16880603
Adaptive Load Balancing for Long-Range MD Simulations in A Distributed Environment
Molecular dynamics, a computationally intensive application is used by researchers in various fields. The inherent parallelism (Plimpton and Hendrickson, 1994) in the computations involved with this application can be exploited in parallel and distributed environments. However, in distributed environments such as the grid (Foster et al., 2001), the available resources, namely the network and computational power, are continually changing with respect to every available node. To optimally utilize these dynamic resources, a scheduler should be able to continually adapt to the changes and suitably vary the load scheduled to every available node. We propose one such scheduling algorithm. The proposed scheduling algorithm builds and continually updates a model of the distributed system, which it then uses to make decisions about how to optimally redistribute the load in the system at every time step of the MD simulation. The scheduling algorithm can additionally handle dynamic changes in the number of nodes available for computation at runtime. We then demonstrate the efficiency of our scheduling algorithm when applied to MD simulations in a distributed environment
45166966
Approximate Analysis of Multiprocessing Task Graphs
8918525
An efficient, low-cost inconsistency detection framework for data and service sharing in an Internet-scale system
In this paper, we argue that a broad range of Internet-scale distributed applications can benefit from an underlying low-cost consistency detection framework that is an alternative to inconsistency avoidance and can detect inconsistency among nodes sharing data or services in a timely manner. This paper first presents an overview of the inconsistency detection framework. Then, it discusses the detailed design of the two-layer inconsistency detection module, the core component of this framework, which can detect inconsistency among nodes in a timely manner. The proposed two-layer inconsistency detection module is evaluated both analytically and via simulations, which shows that this module can significantly reduce the time to detect inconsistency among nodes without adding much maintenance cost. Finally, this paper outlines the possible mechanisms to discern the application semantics and to resolve the detected inconsistencies
14848209
Distributed systems middleware architecture from a software engineering perspective
Networked heterogeneous systems pose a great challenge for parallel and distributed applications. Middleware provides a critical link between the vast resources and the application domain that simplifies development, provides robust and reliable access to resources, helps optimize resource utilization, and facilitates the generation of stable distributed software. In this paper, we discuss a layered framework for distributed systems middleware, called Delmon, which supports parallel and distributed programming models, tools and applications on heterogeneous systems. Distributed systems middleware provides multiple layers of abstractions to hide the details of the distributed system and facilitate the efficient utilization of such systems. From a software engineering point-of-view, such a layered middleware approach and the separation of concerns improve the development and management of parallel and distributed applications in many ways. The proposed model represented by Delmon is a general three-layer middleware that provides the services required to support parallel and distributed models and applications in clusters and heterogeneous systems. The layers are: the resource-specific services, the self-organized run-time environment, and the parallel and distributed programming models. We also demonstrate the benefits of this well-defined layered approach that offers different levels of services and functionalities.
23742969
High-performance message striping over reliable transport protocols
This paper introduces a high-performance middleware-level message striping approach to increase communication bandwidth for data transfer in heterogeneous clusters equipped with multiple networks. In this scheme, concurrency is used for the striping process. The proposed striping approach is designed to work at the middleware-level, between the distributed applications and the reliable transport protocols such as TCP. The middleware-level striping approach provides flexible, scalable, and hardware-, network-, and operating systems-independent communication bandwidth solution. In addition, techniques to enhance the performance of this approach over multiple networks are introduced. The proposed techniques, which minimize synchronization contention and eliminate the striping sequence header, rely on the features of a reliable transport protocol such as TCP to reduce some of the concurrent striping overhead. The techniques have been implemented and evaluated on a real cluster with multiple networks and the results show significant performance gains for data transfer over existing approaches.
1546029
Design and Analysis of Hierarchical Ring Networks for Shared-Memory Multiprocessors
ÐWe study four augmentations of ring networks which are intended to enhance a ring's efficiency as a communication medium significantly, while increasing its structural complexity only modestly. Chordal rings add ashortcuto edges, which can be viewed as chords, to the ring. Express rings are chordal rings whose chords are routed outside the ring. Multirings append subsidiary rings to edges of a ring and, recursively, to edges of appended subrings. Hierarchical ring networks (HRN's) append subsidiary rings to nodes of a ring and, recursively, to nodes of appended subrings. We show that these four modes of augmentation are very closely related: 1) Planar chordal rings, planar express rings, and multirings are topologically equivalent families of networks with the acutwidtho of an express ring translating into the atree deptho of its isomorphic multiring and vice versa. 2) Every depth-d HRN is a spanning subgraph of a depth-2dÿ 1 multiring. 3) Every depth-d multiring M can be embedded into a d-dimensional mesh with dilation 3 in such a way that some node of M resides at a corner of the mesh. 4) Every depth-d HRN H can be embedded into a d-dimensional mesh with dilation 2 in such a way that some node of H resides at a corner of the mesh. In addition to demonstrating that these four augmented ring networks are grid graphs, our embedding results afford us close bounds on how much decrease in diameter is achievable for a given increase in structural complexity for the networks. Specifically, we derive upper and lower bounds on the optimal diameters of N-node depth-d multirings and HRNs that are asymptotically tight for large N and d. Index TermsÐRing networks, chordal rings, express rings, multirings, hierarchical ring networks, grid graphs, graph embedding, diameter trade-offs.
16906364
Scalable and Robust Aggregation Techniques for Extracting Statistical Information in Sensor Networks
Wireless sensor networks have stringent constraints on system resources and data aggregation techniques are critically important. However, accurate data aggregation is difficult due to the variation of sensor readings and due to the frequent communication failures. To address these difficulties, we propose a scalable and robust data aggregation algorithm. The novelty of our work includes two aspects. First, our algorithm exploits the mixture model and the Expectation Maximization (EM) algorithm for parameter estimation. Hence, it captures the effects of aggregation over different scales while keeping the communication cost low. Second, our algorithm exploits loss-tolerant multi-path routing schemes. Hence, it obtains accurate statistical information even in the presence of high link and node failure rates. We demonstrate that our techniques reduce communication cost while retaining the precious statistical information otherwise neglected by other aggregation techniques. Our evaluation shows the proposed techniques are robust against link and node failures, and perform consistently well.
22852167
Parallel Random Tunneling Algorithm for Structural Optimization of Lennard-Jones Clusters up to N = 330
A random tunneling algorithm (RTA) is derived from the terminal repeller unconstrained subenergy tunneling (TRUST) algorithm, and the parallelization of the RTA is implemented with an island parallel paradigm. Combined with the techniques of angular moving, the parallel random tunneling algorithm (PRTA) is applied to the optimization of Lennard-Jones (LJ) atomic clusters, and all the global minima of LJ clusters with size up to 200 are successfully located. For the optimization of larger cluster, a PRTA with an improved seeding technique is developed and successfully applied to the optimization of LJ151-LJ309. Furthermore, the optimized structures of LJ309-330 with the PRTA, which have not been studied before, are also provided.
2540895
Large margin hidden Markov models for speech recognition
In this paper, motivated by large margin classifiers in machine learning, we propose a novel method to estimate continuous-density hidden Markov model (CDHMM) for speech recognition according to the principle of maximizing the minimum multiclass separation margin. The approach is named large margin HMM. First, we show this type of large margin HMM estimation problem can be formulated as a constrained minimax optimization problem. Second, we propose to solve this constrained minimax optimization problem by using a penalized gradient descent algorithm, where the original objective function, i.e., minimum margin, is approximated by a differentiable function and the constraints are cast as penalty terms in the objective function. The new training method is evaluated in the speaker-independent isolated E-set recognition and the TIDIGITS connected digit string recognition tasks. Experimental results clearly show that the large margin HMMs consistently outperform the conventional HMM training methods. It has been consistently observed that the large margin training method yields significant recognition error rate reduction even on top of some popular discriminative training methods
19285635
Global Optimization of Lennard-Jones Clusters by a Parallel Fast Annealing Evolutionary Algorithm
A parallel fast annealing evolutionary algorithm (PFAEA) was presented and applied to optimize Lennard-Jones (LJ) clusters. All the lowest known minima up to LJ(116) with both icosahedral and nonicosahedral structure, including the truncated octahedron of LJ(38), central fcc tetrahedron of LJ(98), the Marks' decahedron of LJ(75)(-)(77), and LJ(102)(-)(104), were located successfully by the unbiased algorithm. PFAEA is a parallel version of fast annealing evolutionary algorithm (FAEA) that combines the aspect of population in genetic algorithm and annealing algorithm with a very fast annealing schedule. A master-slave paradigm is used to parallelize FAEA to improve the efficiency. The performance of PFAEA is studied, and the scaling of execution time with the cluster size is approximately cubic, which is important for larger scale energy minimization systems.
9730668
Broadening the Semantic Coverage of Agent Communicative Acts
Communicative acts-based ACLs specify domain-independent information about communication and relegate domain-dependent information to an unspecified content language. This is reasonable, but the ACLs cover only a small fraction of the domain-independent information possible. As a key element of modern ACLs, the set of communicative acts needs to be as complete as possible to allow agents to communicate the widest range of information with agreed-upon semantics. This paper describes a new approach to broaden the semantic coverage of agent communicative acts. It provides agents with the ability to express more of the semantics of human languages and yields a more powerful ACL. We first describe the main meaning categories and semantics for an ACL, which we derive from prior work on speech-act classifications. Next, we prove the resultant semantic coverage. Finally, we present some example applications, which demonstrate that the approach can combine the benefits of the FIPA ACL with Ballmer and Brennenstuhl’s speech act classification, resulting in a more expressive and efficient ACL.