline is missed. Finally, we show that the proposed temperature minimization problem can efficiently be solved by metaheuristics.
收起
摘要 :
The reduced feature size of electronic systems and the demand for high performance lead to increased power densities and high chip temperatures, which in turn reduce the system reliability. Thermal-aware task allocation and schedu...
展开
The reduced feature size of electronic systems and the demand for high performance lead to increased power densities and high chip temperatures, which in turn reduce the system reliability. Thermal-aware task allocation and scheduling algorithms are promising approaches to reduce the peak temperature of multi-core systems with real-time constraints. However, as long as the worst-case chip temperature is not incorporated into system analysis, no guarantees on the performance can be given. This paper explores thermal-aware task assignment strategies for real-time applications with non-deterministic workload that are running on a multi-core system. In particular, tasks are assigned to the multi-core system so that the worst-case chip temperature is minimized and all real-time deadlines are met. Each core has its own clock domain and the static assigned frequency corresponds to the minimum operation frequency such that no real-time deadline is missed. Finally, we show that the proposed temperature minimization problem can efficiently be solved by metaheuristics.
收起
摘要 :
We introduce a task model for embedded systems operating on packet streams, such as network processors. This model along with a calculus meant for reasoning about packet streams allows a unified treatment of several problems arisi...
展开
We introduce a task model for embedded systems operating on packet streams, such as network processors. This model along with a calculus meant for reasoning about packet streams allows a unified treatment of several problems arising in the network packet processing domain such as packet scheduling, task scheduling and architecture/algorithm explorations in the design of network processors. The model can take into account quality of service constraints such as data throughput and deadlines associated with packets. To illustrate its potential, we provide two applications: (a) a new task scheduling algorithm for network processors to support a mix of real-time and non-real-time flows, (b) a scheme for design space exploration of network processors.
收起
摘要 :
We introduce a task model for embedded systems operating on packet streams, such as network processors. This model along with a calculus meant for reasoning about packet streams allows a unified treatment of several problems arisi...
展开
We introduce a task model for embedded systems operating on packet streams, such as network processors. This model along with a calculus meant for reasoning about packet streams allows a unified treatment of several problems arising in the network packet processing domain such as packet scheduling, task scheduling and architecture/algorithm explorations in the design of network processors. The model can take into account quality of service constraints such as data throughput and deadlines associated with packets. To illustrate its potential, we provide two applications: (a) a new task scheduling algorithm for network processors to support a mix of real-time and non-real-time flows, (b) a scheme for design space exploration of network processors.
收起
摘要 :
In this work we describe a systematic approach to power subsystem capacity planning for solar energy harvesting embedded systems, such that uninterrupted, long-term (i.e., multiple years) operation at a predefined performance leve...
展开
In this work we describe a systematic approach to power subsystem capacity planning for solar energy harvesting embedded systems, such that uninterrupted, long-term (i.e., multiple years) operation at a predefined performance level may be achieved. We propose a power subsystem capacity planning algorithm based on a modified astronomical model to approximate the harvestable energy and compute the required battery capacity for a given load and harvesting setup. The energy availability model takes as input the deployment site's latitude, the panel orientation and inclination angles, and an indication of expected meteorological and environmental conditions. We validate the model's ability to predict the harvestable energy with power measurements of a solar panel. Through simulation with 10 years of solar traces from three different geographical locations and four harvesting setups, we demonstrate that our approach achieves 100% availability at up to 53% smaller batteries when compared to the state-of-the-art.
收起
摘要 :
In this work we describe a systematic approach to power subsystem capacity planning for solar energy harvesting embedded systems, such that uninterrupted, long-term (i.e., multiple years) operation at a predefined performance leve...
展开
In this work we describe a systematic approach to power subsystem capacity planning for solar energy harvesting embedded systems, such that uninterrupted, long-term (i.e., multiple years) operation at a predefined performance level may be achieved. We propose a power subsystem capacity planning algorithm based on a modified astronomical model to approximate the harvestable energy and compute the required battery capacity for a given load and harvesting setup. The energy availability model takes as input the deployment site's latitude, the panel orientation and inclination angles, and an indication of expected meteorological and environmental conditions.We validate the model's ability to predict the harvestable energy with power measurements of a solar panel. Through simulation with 10 years of solar traces from three different geographical locations and four harvesting setups, we demonstrate that our approach achieves 100% availability at up to 53% smaller batteries when compared to the state-of-the-art.
收起
摘要 :
Emerging edge intelligence applications require the server to retrain and update deep neural networks deployed on remote edge nodes to leverage newly collected data samples. Unfortunately, it may be impossible in practice to conti...
展开
Emerging edge intelligence applications require the server to retrain and update deep neural networks deployed on remote edge nodes to leverage newly collected data samples. Unfortunately, it may be impossible in practice to continuously send fully updated weights to these edge nodes due to the highly constrained communication resource. In this paper, we propose the weight-wise deep partial updating paradigm, which smartly selects a small subset of weights to update in each server-to-edge communication round, while achieving a similar performance compared to full updating. Our method is established through analytically upper-bounding the loss difference between partial updating and full updating, and only updates the weights which make the largest contributions to the upper bound. Extensive experimental results demonstrate the efficacy of our partial updating methodology which achieves a high inference accuracy while updating a rather small number of weights.
收起
摘要 :
We study whether the executions of a time-annotated sound workflow graph (WFG) meet a given deadline when an unbounded number of resources (i.e., executing agents) is available. We present polynomialtime algorithms and NP-hardness...
展开
We study whether the executions of a time-annotated sound workflow graph (WFG) meet a given deadline when an unbounded number of resources (i.e., executing agents) is available. We present polynomialtime algorithms and NP-hardness results for different cases. In particular, we show that it can be decided in polynomial time whether some executions of a sound workflow graph meet the deadline. For acyclic sound workflow graphs, it can be decided in linear time whether some or all executions meet the deadline. Furthermore, we show that it is NP-hard to compute the expected duration of a sound workflow graph for unbounded resources, which is contrasting the earlier result that the expected duration of a workflow graph executed by a single resource can be computed in cubic time. We also propose an algorithm for computing the maximum concurrency of the workflow graph, which helps to determine the optimal number of resources needed to execute the workflow graph.
收起
摘要 :
We study whether the executions of a time-annotated sound workflow graph (WFG) meet a given deadline when an unbounded number of resources (i.e., executing agents) is available. We present polynomial-time algorithms and NP-hardnes...
展开
We study whether the executions of a time-annotated sound workflow graph (WFG) meet a given deadline when an unbounded number of resources (i.e., executing agents) is available. We present polynomial-time algorithms and NP-hardness results for different cases. In particular, we show that it can be decided in polynomial time whether some executions of a sound workflow graph meet the deadline. For acyclic sound workflow graphs, it can be decided in linear time whether some or all executions meet the deadline. Furthermore, we show that it is NP-hard to compute the expected duration of a sound workflow graph for unbounded resources, which is contrasting the earlier result that the expected duration of a workflow graph executed by a single resource can be computed in cubic time. We also propose an algorithm for computing the maximum concurrency of the workflow graph, which helps to determine the optimal number of resources needed to execute the workflow graph.
收起
原文获取