面向访问模式的多核末级Cache优化方法

多核处理器架构已经成为当前处理器的主流趋势,应用程序中访问模式的多样性给多核处理器的末级Cache带来了许多挑战。提出了访问模式的多核末级Cache优化方法,它包含"可配置的共享私有Cache划分"、"可配置的旁路Cache策略"和"优先权替换策略"三个协同递进的层次。通过使用该方法,程序员能够灵活地改变末级Cache执行行为,从而高效地适应应用程序访问模式的变化。实验结果表明,提出的方法能够显著降低末级Cache的缺失率,进而提高系统的整体性能。     

Screening multi-dimensional heterogeneous populations for infectious diseases under scarce testing resources,with application to COVID-19

Testing provides essential information for managing infectious disease outbreaks, such as the COVID-19 pandemic. When testing resources are scarce, an important managerial decision is who to test. This decision is compounded by the fact that potential testing subjects are heterogeneous in multiple dimensions that are important to consider, including their likelihood of being disease-positive, and how much potential harm would be averted through testing and the subsequent interventions. To increase testing coverage, pooled testing can be utilized, but this comes at a cost of increased false-negatives when the test is imperfect. Then, the decision problem is to partition the heterogeneous testing population into three mutually exclusive sets: those to be individually tested, those to be pool tested, and those not to be tested. Additionally, the subjects to be pool tested must be further partitioned into testing pools, potentially containing different numbers of subjects. The objectives include the minimization of harm (through detection and mitigation) or maximization of testing coverage. We develop data-driven optimization models and algorithms to design pooled testing strategies, and show, via a COVID-19 contact tracing case study, that the proposed testing strategies can substantially outperform the current practice used for COVID-19 contact tracing (individually testing those contacts with symptoms). Our results demonstrate the substantial benefits of optimizing the testing design, while considering the multiple dimensions of population heterogeneity and the limited testing capacity.     

基于可靠度的管道支架结构设计表达式研究

运用可靠度的相关理论及方法,针对管道支架结构的实际情况,考虑了钢筋混凝土结构支架和钢结构支架两种形式的9种常用代表性结构构件,确定了管道支架结构的最优荷栽分项系数以及管道支架结构设计表达式。     

商贸城消防安全管理存在问题及对策

针对贵州省商贸城商业用房的消防安全管理工作现状的分析,提出以＂防火墙＂工作建设为契机,加大对商贸城商业用房的消防安全管理力度,使此项重而难的工作逐步走向良好轨道,避免出现重大火灾事故,为构建和谐社会奠定良好基础。     

地下空间分区与疏散设计解析

地下空间的利用率越来越高,增加了对空间的使用效率,拓展了人们的生活休闲空间。虽然相关规范对地下空间的安全性做了一些规定,但比较零散,各种数据还不统一,加之受地下空间自身条件所限,设计上很难达到实用与消防安全方面的和谐统一,笔者根据工作实际,对地下空间的分区和疏散问题进行分析和归纳,提出了对民用地下空间防火分区和安全疏散消防设计要点的理解。     

关于《消防法》实施以来的几点思考

2009年《消防法》实施以来,消防工作得到了长足的发展,但也反映出一定的问题。分析了《消防法》实施几年来在执法主体力量、概念界定、法律术语等方面中存在的问题,认为应通过合理考虑执法力量状况、理性看待法律条文本身、主动形成执法合作意识等措施,更好地发挥《消防法》在消防监督管理中的重要作用。     

虚拟PDM环境下基于特征增长的协同设计

协同设计目前已经成为解决复杂产品设计问题的关键技术之一.在分析了现有协同设计问题的基础上,提出通过构建虚拟PDM(VPDM,Virtual PDM),应用交换特征增长数据的方法,来解决企业间异构PDM、CAD应用系统的协同设计问题.给出了虚拟PDM的定义,并介绍了基于虚拟PDM进行协同设计的基本原理.建立了基于虚拟PD...     

LRE试车数据挖掘中基于最大散度差的模糊聚类分析方法

在对液体火箭发动机试车数据进行聚类分析时,为解决故障数据样本与正常样本类间差异不大的问题,引入最大散度差准则,提出基于最大散度差的聚类算法MSD-CA.该算法以散度度量样本间的相似性,使样本的类内散度最小化和类间散度最大化同时进行.在此基础上,应用模糊理论对最大散度差准则进行模糊化,提出基于最大散度差的模糊聚类算法MS...     

The knapsack problem with a minimum filling constraint

We study a knapsack problem with an additional minimum filling constraint, such that the total weight of selected items cannot be less than a given threshold. The problem has several applications in shipping, e‐commerce, and transportation service procurement. When the threshold equals the knapsack capacity, even finding a feasible solution to the problem is NP‐hard. Therefore, we consider the case when the ratio α of threshold to capacity is less than 1. For this case, we develop an approximation scheme that returns a feasible solution with a total profit not less than (1 ‐ ε) times the total profit of an optimal solution for any ε > 0, and with a running time polynomial in the number of items, 1/ε, and 1/(1‐α). © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

Bounded flexibility in days‐on and days‐off scheduling

This article presents a flexible days‐on and days‐off scheduling problem and develops an exact branch and price (B&P) algorithm to find solutions. The main objective is to minimize the size of the total workforce required to cover time‐varying demand over a planning horizon that may extend up to 12 weeks. A new aspect of the problem is the general restriction that the number of consecutive days on and the number of consecutive days off must each fall within a predefined range. Moreover, the total assignment of working days in the planning horizon cannot exceed some maximum value. In the B&P framework, the master problem is stated as a set covering‐type problem whose columns are generated iteratively by solving one of three different subproblems. The first is an implicit model, the second is a resource constrained shortest path problem, and the third is a dynamic program. Computational experiments using both real‐word and randomly generated data show that workforce reductions up to 66% are possible with highly flexible days‐on and days‐off patterns. When evaluating the performance of the three subproblems, it was found that each yielded equivalent solutions but the dynamic program proved to be significantly more efficient. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 60: 678–701, 2013