Dynamic Predication of Indirect Jumps

Indirect jumps are used to implement increasingly common programming language constructs such as virtual function calls, switch-case statements, jump tables, and interface calls. Unfortunately, the prediction accuracy of indirect jumps has remained low because many indirect jumps have multiple targets that are difficult to predict even with specialized hardware. This paper proposes a new way of handling hard-to-predict indirect jumps: dynamically predicating them. The compiler identifies indirect jumps that are suitable for predication along with their control-flow merge (CFM) points. The microarchitecture predicates the instructions between different targets of the jump and its CFM point if the jump turns out to be hardto-predict at run time. We describe the new indirect jump predication architecture, provide code examples showing why it could reduce the performance impact of jumps, derive an analytical cost-benefit model for deciding which jumps and targets to predicate, and present preliminary evaluation results.     

二进制翻译中解析多目标分支语句的图匹配方法

二进制翻译技术现已成为实现软件移植的重要手段.在二进制翻译系统中,如何有效地挖掘程序的代码并对其进行高效翻译是影响系统性能的关键,而二进制代码中间接跳转语句的存在,使得静态时难以得到它的跳转目标,影响了代码的发掘率和最终的翻译效果.在通常的应用程序中,间接跳转指令经常用来实现多目标分支语义,分支目标存放在跳转表中.提出了一种解析多目标分支语句及其跳转表的方法,能够挖掘出间接跳转的目标,进而对其进行有效翻译并提高二进制翻译系统的性能.该方法提出使用语义图来对预期语义进行刻画和表达.语义图能够对考察的指令序列进行语义提取,识别出与预期语义相匹配的指令流,还可以应对编译器在不同优化选项下生成的指令,并能有效滤除不相关指令带来的干扰.实验结果表明,对于SPEC CINT2000中的部分测试用例,代码翻译的覆盖率可以提高9.85%～22.13%,相应带来的性能提升可达到8.30%～17.71%,而使用的算法时间复杂度仅为O(1).     

Wish Branches: Enabling Adaptive and Aggressive Predicated Execution

The goal of wish branches is to use predicated execution for hard-to-predict dynamic branches, and branch prediction for easy-to-predict dynamic branches, thereby obtaining the best of both worlds. Wish loops, one class of wish branches, use predication to reduce the misprediction penalty for hard-to-predict backward (loop) branches.     

一种隐式流敏感的木马间谍程序检测方法

提出了一种隐式流敏感的木马间谍程序检测方法.采用静态分析方式,具有更高的代码覆盖率;同时结合了数据流分析对间接跳转的目标进行计算;并且基于分支条件的操作语义,使用了针对木马间谍程序检测的改进的污点标记规则.应用该方法分析了103个真实的恶意代码样本和7个合法软件,并与现有方法进行了对比.实验结果表明,在进行木马间谍软件检测时该方法比显示流敏感的方法具有较低的漏报率,并且能够有效地发现需要特定条件触发的信息窃取行为.同时,该方法能够区分木马间谍程序和合法软件中的隐式流,显著消减对合法软件中的隐式流跟踪.     

基于控制流的静态反汇编算法研究

该文在分析各种类型的指令对程序静态流程影响的基础上,提出了一种基于程序流程遍历图的静态反汇编算法,并给出了一种基于统计学的代码间隙填充技术对由间接跳转和间接调用所引用的代码区进行反汇编的方法。     

Testing for jumps in the EGARCH process

This paper considers testing for jumps in the exponential GARCH (EGARCH) models with Gaussian and Student-t innovations. The Wald and log likelihood ratio tests contain a nuisance parameter unidentified under the null hypothesis of no jumps, and hence are unavailable for this problem, because jump probability and variance of jumps in the test statistic cannot be estimated under the null hypothesis of no jumps. It is shown that the nuisance parameter is cancelled out in the Lagrange multiplier (LM) test statistic, and hence that the test is nuisance parameter-free. The one-sided test is also proposed using the nonnegative constraint on jump variance. The actual size and power of the tests are examined in a Monte Carlo experiment. The test is applied to daily returns of S&P 500 as an illustrative example.     

An embedding approach for the design of state‐feedback tracking controllers for references with jumps

We study the problem of designing state‐feedback controllers to track time‐varying state trajectories that may exhibit jumps. Both plants and controllers considered are modeled as hybrid dynamical systems, which are systems with both continuous and discrete dynamics, given in terms of a flow set, a flow map, a jump set, and a jump map. Using recently developed tools for the study of stability in hybrid systems, we recast the tracking problem as the task of asymptotically stabilizing a set, the tracking set, and derive conditions for the design of state‐feedback tracking controllers with the property that the jump times of the plant coincide with those of the given reference trajectories. The resulting tracking controllers guarantee that solutions of the plant starting close to the reference trajectory stay close to it and that the difference between each solution of the controlled plant and the reference trajectory converges to zero asymptotically. Constructive conditions for tracking control design in terms of LMIs are proposed for a class of hybrid systems with linear maps and input‐triggered jumps. The results are illustrated by various examples. Copyright © 2013 John Wiley & Sons, Ltd.     

Robust stability of Markovian jump discrete-time neural networks with partly unknown transition probabilities and mixed mode-dependent delays

This article discusses the robust stability problem for a class of uncertain Markovian jump discrete-time neural networks with partly unknown transition probabilities and mixed mode-dependent time delays. The transition probabilities of the mode jumps are considered to be partly unknown, which relax the traditional assumption in Markovian jump systems that all of them must be completely known a priori. The mixed time delays consist of both discrete and distributed delays that are dependent on the Markovian jump modes. By employing the Lyapunov functional and linear matrix inequality approach, some sufficient criteria are derived for the robust stability of the underlying systems. A numerical example is exploited to illustrate the developed theory.     

Jump linear quadratic regulator with controlled jump rates

Deals with the class of continuous-time linear systems with Markovian jumps. We assume that jump rates are controlled. Our purpose is to study the jump linear quadratic (JLQ) regulator of the class of systems. The structure of the optimal controller is established. For a one-dimensional (1-D) system, an algorithm for solving the corresponding set of coupled Riccati equations of this optimal control problem is provided. Two numerical examples are given to show the usefulness of our results     

转移概率部分未知的随机Markov 跳跃系统的镇定控制

研究一类随机Markov跳跃系统的稳定性与镇定控制问题.此类系统跳跃过程的转移概率部分未知,包括转移概率完全已知和完全未知两种情形,因而更具一般性.首先,给出保证随机Markov跳跃系统均方渐近稳定的充分性判据,并设计了相应的状态反馈镇定控制器;然后,基于矩阵的奇异值分解给出了系统静态输出反馈镇定控制器的设计方法,并将其归结为求解一组线性矩阵不等式（LMIs）的可行性问题;最后,通过数值仿真验证了所得结论的正确性.     

模型相关时变时滞马尔可夫跳变系统低保守稳定性

本文研究了时变时滞与模型相关的随机马尔可夫跳变系统的时滞相关稳定性问题. 通过建立时变时滞与模型相关的系统模型, 构造不同的Lyapunov-Krasovskii函数, 并通过引入改进的积分等式, 以线性矩阵不等式的形式提出了具有较小保守性的时滞依赖稳定性条件. 最后用几个数值算例说明本文结论的有效性及较低的保守性.     

基于关键语义子树的间接跳转目标解析

针对传统间接跳转解析方法受限于特定模板或模式的局限性,提出一种基于关键语义子树的间接跳转目标解析技术,在为机器指令语义映射生成的语义树上,提取间接跳转典型形式的语义特征,忽略与跳转生成无关的指令,自动生成跳转目标计算函数,实现与编译器及优化选项均无关的间接跳转目标的自动解析。实验结果证明,该方法普适性良好。     

A stochastic maximum principle for systems with jumps, with applications to finance

We consider a stochastic control problem with linear dynamics with jumps, convex cost criterion, and convex state constraint, in which the control enters the drift, the diffusion, and the jump coefficients. We allow these coefficients to be random, and do not impose any L^p-bounds on the control.

We obtain a stochastic maximum principle for this model that provides both necessary and sufficient conditions of optimality. This is the first version of the stochastic maximum principle that covers the consumption–investment problem in which there are jumps in the price system.     

A biomechanical analysis of good and poor performers of the vertical jump

The vertical jump is widely used as a field test of performance capability, particularly in games like soccer. Invariably some players perform better than others and, while this is usually put down to greater strength or 'explosive power', there is no detailed information to explain how the muscles around the major joints contribute to this performance and what the nature of this contribution is, or indeed whether aspects of technique are important to performance. Detailed knowledge of this type would be useful to help understand which muscle characteristics are important in successful performance of jumping and may enable insights to be gained in terms of strength training for players. The aim of this study was to investigate the contribution made by the lower limb joints to vertical jump performance by good and poor performers of the counter-movement jump.Two groups of players were selected who were found to be good and poor jumpers, respectively. Each player was required to perform three maximal vertical counter-movement jumps with, and three jumps without, an arm swing. The jump performance was recorded simultaneously by means of a force platform and a ProReflex automatic motion analysis system at 240 Hz. Values at the ankle, knee and hip were computed from these data for joint moments and power.Generally, better jumpers demonstrated greater joint moments, power and work done at the ankle, knee and hip, and as a result jumped higher under both conditions. It appears that the superior performance of the better jumpers was due to greater muscle capability in terms of strength and rate of strength development in all lower limb joints rather than to technique, which differed less noticeably between the groups. It is concluded that the muscle strength characteristics of the lower limb joints are the main determinant of vertical jump performance with technique playing a smaller role.     

Finite horizon quadratic optimal control and a separation principle for Markovian jump linear systems

In this note, we consider the finite-horizon quadratic optimal control problem of discrete-time Markovian jump linear systems driven by a wide sense white noise sequence. We assume that the output variable and the jump parameters are available to the controller. It is desired to design a dynamic Markovian jump controller such that the closed-loop system minimizes the quadratic functional cost of the system over a finite horizon period of time. As in the case with no jumps, we show that an optimal controller can be obtained from two coupled Riccati difference equations, one associated to the optimal control problem when the state variable is available, and the other one associated to the optimal filtering problem. This is a principle of separation for the finite horizon quadratic optimal control problem for discrete-time Markovian jump linear systems. When there is only one mode of operation our results coincide with the traditional separation principle for the linear quadratic Gaussian control of discrete-time linear systems.     

A control theoretic approach to malaria immunotherapy with state jumps

We investigate a control method for malaria dynamics to boost the immune response using a model-based approach. The idea of state jump is introduced and discussed using a hybrid model. To implement the state jumps we use a physiologically feasible method for the biological system, whereby the introduction of a pathogen into the system steers it to a desirable status. It is noted that we take advantage of a pathogen to implement state jumps in the system. The study is supported by recently reported experimental results.     

多目标跟踪中一种改进的高斯混合PHD滤波算法

高斯混合概率假设密度（GM-PHD）滤波是一种杂波环境下多目标跟踪问题算法,针对算法中存在的目标漏检和距离相近时精度下降的问题,提出一种改进的高斯混合PHD滤波算法。该算法在高斯混合框架下通过修正PHD递归方程,有效地解决了漏检引起的有用信息丢失问题;利用权值判断高斯分量是否用于提取目标状态,避免了具有较高权值的高斯分量合并在一起,从而改善目标相互接近时的跟踪性能。仿真实验表明,改进算法在滤波精度和目标数估计方面均优于传统的GM-PHD算法。     

On an New Algorithm for Function Approximation with Full Accuracy in the Presence of Discontinuities Based on the Immersed Interface Method

This paper is devoted to the construction and analysis of an adapted and nonlinear multiresolution algorithm designed for interpolation or approximation of discontinuous univariate functions. The adaption attained allows to avoid numerical artifacts that appear when using linear algorithms and, at the same time, to obtain a high order of accuracy close to the singularities. It is known that linear algorithms are stable and convergent for smooth functions, but diffusion and Gibbs effect appear if the functions are piecewise continuous. Our aim is to develop an algorithm for function approximation with full accuracy that is capable to adapt to corners (kinks) and jump discontinuities, that uses a centered stencil and that does not use extrapolation. In order to reach this goal, we will need some information about the jumps in the function that we want to approximate and its derivatives. If this information is available, the algorithm is the most compact possible in the sense that the stencil is fixed and we do not need a stencil selection procedure as other algorithms do, such as ENO subcell resolution (ENO-SR). If the information about the jumps is not available, we will show a technique to approximate it. The algorithm is based on linear interpolation plus correction terms that provide the desired accuracy close to corners or jump discontinuities.     

A New Ghost Cell/Level Set Method for Moving Boundary Problems: Application to Tumor Growth

In this paper, we present a ghost cell/level set method for the evolution of interfaces whose normal velocity depend upon the solutions of linear and nonlinear quasi-steady reaction-diffusion equations with curvature-dependent boundary conditions. Our technique includes a ghost cell method that accurately discretizes normal derivative jump boundary conditions without smearing jumps in the tangential derivative; a new iterative method for solving linear and nonlinear quasi-steady reaction-diffusion equations; an adaptive discretization to compute the curvature and normal vectors; and a new discrete approximation to the Heaviside function. We present numerical examples that demonstrate better than 1.5-order convergence for problems where traditional ghost cell methods either fail to converge or attain at best sub-linear accuracy. We apply our techniques to a model of tumor growth in complex, heterogeneous tissues that consists of a nonlinear nutrient equation and a pressure equation with geometry-dependent jump boundary conditions. We simulate the growth of glioblastoma (an aggressive brain tumor) into a large, 1 cm square of brain tissue that includes heterogeneous nutrient delivery and varied biomechanical characteristics (white matter, gray matter, cerebrospinal fluid, and bone), and we observe growth morphologies that are highly dependent upon the variations of the tissue characteristics-an effect observed in real tumor growth.     

Leverage, heavy-tails and correlated jumps in stochastic volatility models

Efficient and fast Markov chain Monte Carlo estimation methods for the stochastic volatility model with leverage effects, heavy-tailed errors and jump components, and for the stochastic volatility model with correlated jumps are proposed. The methods are illustrated using simulated data and are applied to analyze daily stock returns data on S&P500 index and TOPIX. Model comparisons are conducted based on the marginal likelihood for various SV models including the superposition model.