Jerry L. Trahan

Optimally Scaling Permutation Routing on Reconfigurable Linear Arrays with Optical Buses

We present an optimal and scalable permutation routing algorithm for three reconfigurable models based on linear arrays that allow pipelining of information through an optical bus. Specifically, for any P?N, our algorithm routes any permutation of N elements on a P-processor model optimally in O(NP) steps. This algorithm extends naturally to one for routing h-relations optimally in O(h) steps. We also establish the equivalence of the three models: linear array with a reconfigurable pipelined bus system, linear pipelined bus, and pipelined optical bus. This implies an automatic translation of algorithms (without loss of speed or efficiency) among these models.

Improved lower bounds on the reliability of hypercube architectures

The hypercube topology, also known as the Boolean n-cube, has recently been used for multiprocessing systems. The paper considers two structural-reliability models, namely, terminal reliability (TR) and network reliability (NR), for the hypercube. Terminal (network) reliability is defined as the probability that there exists a working path connecting two (all) nodes. There are no known polynomial time algorithms for exact computation of TR or NR for the hypercube. Thus, lower-bound computation is a better alternative, because it is more efficient computationally, and the system will be at least as reliable as the bound. The paper presents algorithms to compute lower bounds on TR and NR for the hypercube considering node and/or link failures. These algorithms provide tighter bounds for both TR and NR than known results and run in time polynomial in the cube dimension n, specifically, within time O(n/sup 2/). >

Tighter and Broader Complexity Results for Reconfigurable Models

A number of models allow processors to reconfigure their local connections to create and alter various bus configurations. This reconfiguration enables development of fast algorithms for fundamental problems, many in constant time. We investigate the ability of such models by relating time and processor bounded complexity classes defined for these models to each other and to those of more traditional models. In this work, (1) we tighten the relations for some of the models, placing them more precisely in relation to each other than was previously known (particularly, the Linear Reconfigurable Network and Directed Reconfigurable Network relative to circuit-defined classes), and (2) we include models (Fusing-Restricted Reconfigurable Mesh and Pipelined Reconfigurable Mesh) not previously considered.

Neural-network techniques for software-quality evaluation

Software quality modeling involves identifying fault-prone modules and predicting the number of errors in the early stages of the software development life cycle. This paper investigates the viability of several neural network techniques for software quality evaluation (SQE). We have implemented a principal component analysis technique (used in SQE) with two different neural network training rules, and have classified software modules as fault-prone or nonfault-prone using software complexity metric data. Our results reveal that neural network techniques provide a good management tool in a software engineering environment.

Secure Referee Selection for Fair and Responsive Peer-to-Peer Gaming

Peer-to-Peer (P2P) architectures for Massively Multiplayer Online Games (MMOG) provide better scalability than Client/Server (C/S), however, they increase the possibility of cheating. Recently proposed P2P protocols use trusted referees that simulate/validate the game to provide security equivalent to C/S. When selecting referees from un-trusted peers, selecting non-colluding referees becomes critical. Further, referees should be selected such that the range and length of delays to players is minimized (maximizing game fairness and responsiveness). In this paper we formally define the referee selection problem and propose two secure referee selection algorithms, SRS-1 and SRS-2, to solve it. Both algorithms ensure the probability of corrupt referees controlling a zone/region is below a pre-defined limit, while attempting to maximize responsiveness and fairness. The trade-off between responsiveness and fairness is adjustable for both algorithms. Simulations of three different scenarios show the effectiveness of our algorithms.

Adaptive image filtering using run-time reconfiguration

In adaptive image filtering, the coefficients of the filtering window can change in response to local conditions as the window moves from pixel to pixel over an image. This appears to preclude a solution approach involving run-time reconfiguration (RTR), as efficient use of RTR depends on a sufficient stretch of computing time between reconfiguring phases. This paper applies RTR to solve the adaptive image filtering problem by capitalizing on the regular appearance of each pixel in multiple filtering windows. We describe our approach and present simulation results demonstrating its merit.

Using Bus Linearization to Scale the Reconfigurable Mesh

The reconfigurable mesh (R-Mesh) has drawn much interest in recent years due, in part, to its ability to admit extremely fast algorithms for a large number of problems. The unrestricted R-Mesh creates a great variety of bus shapes that facilitate algorithm design and reduce running time. In this paper, we present a bus linearization procedure that transforms an arbitrary nonlinear bus configuration of an R-Mesh into an equivalent acyclic linear bus configuration implementable on a linear R-Mesh (LR-Mesh), a weaker version of the unrestricted R-Mesh. This procedure gives an algorithm designer the liberty of using buses of arbitrary shape, while automatically translating the algorithm to run on a simpler platform. We illustrate our bus linearization method through two important applications. The first leads to a faster scaling simulation for the unrestricted R-Mesh. This scaling simulation has an overhead of logN (smaller than the logPlogNP overhead of the previous fastest scaling simulation) and uses an exclusive write LR-Mesh as the simulating model; prior simulations needed concurrent write. The second application adapts algorithms designed for R-Meshes to run on models with pipelined optical buses.

Broadcast reliability evaluation of multistage interconnection networks

The authors propose a simple and efficient algorithm for the reliability evaluation of a shuffle exchange network with extra stage (SENE) by a two-step method, called the sum of disjoint products method. Reliability expressions are derived for cases in which all outputs are to be reached (broadcast reliability) and in which only a subset of outputs of size s is to be reached (s-terminal reliability). Once the broadcast tree terms are obtained, a sum of disjoint products is generated for the reliability expression by a relatively small number of calculations.<<ETX>>

Scaling simulation of the fusing-restricted reconfigurable mesh

This paper deals with the ability of a model to adapt algorithm instances of different sizes to run on a given model size without significant loss of efficiency. The overhead in simulating a step of a large instance of the model on a smaller instance can quantify this ability. A reconfigurable mesh (R-Mesh) can use its bus structure as a computational resource, presenting an obstacle to efficiently scaling down algorithms to run on a smaller R-Mesh. We construct a scaling simulation of a Fusing-Restricted Reconfigurable Mesh (FR-Mesh), a version of the R-Mesh. The overhead of this simulation depends only on the simulating machine size and not on the simulated machine size. Previously, the R-Mesh was not known to admit such a simulation overhead without significantly reducing its computational power. The small overhead holds importance for flexibility in algorithm design and for running algorithms with various input sizes on an available model of given size. The results of this paper extend to a variety of concurrent write rules and also translate to an improved scaling simulation of an unrestricted R-Mesh.

List Ranking and Graph Algorithms on the Reconfigurable Multiple Bus Machine

The Reconfigurable Multiple Bus Machine (RMBM) is a model of parallel computation based on reconfigurable buses. We present constant time algorithms for list ranking, integer sorting and a number of fundamental graph problems on the RMBM. The algorithms are more efficient in terms of processors than the corresponding PARBS algorithms. The algorithms demonstrate some of the potential for computation available in the ability to manipulate communication paths as a vital part of computation.