Efficient computation of optimal assignments for distributed tasks

We consider the problem of finding an optimal assignment of the modules of a program to processors in a distributed system. A module incurs an execution cost that may be different for each processor assignment, and modules that are not assigned to the same processor but that communicate with one another incur a communication cost. An optimal assignment minimizes the sum of the module execution costs and the intermodule communication costs. This problem is known to be NP-complete for more than three processors. Using a branch-and-bound-with-underestimates algorithm to reduce the size of the search tree, we evaluate its average time and space complexity for two underestimating functions through simulation. The more complex of the two functions, called the minimum independent assignment cost underestimate (MIACU), performs extremely well over a wide range of values of program model parameters such as the number of modules, the number of processors, and the ratio of average module execution cost to average intermodule communication cost. By reordering the list of modules to allow a subset of modules that do not communicate with one another to be assigned last, further improvements using MIACU are possible.     

ARM程序执行周期估计的基于模拟的非线性方法

为了快速而准确地估计ARM处理器上的程序执行时间,研究了基于模拟的非线性程序执行时间估计器的结构.它由程序功能剖面生成模块和程序执行时间预测模块串联而成.程序功能剖面生成模块直接用精确指令模拟器Sim-profile实现;而基于程序执行中的动态指令数与执行时间在处理器上的非线性关系,对于程序执行时间预测模块的实现,首先设计了一种人工神经网络方案,再根据对人工神经网络局限性的判断,如局部最优问题、不适于解决小样本的回归、网络拓扑结构依赖先验知识等缺点,又提出了基于最小二乘支持向量机的方法.实验证明,这些非线性方法,特别是基于最小二乘支持向量机的方法,可以用较低的模拟代价获得较高的程序执行时间估计精度.     

Allocating modules to processors in a distributed system

The author studies the complexity of the problem of allocating modules to processes in a distributed system to minimize total communication and execution costs. He shows that unless P=NP, there can be no polynomial-time ϵ-approximate algorithm for the problem, nor can there exist a local search algorithm that requires polynomial time per iteration and yields an optimum assignment. Both results hold even if the communication graph is planar and bipartite. On the positive side, it is shown that if the communication graph is a partial k-tree or an almost-tree with parameter k, the module allocation problem can be solved in polynomial time     

Synchronization and communication costs of loop partitioning onshared-memory multiprocessor systems

The author presents strategies for static loop decomposition and scheduling as well as computer-assisted run-time scheduling that take into account, in addition to the cost of performing operations, the overhead costs associated with a decomposition and schedule. An algorithm for static decomposition of multidimensional loops based on the operation execution costs, communication costs, and synchronization costs is discussed. Synchronization instructions are introduced to ensure correct program execution following program decomposition. An algorithm for determining the explicit synchronization instruction that should be introduced to ensure correct execution of a program with arbitrarily nested loops is presented. Techniques for reducing run-time scheduling and communication and synchronization costs due to self-scheduling of multidimensional loops are also presented. Experiments performed on the Encore multiprocessor system demonstrate that the techniques developed can reduce overhead costs     

The decision model of task allocation for constrained stochastic distributed systems

In distributed systems, an application program is divided into several software modules, which need to be allocated to processors connected by communication links. The distributed system reliability (DSR) could be defined as the probability of successfully completing the distributed program. Previous studies about optimal task allocation with respect to DSR focused on the effects of the inter-connectivity of processors, the failure rates of the processors, and the failure rates of the communication links. We are the first to study the effects of module software reliabilities and module execution frequencies on the optimal task allocation. By viewing each module as a state in the Markov process, we build a task allocation decision model to maximize DSR for distributed systems with 100% reliable network. In this model, the DSR is derived from the module software reliabilities, the processor hardware reliabilities, the transition probabilities between modules, and the task allocation matrix. Resource constraints of memory space limitation and computation load limitation on each processor are considered. The constraint of total system cost, including the execution cost, the communication cost, and the failure cost, is also considered. We solve the problem by Constraint Programming using the ILOG SOLVER library. We then apply the proposed model to a case extended from previous studies. Finally, a sensitivity analysis is performed to verify the effects of module software reliabilities and processor hardware reliabilities on the DSR and on the task allocation decision.     

Optimal task assignment in homogeneous networks

This paper considers the problem of assigning the tasks of a distributed application to the processors of a distributed system such that the sum of execution and communication costs is minimized. Previous work has shown this problem to be tractable for a system of two processors or a linear array of N processors, and for distributed programs of serial parallel structures. Here we focus on the assignment problem on a homogeneous network, which is composed of N functionally-identical processors, each with its own memory. Some processors in the network may have unique resources, such as data files or certain peripheral devices. Certain tasks may have to use these unique resources; they are called attached tasks. The tasks of a distributed program should therefore be assigned so as to make use of specific resources located at certain processors in the network while minimizing the amount of interprocessor communication. The assignment problem in such a homogeneous network is known to be NP-hard even for N=3, thus making it intractable for a network with a medium to large number of processors. We therefore focus on task assignment in general array networks, such as linear arrays, meshes, hypercubes, and trees. We first develop a modeling technique that transforms the assignment problem in an array or tree into a minimum-cut maximum-flow problem. The assignment problem is then solved for a general array or tree network in polynomial time     

Program structuring for effective parallel portability

The tension between software development costs and efficiency is especially high when considering parallel programs intended to run on a variety of architectures. In the domain of shared memory architectures and explicitly parallel programs, the authors have addressed this problem by defining a programming structure that eases the development of effectively portable programs. On each target multiprocessor, an effectively portable program runs almost as efficiently as a program fine-tuned for that machine. Additionally, its software development cost is close to that of a single program that is portable across the targets. Using this model, programs are defined in terms of data structure and partitioning-scheduling abstractions. Low software development cost is attained by writing source programs in terms of abstract interfaces and thereby requiring minimal modification to port; high performance is attained by matching (often dynamically) the interfaces to implementations that are most appropriate to the execution environment. The authors include results of a prototype used to evaluate the benefits and costs of this approach     

Task allocation model for distributed systems

The problem of distributing tasks to processors in a distributed computing system is addressed. A task should be assigned to a processor whose capabilities are most appropriate for the execution of that task and excessive interprocessor communication is avoided. A simple algorithm for task allocation is presented. The execution costs and communication costs of the tasks are represented by arrays. A task is either assigned to a processor or fused with another task using a simple criterion. The execution and communication costs are then modified suitably. The process continues until all the tasks are assigned to processors. This algorithm also facilitates incorporation of various system constraints. It is applicable to random program structures and to a system containing any number of processors.     

Comments on `Allocating programs containing branches and loopswithin a multiple processor system' by D. Towsley

The assignment algorithms proposed by D. Towsley (see ibid., vol.12, no.10, p.1018-24 (1986)) may not minimize the total communication and execution costs as stated. An example where the proposed restricted assignment algorithm fails to find an optimal assignment is given, and modifications that allow the algorithm to properly consider execution costs are proposed. Additional changes needed to model communication costs correctly in many assignment problems are discussed     

编译支持的多变体融合执行设计与实现

多变体执行是由异构冗余变体并行执行来检测攻击的一种技术。作为一种主动防御技术,多变体执行(multi-variant execution,MVX)通过并行运行的异构执行体之间一致性检查发现攻击行为。相较于补丁式的被动防御,MVX可在不依赖攻击特征信息的情况下防御已知漏洞乃至未知漏洞威胁,在网络安全领域具有广泛的应用前景。然而该技术在实际部署中,由于多变体执行架构的边界不清晰,将随机数、进程PID号等被动地纳入到了表决范围,从而产生误报,导致多变体执行无法兼容更多的软件系统。本文分析了多变体执行假阳问题产生的原因,提出I-MVX,一种编译支持的多变体融合执行架构,包括多变体同步编程框架和运行时同步模块。I-MVX通过添加少量编译指示,在编译阶段对程序内部引起假阳性问题的代码和变量进行插桩标识,在运行时由监视器对变体进程内部和外部的变量及资源进行同步处理,消除多变体执行中的误报。本文基于LLVM/Clang编译器和Linux内核加载模块设计实现了I-MVX的编译器和同步监视器。性能实验评估显示,I-MVX在SPEC 2006基准测试集和tinyhttpd测试程序下引入的平均开销分别为2.13%和13.2%。多变体融合执行架构能够以少量的性能损耗为代价有效解决多变体执行中的假阳问题,提升多变体执行的可用性。基于真实CVE漏洞的安全性测试表明,I-MVX在保证多变体执行安全防御有效性基础上提升了多变体执行的兼容性。     

一个关于求解k-种产品选址问题的近似算法

对于k-种产品工厂选址问题,有如下描述：存在一组客户和一组可以建立工厂的厂址。现在有k种不同的产品,要求每一个客户必须由k个不同的工厂来提供k种不同的产品,其中每个工厂都只能为客户提供唯一的一种产品。在该问题中,假定建厂费用以及任意两个结点之间的运输费用都为非负,并且任意两个结点之间的运输费用都满足对称和三角不等式关系的性质。问题的要求是要从若干厂址中选择一组厂址来建立工厂,给每个工厂指定一种需要生产的产品,并且给每一个客户提供一组指派使每个客户都能有k个工厂来为其供应这k种不同的产品。对于此类问题,优化目标是最小化建厂费用以及运输费用。论文在假设建厂费用为零的前提下,提出了求解该类问题的一种最坏性能比为3k/2-1的近似算法。     

Task assignment in heterogeneous computing systems

The problem of task assignment in heterogeneous computing systems has been studied for many years with many variations. We consider the version in which communicating tasks are to be assigned to heterogeneous processors with identical communication links to minimize the sum of the total execution and communication costs. Our contributions are three fold: a task clustering method which takes the execution times of the tasks into account; two metrics to determine the order in which tasks are assigned to the processors; a refinement heuristic which improves a given assignment. We use these three methods to obtain a family of task assignment algorithms including multilevel ones that apply clustering and refinement heuristics repeatedly. We have implemented eight existing algorithms to test the proposed methods. Our refinement algorithm improves the solutions of the existing algorithms by up to 15% and the proposed algorithms obtain better solutions than these refined solutions.     

A Block-Based Mode Selection Model for SIMD/SPMD Parallel Environments

One of the challenges for parallel compilers and compiler-related tools is, given a machine-independent parallel language, to generate executable code for a variety of computational models, and to identify those specific parallel modes for which a program is well-suited. One portion of this problem, developing a method for estimating the relative execution time of a data-parallel algorithm in an environment capable of the SIMD and SPMD (MIMD) modes of parallelism, is presented. Given a data-parallel program in a language whose syntax is mode-independent and empirical information about instruction execution time characteristics, the goal is to use static source-code analysis to determine an implementation that results in an optimal execution time for a mixed-mode machine capable of SIMD and SPMD parallelism. Statistical information about individual operation execution times and paths of execution through a parallel program is assumed. A secondary goal of this study is to indicate language, algorithm, and machine characteristics that must be researched to learn how to provide the information needed to obtain an optimal assignment of parallel modes to program segments.     

Optimal assignment of cells in PCS networks

This paper deals with the assignment problem of cells to switches in a personal communication service network. Three types of costs in a PCS network are considered in detail: the cost of handoffs, the cost of cabling, and the cost of switching. The optimal assignment problem is formulated as an integer-programming problem. A heuristic algorithm is proposed to obtain an assignment of cells in a PCS network. The proposed algorithm is compared with an existing heuristic cell assignment algorithm. By numerical examination, it is shown that the switching cost has a large effect on the solution of the cell assignment problem. The proposed algorithm obtains much better cell assignment in which the load of each switch is balanced and the total cost of a PCS network is much lower than what is obtained by the existing algorithm that does not take account of the switching cost. If the switching cost is taken into account, it has also been shown that our proposed algorithm achieves substantially the same results as the existing algorithm while requiring much less computation time.     

混合云环境中数据敏感工作流调度

混合云环境下调度包含敏感数据的工作流主要考虑在满足数据安全性以及工作流截止时间的前提下,对工作流任务在混合云上进行分配,实现计算资源与任务的映射,并优化调度费用。采用了整数规划来建模求解包含数据敏感性、截止时间和调度费用3种约束条件的混合云工作流调度问题,同时为优化模型求解速度,基于“帕雷托最优”原理对工作流任务在混合云上的分配方案进行筛选以减小模型求解规模。实验表明,优先排除不合理的任务分配方案可有效减小整数规划模型的求解规模,缩短模型计算时间,在产生较小误差的情况下获得较优的调度结果。     

A binary linear programming formulation of the graph edit distance

A binary linear programming formulation of the graph edit distance for unweighted, undirected graphs with vertex attributes is derived and applied to a graph recognition problem. A general formulation for editing graphs is used to derive a graph edit distance that is proven to be a metric, provided the cost function for individual edit operations is a metric. Then, a binary linear program is developed for computing this graph edit distance, and polynomial time methods for determining upper and lower bounds on the solution of the binary program are derived by applying solution methods for standard linear programming and the assignment problem. A recognition problem of comparing a sample input graph to a database of known prototype graphs in the context of a chemical information system is presented as an application of the new method. The costs associated with various edit operations are chosen by using a minimum normalized variance criterion applied to pairwise distances between nearest neighbors in the database of prototypes. The new metric is shown to perform quite well in comparison to existing metrics when applied to a database of chemical graphs.     

Modeling of Software Partition for Distributed Real-Time Applications

The issue of software partition deals with the process of mapping the given set of logical modules, which reflect the user's point of view, into a set of software tasks, which reflect the software implementor's point of view. It is shown in this paper that the software partitioning problem can be modeled as one that maximizes the efficiency in resource utilization while observing the constraints on CPU throughput, memory space available, maximally allowed task execution time, and the order of module execution. The CPU and memory constraints are implementation dependent. The maximum task execution time constraint is due to considerations on the response time performance. The constraint on module execution order is a logical one, and it is shown to have significant performance impact. It is proven that by employing the module precedence relation, which reflects the sequence of module execution, the order of module execution can be properly maintained during the software partitioning process. And thus the defined tasks can be guaranteed to be completely executable, once properly activated With completely executable tasks, the operating overhead cost and the response time delay can be minimized. The following four module precedence relations are explored: precede, succeed, parallel, and precede as well as succeed. The validity of the selected partitioning criterion of maximizing the resource utilization efficiency is also assessed through simulation experiments. The results of simulation show that performance of the selected criterion is insensitive to the application environment, as well as to the application requirements.     

Multiprocessor Scheduling with the Aid of Network Flow Algorithms

In a distributed computing system a modular program must have its modules assigned among the processors so as to avoid excessive interprocessor communication while taking advantage of specific efficiencies of some processors in executing some program modules. In this paper we show that this program module assignment problem can be solved efficiently by making use of the well-known Ford–Fulkerson algorithm for finding maximum flows in commodity networks as modified by Edmonds and Karp, Dinic, and Karzanov. A solution to the two-processor problem is given, and extensions to three and n-processors are considered with partial results given without a complete efficient solution.