An efficient bi-objective optimization framework for statistical chip-level yield analysis under parameter variations

With shrinking technology, the increase in variability of process, voltage, and temperature (PVT) parameters significantly impacts the yield analysis and optimization for chip designs. Previous yield estimation algorithms have been limited to predicting either timing or power yield. However, neglecting the correlation between power and delay will result in significant yield loss. Most of these approaches also suffer from high computational complexity and long runtime. We suggest a novel bi-objective optimization framework based on Chebyshev affine arithmetic (CAA) and the adaptive weighted sum (AWS) method. Both power and timing yield are set as objective functions in this framework. The two objectives are optimized simultaneously to maintain the correlation between them. The proposed method first predicts the guaranteed probability bounds for leakage and delay distributions under the assumption of arbitrary correlations. Then a power-delay bi-objective optimization model is formulated by computation of cumulative distribution function (CDF) bounds. Finally, the AWS method is applied for power-delay optimization to generate a well-distributed set of Pareto-optimal solutions. Experimental results on ISCAS benchmark circuits show that the proposed bi-objective framework is capable of providing sufficient trade-off information between power and timing yield.     

A virtual service placement approach based on improved quantum genetic algorithm

Despite the critical role that middleboxes play in introducing new network functionality, management and innovation of them are still severe challenges for network operators, since traditional middleboxes based on hardware lack service flexibility and scalability. Recently, though new networking technologies, such as network function virtualization (NFV) and software-defined networking (SDN), are considered as very promising drivers to design cost-efficient middlebox service architectures, how to guarantee transmission efficiency has drawn little attention under the condition of adding virtual service process for traffic. Therefore, we focus on the service deployment problem to reduce the transport delay in the network with a combination of NFV and SDN. First, a framework is designed for service placement decision, and an integer linear programming model is proposed to resolve the service placement and minimize the network transport delay. Then a heuristic solution is designed based on the improved quantum genetic algorithm. Experimental results show that our proposed method can calculate automatically the optimal placement schemes. Our scheme can achieve lower overall transport delay for a network compared with other schemes and reduce 30% of the average traffic transport delay compared with the random placement scheme.     

Adaptive fuzzy integral sliding mode velocity control for the cutting system of a trench cutter

This paper presents a velocity controller for the cutting system of a trench cutter (TC). The cutting velocity of a cutting system is affected by the unknown load characteristics of rock and soil. In addition, geological conditions vary with time. Due to the complex load characteristics of rock and soil, the cutting load torque of a cutter is related to the geological conditions and the feeding velocity of the cutter. Moreover, a cutter’s dynamic model is subjected to uncertainties with unknown effects on its function. In this study, to deal with the particular characteristics of a cutting system, a novel adaptive fuzzy integral sliding mode control (AFISMC) is designed for controlling cutting velocity. The model combines the robust characteristics of an integral sliding mode controller with the adaptive adjusting characteristics of an adaptive fuzzy controller. The AFISMC cutting velocity controller is synthesized using the backstepping technique. The stability of the whole system including the fuzzy inference system, integral sliding mode controller, and the cutting system is proven using the Lyapunov theory. Experiments have been conducted on a TC test bench with the AFISMC under different operating conditions. The experimental results demonstrate that the proposed AFISMC cutting velocity controller gives a superior and robust velocity tracking performance.     

基于状态指标的更新决策方法研究

针对设备在实际运行和执行任务时经常涉及到维修、更新报废等管理活动缺乏定量模型支撑的问题,提出了利用典型部件的预测寿命和非典型部件的历史寿命对设备系统级的健康状态进行综合评估的方法,建立了一种以状态指标为决策序列的动态规划更新决策方法;该方法能综合考虑维修费用和更新费用,确定最优更新决策,降低保障费用,有效地提高了设备的经济效益;最后经过案例分析证明了该方法的有效性,对于提高设备的保障能力和经济效益提供了理论支撑和方法指导.     

高可扩展可容错的无网格/粒子程序petaPar及其测试

petaPar 粒子模拟程序面向千万亿次级计算,在统一框架下实现两种广受关注的粒子模拟算法：光滑粒子流体动力学（Smoothed Particle Hydrodynamics,SPH）和物质点法（Material Point Method,MPM)。代码支持多种材料模型、强度模型和失效模型,适合模拟大变形、高应变率和流固耦合问题。支持纯 MPI 和 MPI+X 混合两种并行模型。系统具有可容错性,支持无人值守变进程重启。在Titan 上测试表明,petaPar 可线性扩展到 26 万 CPU 核,SPH 和 MPM 算法并行效率相对 8 192 核分别为 87% 和 90%。     

基于数据库语言的网站后台编程的技术分析

数据库系统在整个动态Web站点中具有重要的支撑作用,网站的数据库系统主要伴随网站的后台而存在。本文主要是针对数据库在网站中的关键作用进行分析,探讨数据库对网站后台编程的影响因素,从而作出相关的编程技术分析,并以数据库设计为出发点,提出网站后台编程的相关优化建议。     

File-aware P2P traffic classification: An aid to network management

As P2P dominates Internet traffic in recent years, ISPs are striving to balance between providing the basic networking services for P2P users and properly managing network bandwidth usage. That is, ISPs are required to provide proper bandwidth for each P2P user to get every file to fulfill their provision for communications, while they have to control bandwidth consumption for efficient usage. However, current P2P traffic management strategies are unable to satisfy both requirements. In this paper, our goal is to design a simple and effective scheme for ISPs to moderate the tradeoff. It is achieved by proposing a file-aware P2P traffic classification method that can identify files and the associated flows. The file-level information can lead to more efficient and flexible management strategies on a per-file basis. We offer two alternatives: constraining the per-file bandwidth consumption and the number of per-file concurrent flows. Finally, a real-life trace is measured using our file-aware method from the perspectives of peers and files. The results indicate that ISPs can gain enough opportunities to flexibly choose proper traffic manage parameters according to actual demands.