5480787
Parallel Formulations of Decision-Tree Classification Algorithms
Classification decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud detection, etc. Highly parallel algorithms for constructing classification decision trees are desirable for dealing with large data sets in reasonable amount of time. Algorithms for building classification decision trees have a natural concurrency, but are difficult to parallelize due to the inherent dynamic nature of the computation. In this paper, we present parallel formulations of classification decision tree learning algorithm based on induction. We describe two basic parallel formulations. One is based on Synchronous Tree Construction Approach and the other is based on Partitioned Tree Construction Approach. We discuss the advantages and disadvantages of using these methods and propose a hybrid method that employs the good features of these methods. We also provide the analysis of the cost of computation and communication of the proposed hybrid method. Moreover, experimental results on an IBM SP-2 demonstrate excellent speedups and scalability.
10015251
Repartitioning of Adaptive Meshes: Experiments with Multilevel Diffusion
For a large class of irregular grid applications, the structure of the mesh changes from one phase of the computation to the next. Eventually, as the graph evolves, the adapted mesh has to be repartitioned to ensure good load balance. If this new graph is partitioned from scratch, it will lead to an excessive migration of data among processors. In this paper, we present a new scheme for computing repartitionings of adaptively refined meshes. This scheme performs diffusion of vertices in a multilevel framework and minimizes vertex movement without significantly compromising the edge-cut.
38254367
Parallel formulations of decision-tree classification algorithms
Classification decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud detection, etc. Highly parallel algorithms for constructing classification decision trees are desirable for dealing with large data sets in reasonable amount of time. Algorithms for building classification decision trees have a natural concurrency, but are difficult to parallelize due to the inherent dynamic nature of the computation. We present parallel formulations of classification decision tree learning algorithm based on induction. We describe two basic parallel formulations. One is based on Synchronous Tree Construction Approach and the other is based on Partitioned Tree Construction Approach. We discuss the advantages and disadvantages of using these methods and propose a hybrid method that employs the good features of these methods. Experimental results on an IBM SP-2 demonstrate excellent speedups and scalability.
9454097
An asynchronous integration and event detection algorithm for simulating multi-agent hybrid systems
A simulation algorithm is presented for multi-agent hybrid systems---systems consisting of many sets of nonsmooth differential equations---such as systems involving multiple rigid bodies, vehicles, or airplanes. The differential equations are partitioned into coupled subsystems, called "agents"; and the conditions which trigger the discontinuities in the derivatives, called "events", may depend on the global state vector. Such systems normally require significant computational resources to simulate because a global time step is used to ensure the discontinuity is properly handled. When the number of systems is large, forcing all system to be simulated at the same rate creates a computational bottleneck, dramatically decreasing efficiency. By using a control systems approach for selecting integration step sizes, we avoid using a global time step. Each subsystem can be simulated asynchronously when the state is away from the event. As the state approaches the event, the simulation is able to synchronize each of the local time clocks in such a way that the discontinuities are properly handled without the need for "roll back". The algorithm's operation and utility is demonstrated on an example problem inspired by autonomous highway vehicles. Using a combination of stochastic modelling and numerical experiments we show that the algorithm requires significantly less computation time when compared with traditional simulation techniques for such problems, and scales more favorably with problem size.
1842716
Dynamic control of 3-D rolling contacts in two-arm manipulation
When two or more arms are used to manipulate a large object, it is necessary to maintain and control contacts between the object and effector(s) on one or more arms. The dynamic control of two arms manipulating a large object with rolling contacts is addressed. In the framework presented, the motion of the object as well as the loci of the contact points on the surface of the effectors and on the object can be directly controlled. The velocity and acceleration equations for three-dimensional rolling contacts are derived in order to obtain a dynamical model of the system. A nonlinear feedback algorithm that decouples and linearizes the system is used to demonstrate the control of rolling motion along each arm and the adaption of grasps to varying loads.<<ETX>>
5564142
Provable algorithms for parallel generalized sweep scheduling
Abstract We present provably efficient parallel algorithms for sweep scheduling, which is a commonly used technique in radiation transport problems, and involves inverting an operator by iteratively sweeping across a mesh from multiple directions. Each sweep involves solving the operator locally at each cell. However, each direction induces a partial order in which this computation can proceed. On a distributed computing system, the goal is to schedule the computation, so that the length of the schedule is minimized. Due to efficiency and coupling considerations, we have an additional constraint, namely, a mesh cell must be processed on the same processor along each direction. Problems similar in nature to sweep scheduling arise in several other applications, and here we formulate a combinatorial generalization of this problem that captures the sweep scheduling constraints,and call it the generalized sweep scheduling problem. Several heuristics have been proposed for this problem; see [S. Pautz, An algorithm for parallel S n sweeps on unstructured meshes, Nucl. Sci. Eng. 140 (2002) 111–136; S. Plimpton, B. Hendrickson, S. Burns, W. McLendon, Parallel algorithms for radiation transport on unstructured grids, Super Comput. (2001)] and the references therein; but none of these have provable worst case performance guarantees. Here we present a simple, almost linear time randomized algorithm for the generalized sweep scheduling problem that (provably) gives a schedule of length at most O ( log 2 n ) times the optimal schedule for instances with n cells, when the communication cost is not considered, and a slight variant, which coupled with a much more careful analysis, gives a schedule of (expected) length O ( log m log log log m ) times the optimal schedule for m processors. These are the first such provable guarantees for this problem. The algorithm can be extended with an additional multiplicative factor in the case when we have inter-processor communication latency, in the models of Rayward-Smith [UET scheduling with inter-processor communication delays, Discrete Appl. Math. 18 (1) (1987) 55–71] and Hwang et al. [Scheduling precedence graphs in systems with inter-processor communication times, SIAM J. Comput. 18(2) (1989) 244–257]. Our algorithms are extremely simple, and use no geometric information about the mesh; therefore, these techniques are likely to be applicable in more general settings. We also design a priority based list schedule using these ideas, with the same theoretical guarantee, but much better performance in practice; combining this algorithm with a simple block decomposition also lowers the overall communication cost significantly. Finally, we perform a detailed experimental analysis of our algorithm. Our results indicate that the algorithm compares favorably with the length of the schedule produced by other natural and efficient parallel algorithms proposed in the literature [S. Pautz, An Algorithm for parallel S n sweeps on unstructured meshes, Nucl. Sci. Eng. 140 (2002) 111–136; S. Plimpton, B. Hendrickson, S. Burns, W. McLendon, Parallel algorithms for radiation transport on unstructured grids, Super Comput. (2001)].
42935672
Performance Measurement of Main Memory Database Recovery Algorithms Based on Update-in-Place and Shadow Approaches
The authors present a performance study of two main memory database recovery algorithms, one using a shadow approach and the other update-in-place. The results show that in main memory databases, shadow approach performs better than update-in-place. The authors introduce minor improvements to the shadow scheme and show that the modified algorithm does show further performance improvement. >
8129817
Trajectory design for formations of robots by kinetic energy shaping
We develop a method for generating smooth trajectories for a set of mobile robots. Given two end configurations, by tuning one parameter, the user can choose an interpolating trajectory from a continuum of curves varying from that corresponding to maintaining a rigid formation to motion of the robots toward each other The idea behind our method is to change the original constant kinetic energy metric in the configuration space and can be summarized into three steps. First, the energy of the motion as a rigid structure is decoupled from the energy of motion along directions that violate the rigid constraints. Next, the metric is "shaped" by assigning different weights to each term. Finally, geodesic flow is constructed for the modified metric. The optimal motions generated on the manifolds of rigid body displacements in 3D space or in plane, and the uniform rectilinear motion of each robot corresponding to a totally uncorrelated approach are particular cases of our general treatment.