10751860
Multilevel Diffusion Schemes for Repartitioning of Adaptive Meshes
For a large class of irregular mesh applications, the structure of the mesh changes from one phase of the computation to the next. Eventually, as the mesh evolves, the adapted mesh has to be repartitioned to ensure good load balance. If this new graph is partitioned from scratch, it may lead to an excessive migration of data among processors. In this paper, we present schemes for computing repartitionings of adaptively refined meshes that perform diffusion of vertices in a multilevel framework. These schemes try to minimize vertex movement without significantly compromising the edge-cut. We present heuristics to control the tradeoff between edge-cut and vertex migration costs. We also show that multilevel diffusion produces results with improved edge-cuts over single-level diffusion, and is better able to make use of heuristics to control the tradeoff between edge-cut and vertex migration costs than single-level diffusion.
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.
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.
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.
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. >
5147118
Location dependent query processing
The advances in wireless and mobile computing allow a mobile user to perform a wide range of aplications once limited to non-mobile hard wired computing environments. As the geographical position of a mobile user is becoming more trackable, users need to pull data which are related to their location, perhaps seeking information about unfamiliar places or local lifestyle data. In these requests, a location attribute has to be identified in order to provide more efficient access to location dependent data, whose value is determined by the location to which it is related. Local yellow pages, local events, and weather information are some of the examples of these data.
In this paper, we give a formalization of location relatedness in queries. We differentiate location dependence and location awareness and provide thorough examples to support our approach.
8409648
Secured Web access
We discuss various secured Web access schemes using dynamic and static approaches. In a static approach the access environment, that is, the set of authorized users, the mode of access, their access rights, etc., are predefined. This approach is suitable only for a static set up where the user requirements do not change frequently. In the dynamic approach, on the other hand, the authorized user set is defined when Web pages access requests appear. An interested user to the Web is authenticated by necessary information provided by the user. Once the information is verified, the user is either given conditional access, timed access, or full access only to the information relevant to the user.
11619174
Provable algorithms for parallel sweep scheduling on unstructured meshes
We present provably efficient parallel algorithms for sweep scheduling on unstructured meshes. Sweep scheduling is a commonly used technique in radiation transport problems, and involves inverting an operator by iteratively sweeping across a mesh. 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. Several heuristics have been proposed for this problem; but none of the heuristics have worst case performance guarantees. We present a simple, almost linear time randomized algorithm which (provably) gives a schedule of length at most O(log/sup 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(logmlogloglogm) times the optimal schedule for m processors. These are the first such provable guarantees for this problem. We also design a priority based list schedule using these ideas, with the same theoretical guarantee, but much better performance in practice. We complement our theoretical results with extensive empirical analysis. The results show that (i) our algorithm performs very well and has significantly better performance guarantee in practice and (ii) the algorithm compares favorably with other natural and efficient parallel algorithms proposed in the literature [S. Pautz, (2002), S. Plimpton et al., (2001)].
1921533
A superior two-phase locking algorithm and its performance
Abstract Concurrent transactions, during their execution, may conflict over common data entities. Such conflicts are resolved by concurrency control mechanisms by use of operations such as transaction rollback and/or transaction blocking. There are a number of mechanisms available and each applies these operations in different ways to resolve conflicts and claims some performance advantages. In this work we have analyzed the behavior of a new deadlock-free two-phase locking mechanism, called Cautious Waiting, and have compared its performance with other well-known mechanisms. The mechanism is conceptually quite simple; therefore it is not likely to be difficult to implement. We show that this mechanism performs consistently better under a wide range of parameter values than the other mechanisms investigated here. We also show that it is more robust, in the sense that it is less sensitive to load increases and other changes in parameter settings. In contrast, we show that one of the most commonly used mechanisms is not as robust and efficient under stress situations.