An FFT Performance Model for Optimizing General-Purpose Processor Architecture

General-purpose processor (GPP) is an important platform for fast Fourier transform (FFT),due to its flexibility,reliability and practicality.FFT is a representative application intensive in both computation and memory access,optimizing the FFT performance of a GPP also benefits the performances of many other applications.To facilitate the analysis of FFT,this paper proposes a theoretical model of the FFT processing.The model gives out a tight lower bound of the runtime of FFT on a GPP,and guides the architecture optimization for GPP as well.Based on the model,two theorems on optimization of architecture parameters are deduced,which refer to the lower bounds of register number and memory bandwidth.Experimental results on different processor architectures (including Intel Core i7 and Godson-3B) validate the performance model.The above investigations were adopted in the development of Godson-3B,which is an industrial GPP.The optimization techniques deduced from our performance model improve the FFT performance by about 40%,while incurring only 0.8% additional area cost.Consequently,Godson-3B solves the 1024-point single-precision complex FFT in 0.368 μs with about 40 Watt power consumption,and has the highest performance-per-watt in complex FFT among processors as far as we know.This work could benefit optimization of other GPPs as well.     

基于行为监控的自适应动态信任度测模型

大规模分布式系统中的动态信任关系模型本质上是最复杂的社会关系之一,涉及假设、期望、行为和环境等多种因子,很难准确的定量表示和预测.将粗糙集理论和信息熵理论结合起来,应用于开放环境下动态构建基于行为数据监控与分析的信任关系度测(度量与预测)模型.该方法直接从分析传感器监测到的动态数据入手,针对影响信任的多个度测指标进行自适应的数据挖掘与知识发现,从而改变了传统的信任关系建模思路,跳出了传统信任关系建模过程中各种主观假设的束缚,并克服了传统模型对多维数据处理能力不足的问题.实验结果表明,与已有模型相比,新模型能够快速准确地实现开放分布式环境下实体的可信性判别,而且具有良好的行为数据规模的扩展能力.     

STBC系统在非同分布Nakagami信道下的一种快速性能评估算法

针对非同分布的Nakagami信道,基于矩生成函数MGF(Moment Generation Function)的分析方法,提出正交空时分组码系统STBC(Space-Time Block Coding)的一种快速性能评估算法,不需要涉及超几何函数积分运算,可在中高信噪比时,快速准确地估计STBC系统的符号错误概率性能。在平坦瑞利衰落信道下的计算机仿真表明,该算法与已有的STBC系统的近似估计算法相比,具有较优的性能。     

一种基于信漏噪比的多用户优化预编码迭代算法

提出了一种新的基于信漏噪比的多用户优化预编码迭代算法。在深入分析和发掘系统设计中预编码矩阵和接收合并矩阵之间的内在联系的基础上,利用新提出的迭代算法解决其本质上存在的嵌套关系,从而实现系统综合性能优化。数字仿真从平均误码率与系统和速率两个层面对新算法进行验证。结果表明,新方案相较于原始基于信漏噪比的方案以及过去提出的其他经典方案具有明显性能优势。因其迭代算法收敛迅速,因此具有工程实践价值。     

A novel differential evolution algorithm for bi-criteria no-wait flow shop scheduling problems

This paper presents a novel discrete differential evolution (DDE) algorithm for solving the no-wait flow shop scheduling problems with makespan and maximum tardiness criteria. First, the individuals in the DDE algorithm are represented as discrete job permutations, and new mutation and crossover operators are developed based on this representation. Second, an elaborate one-to-one selection operator is designed by taking into account the domination status of a trial individual with its counterpart target individual as well as an archive set of the non-dominated solutions found so far. Third, a simple but effective local search algorithm is developed to incorporate into the DDE algorithm to stress the balance between global exploration and local exploitation. In addition, to improve the efficiency of the scheduling algorithm, several speed-up methods are devised to evaluate a job permutation and its whole insert neighborhood as well as to decide the domination status of a solution with the archive set. Computational simulation results based on the well-known benchmarks and statistical performance comparisons are provided. It is shown that the proposed DDE algorithm is superior to a recently published hybrid differential evolution (HDE) algorithm [Qian B, Wang L, Huang DX, Wang WL, Wang X. An effective hybrid DE-based algorithm for multi-objective flow shop scheduling with limited buffers. Computers & Operations Research 2009;36(1):209–33] and the well-known multi-objective genetic local search algorithm (IMMOGLS2) [Ishibuchi H, Yoshida I, Murata T. Balance between genetic search and local search in memetic algorithms for multiobjective permutation flowshop scheduling. IEEE Transactions on Evolutionary Computation 2003;7(2):204–23] in terms of searching quality, diversity level, robustness and efficiency. Moreover, the effectiveness of incorporating the local search into the DDE algorithm is also investigated.     

An e-commerce performance assessment model: Its development and an initial test on e-commerce applications in the retail sector of China

We developed a performance assessment model for e-commerce; it included indicators, indicator weights, and evaluation methods. The model has seven methods of assessing e-commerce performance and uses four criteria to compare and select the appropriate one for a particular situation. This model was tested in the retail sector of China. According to the data collected from 70 Chinese retailers, 16 indicators of e-commerce performance consisted of four constructs: marketing and sales, customer service, supply chain efficiency, and financial performance. The indicators for those constructs provide a comprehensive measurement of performance. Then weights were assigned for each indicator using a majority aggregation method. Comparison of the results from seven evaluation methods showed that discordance analysis and simple additive weighting were the best evaluation methods for the enterprises we had sampled.     

Multi-sensor calibration through iterative registration and fusion

In this paper, a new multi-sensor calibration approach, called iterative registration and fusion (IRF), is presented. The key idea of this approach is to use surfaces reconstructed from multiple point clouds to enhance the registration accuracy and robustness. It calibrates the relative position and orientation of the spatial coordinate systems among multiple sensors by iteratively registering the discrete 3D sensor data against an evolving reconstructed B-spline surface, which results from the Kalman filter-based multi-sensor data fusion. Upon each registration, the sensor data gets closer to the surface. Upon fusing the newly registered sensor data with the surface, the updated surface represents the sensor data more accurately. We prove that such an iterative registration and fusion process is guaranteed to converge. We further demonstrate in experiments that the IRF can result in more accurate and more stable calibration than many classical point cloud registration methods.     

Deadline division-based heuristic for cost optimization in workflow scheduling

Cost optimization for workflow applications described by Directed Acyclic Graph (DAG) with deadline constraints is a fundamental and intractable problem on Grids. In this paper, an effective and efficient heuristic called DET (Deadline Early Tree) is proposed. An early feasible schedule for a workflow application is defined as an Early Tree. According to the Early Tree, all tasks are grouped and the Critical Path is given. For critical activities, the optimal cost solution under the deadline constraint can be obtained by a dynamic programming strategy, and the whole deadline is segmented into time windows according to the slack time float. For non-critical activities, an iterative procedure is proposed to maximize time windows while maintaining the precedence constraints among activities. In terms of the time window allocations, a local optimization method is developed to minimize execution costs. The two local cost optimization methods can lead to a global near-optimal solution. Experimental results show that DET outperforms two other recent leveling algorithms. Moreover, the deadline division strategy adopted by DET can be applied to all feasible deadlines.     

Performance-First Control for Discrete-Time LQG Problems

Performance-first control for discrete-time LQG is considered in this paper to minimize the probability that the performance index exceeds a preselected threshold via constructing a closed-loop feedback control law. This problem can be converted into a mean-variance control problem which can be solved by developing a nested form of the variance and using polynomial optimization as a solution scheme.     

A MEMS affinity glucose sensor using a biocompatible glucose-responsive polymer

We present a MEMS affinity sensor that can potentially allow long-term continuous monitoring of glucose in subcutaneous tissue for diabetes management. The sensing principle is based on detection of viscosity changes due to affinity binding between glucose and poly(acrylamide-ran-3-acrylamidophenylboronic acid) (PAA-ran-PAAPBA), a biocompatible, glucose-specific polymer. The device uses a magnetically driven vibrating microcantilever as a sensing element, which is fabricated from Parylene and situated in a microchamber. A solution of PAA-ran-PAAPBA fills the microchamber, which is separated from the surroundings by a semi-permeable membrane. Glucose permeates through the membrane and binds reversibly to the phenylboronic acid moiety of the polymer. This results in a viscosity change of the sensing solution, which is obtained by measuring the damped cantilever vibration using an optical lever setup, allowing determination of the glucose concentration. Experimental results demonstrate that the device is capable of detecting glucose at physiologically relevant concentrations from 27 mg/dL to 324 mg/dL. The glucose response time constant of the sensor is approximately 3 min, which can be further improved with device design optimization. Excellent reversibility and stability are observed in sensor responses, as highly desired for long-term, stable continuous glucose monitoring.