16852145
The infinity Lambda test
In this paper, WC proposed the infinity Lambda test. The infinity Lambda test can be applied IO deal with data dependence of coupled arrays with symbolic (urrknowr, at compile time) bounds. Experimental data reflecting the effect of the infinity Lambda test are also presented.
39715098
A Requirement-Based Project Estimation Approach
12245644
Multicast communication in wormhole-routed star graph interconnection networks
Multicast, an important communication mechanism, is frequently applied in parallel computing. The star graph interconnection network, when compared with the hypercube network, being with low degree and small diameter, has been recognized to be an attractive alternative to the popular hypercube network. In this paper, we derive a node labeling formula based on a hamiltonian path and propose four efficient multicast routing schemes in wormhole-routed star networks with multidestination routing capability. All of the four proposed schemes are path-based and deadlock-free. The first scheme, dual-path routing, sends the message in parallel through two independent paths (toward high label nodes and low label nodes). The second one, shortcut-node-based dual-path routing, is similar to dual-path routing except that the routing tries to find a shortcut node to route the message as soon as possible to reduce the length of transmission path. The third one, multipath routing, is a multiple dual-path routing strategy that includes source-to-relay and relay-to-destination phases. The last scheme, proximity grouping routing, is similar to multipath routing except that in the partitioning step of source and destination nodes the relation of spatial locality of nodes is also taken into account to reduce the length of transmission paths. Finally, the experimental results are given to show that the performance based on unicast-based and traditional hamiltonian-path routing schemes can be improved significantly by the four proposed routing schemes respectively.
7900750
A Web-service oriented framework for building SCORM compatible learning management systems
Managing the large amount of learning content involved in the development of an expandable learning management system (LMS) is a critical task for most educational organizations. In designing such a system, consideration must be given not only to the requirement of instructors and students, but also to the adaptive qualities of the system itself, because of the rapidly changing software environment. Unlike most enterprises, educational organization can't afford high system maintenance. Development of a flexible, expandable and reliable learning management system is, therefore, imperative. This paper proposes a Web service oriented framework in building a sharable content object reference model (SCORM) compatible LMS. We integrated the SCORM concept with distributed computing technologies to build the components of the LMS and demonstrate how these services can be configured to create a complete system. This framework increases reusability and reduces the maintenance requirements of the LMS. It provides a way for small educational organizations, with limited resources, to build a complete SCORM compatible LMS. In such an ideal situation, the content provider not only provides the content, but also the service for the consumers of that content.
22379683
Analyzing reconfigurable algorithms for managing replicated data
We analyze reconfigurable algorithms for managing replicated data to determine how often one should detect and react to failure conditions so that reorganization operations can be performed at the appropriate time to improve the availability of replicated data. We use dynamic voting as a case study to reveal design trade-offs for designing such reconfigurable algorithms and illustrate how often failure detection and reconfiguration activities should be performed so as to maximize data availability. Stochastic Petri nets are used as a tool to facilitate our analysis.
37782928
A multi-dimensional version of the I test
Abstract Two-dimensional arrays with linear subscripts occur quite frequently in real programs. In general, for multi-dimensional linear arrays under constant bounds the Lambda test is an efficient data dependence method to check whether there exist real solutions. In this paper, we propose a multi-dimensional version of the I test, the multi-dimensional I test, that can be applied to testing whether there are integer solutions for multi-dimensional linear arrays under constant limits. Experiments with benchmark showing the effects of the multi-dimensional I test on testing precision and testing efficiency are also presented.
13097054
RQL: Global Placement via Relaxed Quadratic Spreading and Linearization
This paper describes a simple and effective quadratic placement algorithm called RQL. We show that a good quadratic placement, followed by local wirelength-driven spreading can produce excellent results on large-scale industrial ASIC designs. As opposed to the current top performing academic placers [4,7,11], RQL does not embed a linearization technique within the solver. Instead, it only requires a simpler, pure quadratic objective function in the spirit of [8,10,23]. Experimental results show that RQL outperforms all available academic placers on the ISPD-2005 placement contest benchmarks. In particular, RQL obtains an average wire- length improvement of 2.8%, 3.2%, 5.4%, 8.5%, and 14.6% versus mPL6 [5], NTUPlaceS [7], Kraflwerk [20], APlace2.0 [11], and Capo10.2 [18], respectively. In addition, RQL is three, seven, and ten times faster than mpL6, Capo10.2, and APlace2.0, respectively. On the ISPD-2006 placement contest benchmarks, on average, RQL obtains the best scaled wirelength among all available academic placers.
776801
Optimizing SOC Test Resources using Dual Sequences
In this paper, we propose a new data structure called dual sequences to represent SOC test schedules. Dual sequences are used together with a simulated annealing based procedure to optimize the SOC test application time and tester resources. The problems we consider are generation of optimal test schedules for SOCs and minimizing tester memory and test channels. Results of experiments conducted on ITC’02 benchmark SOCs show the effectiveness of the proposed method.
24078054
Greedy wire-sizing is linear time
The greedy wire-sizing algorithm (GWSA) has been experimentally shown to be very efficient, but no mathematical analysis on its convergence rate has ever been reported. In this paper, we consider GWSA for continuous wire sizing. We prove that GWSA converges linearly to the optimal solution, which implies that the run time of GWSA is linear with respect to the number of wire segments for any fixed precision of the solution. Moreover, we also prove that this is true for any starting solution. This is a surprising result because previously it was believed that in order to guarantee convergence, GWSA had to start from a solution in which every wire segment is set to the minimum (or maximum) possible width. Our result implies that GWSA can use a good starting solution to achieve faster convergence. We demonstrate this point by showing that the minimization of maximum delay and the minimization of area subject to maximum delay bound using Lagrangian relaxation can be sped up by more than 50%.
27561759
Splice site prediction using support vector machines with a Bayes kernel
One of the most important tasks in correctly annotating genes in higher organisms is to accurately locate the DNA splice sites. Although relatively high accuracy has been achieved by existing methods, most of these prediction methods are computationally extensive. Due to the enormous amount of DNA sequences to be processed, the computational speed is an important issue to consider. In this paper, we present a new machine learning method for predicting DNA splice sites, which first applies a Bayes feature mapping (kernel) to project the data into a new feature space and then uses a linear Support Vector Machine (SVM) as a classifier to recognize the true splice sites. The computation time is linear to the number of sequences tested, while the performance is notably improved compared with the Naive Bayes classifier in terms of classification accuracy, precision, and recall. Our classification results are also comparable to the solution quality obtained by the SVMs with polynomial kernels, while the speed of our proposed method is significantly faster. This is a notable improvement in computational modeling considering the huge amount of DNA sequences to be processed.
34361185
Dilation-5 embedding of 3-dimensional grids into hypercubes
We present an algorithm to map the nodes of a 3-dimensional grid to the nodes of its optimal hypercube on a one-to-one basis with dilation at most 5.<<ETX>>