Proactive scheduling in distributed computing—A reinforcement learning approach

In distributed computing such as grid computing, online users submit their tasks anytime and anywhere to dynamic resources. Task arrival and execution processes are stochastic. How to adapt to the consequent uncertainties, as well as scheduling overhead and response time, are the main concern in dynamic scheduling. Based on the decision theory, scheduling is formulated as a Markov decision process (MDP). To address this problem, an approach from machine learning is used to learn task arrival and execution patterns online. The proposed algorithm can automatically acquire such knowledge without any aforehand modeling, and proactively allocate tasks on account of the forthcoming tasks and their execution dynamics. Under comparison with four classic algorithms such as Min–Min, Min–Max, Suffrage, and ECT, the proposed algorithm has much less scheduling overhead. The experiments over both synthetic and practical environments reveal that the proposed algorithm outperforms other algorithms in terms of the average response time. The smaller variance of average response time further validates the robustness of our algorithm.     

A Parallel Domain Decomposition Method for 3D Unsteady Incompressible Flows at High Reynolds Number

Numerical simulation of three-dimensional incompressible flows at high Reynolds number using the unsteady Navier–Stokes equations is challenging. In order to obtain accurate simulations, very fine meshes are necessary, and such simulations are increasingly important for modern engineering practices, such as understanding the flow behavior around high speed trains, which is the target application of this research. To avoid the time step size constraint imposed by the CFL number and the fine spacial mesh size, we investigate some fully implicit methods, and focus on how to solve the large nonlinear system of equations at each time step on large scale parallel computers. In most of the existing implicit Navier–Stokes solvers, segregated velocity and pressure treatment is employed. In this paper, we focus on the Newton–Krylov–Schwarz method for solving the monolithic nonlinear system arising from the fully coupled finite element discretization of the Navier–Stokes equations on unstructured meshes. In the subdomain, LU or point-block ILU is used as the local solver. We test the algorithm for some three-dimensional complex unsteady flows, including flows passing a high speed train, on a supercomputer with thousands of processors. Numerical experiments show that the algorithm has superlinear scalability with over three thousand processors for problems with tens of millions of unknowns.     

A Stability Criterion for Semi-Discrete Difference Schemes of Hyperbolic Conservation Laws on Uniform Grids

In the present study, the stability condition for semi-discrete difference schemes of hyperbolic conservation laws obtained from Fourier analysis is simplified. This stability condition can be applied only to linear difference schemes with constant coefficients implemented with periodic boundary treatment. It could often give useful results for other cases, such as schemes with variable coefficients, schemes for nonperiodic problem and nonlinear problem. However, this condition usually leads to a trigonometric inequality, which makes it not convenient to use. For explicit difference schemes on uniform grids, this trigonometric inequality can be converted to polynomial form. Furthermore, if the scheme is a high-order one, the polynomial can be factorized into a simple form. Thus, it is much easier to solve than the inequality obtained directly from Fourier analysis. For compact difference schemes and conservative schemes, similar results are obtained. Some applications of this new stability criterion are shown, including judging the stability of two schemes, proving the upstream central schemes to be stable, constructing a stable upwind dissipation relation preserving (DRP) scheme and constructing an optimized weighted essentially non-oscillatory (WENO) scheme. Since WENO schemes are nonlinear schemes, the stability analysis in the present study is performed on their underlying linear schemes. According to the numerical tests, the underlying linear scheme should be stable, otherwise the corresponding WENO scheme may display instability. These applications demonstrate that this criterion is convenient and efficient for judging the linear stability of semi-discrete difference schemes and constructing stable upwind difference schemes.     

配料系统中核子秤的实物标定法

针对使用单位对核子秤实物标定方法的认识与掌握不够，而导致核子秤不能正常使用的问题，文中详细介绍了配料系统中应用核子秤进行实物标定的条件及几种方法。     

新型节能玻璃钢门窗的研究

本文主要围绕节能主题，从能耗方式、性能指标、结构形式、制作安装等方面论述了玻璃钢门窗在不同气候地区、不同环境和不同领域中的开发和应用。     

磺草酮对玉米的安全性及除草效果评价

田间测定了磺草酮对玉米的安全性及防除杂草试验效果，结果表明磺草酮有效成分562．5～1200g／hm^2防除玉米田单子叶杂草马唐、牛筋草、狗尾草效果较好，防效为86．5％～98．0％；对双子叶杂草中的反枝苋防效较好，防效为99．3％～l00％；对铁苋莱和马齿苋防效较差，防效为35．0％～62．9％。对玉米有触杀性药害，至药后15天药害症状消失，不影响玉米的产量，且有较好的增产作用，增产l0．0％左右。     

α-Fe2O3/煤矸石复合光催化剂的制备及其降解五氯酚性能的研究

以Fe（NO₃）₃、煤矸石和NaOH为原料,采用沸腾回流法制得了一系列不同质量比的α-Fe₂O₃/煤矸石复合光催化剂。采用场发射扫描电子显微镜（FESEM）、X射线衍射仪（XRD）及紫外-可见漫反射光谱（UV-Vis DRS）等多种手段对产物做了表征。以五氯酚为目标降解物,考察了模拟太阳光照下样品的光催化效果。结果表明,将球形α-Fe₂O₃负载于改性煤矸石表面可有效提高其光催化活性,且α-Fe₂O₃/煤矸石复合光催化剂的性能与α-Fe₂O₃的含量有关,当α-Fe₂O₃与煤矸石的质量比为30∶100时,样品的光催化效果最佳,180 min内即可将五氯酚降解完全。此外,α-Fe₂O₃/煤矸石复合光催化剂还具有可重复使用的特点。     

大掺量粉煤灰对混凝土渗透性的影响

以粉煤灰代替３０％的水泥，在水胶比为０．３０、０．３３、０．３６及０．３９的情况下，分别试验了用水量及胶凝材料用量变化下混凝土的强度和渗透性。试验结果表明，与不掺粉煤灰的混凝土比较，掺粉煤灰混凝土的渗透性都明显降低，３０天龄期时最大可降低至５０．７％，７０天时可降低至２２．３％；为了获得较低的渗透性而采取较低的水胶比时，不掺粉煤灰的混凝土应用降低用水量的办法有利，掺粉煤灰的混凝土用提高总胶凝材料用量的办法更好     

晶雕堆花装饰环保型高档陶瓷内墙砖的研制

文中简要说明了晶雕堆花装饰环保型陶瓷内墙砖的特点及其研制开发的意义，介绍了无铅干粒釉的制备方法及性能特征，详细阐述了晶雕堆花装饰的加工工艺过程。     

不同混合材掺量对低碱水泥适应性的试验研究

对不同种类及掺量的混合材对低碱水泥流动洼能进行试验研究，结果为：低碱硅酸盐水泥中掺入矿渣粉、粉煤灰、石灰石等混合材有利于改善浆体流动性能，目双掺效果较单掺好；外加剂掺入量对流动性能的改善随着掺量的增加而增加，但掺入量应适宜、经济；石灰石为非活洼混合材，本试验研究结果表明它能显著增大水泥流动性且保持较小的经时损失，但其掺量不宜过大。