Adaptive fault-tolerant routing in hypercube multicomputers

A connected hypercube with faulty links and/or nodes is called an injured hypercube. To enable any non-faulty node to communicate with any other non-faulty node in an injured hypercube, the information on component failures has to be made available to non-faulty nodes so as to route messages around the faulty components. A distributed adaptive fault tolerant routing scheme is proposed for an injured hypercube in which each node is required to know only the condition of its own links. Despite its simplicity, this scheme is shown to be capable of routing messages successfully in an injured hypercube as long as the number of faulty components is less than n. Moreover, it is proved that this scheme routes messages via shortest paths with a rather high probabiltiy and the expected length of a resulting path is very close to that of a shortest path. Since the assumption that the number of faulty components is less than n in an n-dimensional hypercube might limit the usefulness of the above scheme, a routing scheme is introduced based on depth-first search which works in the presence of an arbitrary number of faulty components. Due to the insufficient information on faulty components, the paths chosen by the above scheme may not always be the shortest. To guarantee that all messages be routed via shortest paths, it is proposed that every mode be equipped with more information than that on its own links. The effects of this additional information on routing efficiency are analyzed, and the additional information to be kept at each node for the shortest path routing is determined. Several examples and remarks are also given to illustrate the results

Reliability Analysis of the Hypercube Architecture.

This dissertation presents improved techniques for analyzing network-connected (NCF), 2-connected (2CF), task-based (TBF), and subcube (SF) functionality measures in a hypercube multiprocessor with faulty processing elements (PE) and/or communication elements (CE). These measures help study system-level fault tolerance issues and relate to various application modes in the hypercube. Solutions discussed in the text fall into probabilistic and deterministic models. The probabilistic measure assumes a stochastic graph of the hypercube where PE\u27s and/or CE\u27s may fail with certain probabilities, while the deterministic model considers that some system components are already failed and aims to determine the system functionality. For probabilistic model, MIL-HDBK-217F is used to predict PE and CE failure rates for an Intel iPSC system. First, a technique called CAREL is presented. A proof of its correctness is included in an appendix. Using the shelling ordering concept, CAREL is shown to solve the exact probabilistic NCF measure for a hypercube in time polynomial in the number of spanning trees. However, this number increases exponentially in the hypercube dimension. This dissertation, then, aims to more efficiently obtain lower and upper bounds on the measures. Algorithms, presented in the text, generate tighter bounds than had been obtained previously and run in time polynomial in the cube dimension. The proposed algorithms for probabilistic 2CF measure consider PE and/or CE failures. In attempting to evaluate deterministic measures, a hybrid method for fault tolerant broadcasting in the hypercube is proposed. This method combines the favorable features of redundant and non-redundant techniques. A generalized result on the deterministic TBF measure for the hypercube is then described. Two distributed algorithms are proposed to identify the largest operational subcubes in a hypercube C\sb{n} with faulty PE\u27s. Method 1, called LOS1, requires a list of faulty components and utilizes the CMB operator of CAREL to solve the problem. In case the number of unavailable nodes (faulty or busy) increases, an alternative distributed approach, called LOS2, processes m available nodes in O(mn) time. The proposed techniques are simple and efficient

Near-optimal broadcast in all-port wormhole-routed hypercubes using error-correcting codes

A new broadcasting method is presented for hypercubes with wormhole routing mechanism. The communication model assumed allows an n-dimensional hypercube to have at most n concurrent I/O communication along its ports. It assumes a distance insensitivity of (n + 1) with no intermediate reception capability for the nodes. The approach is based on determination of the set of nodes called stations in the hypercube. Once stations are identified, node disjoint paths are formed from the source to all stations. The broadcasting is accomplished first by sending the message to all stations, which will inform the rest of the nodes. To establish node-disjoint paths between the source node and all stations, we introduce a new routing strategy. We prove that multicasting can be done in one routing step as long as the number of destination nodes are at most n in an n-dimensional hypercube. The number of broadcasting steps using our routing is equal to or smaller than that obtained in an earlier work; this number is optimal for all hypercube dimensions n ≤ 12, except for n = 10

A new strategy for processors allocation in an n-cube multiprocessor

In this paper we will describe two known strategies for static processors allocation in an n-cube multiprocessor, namely the buddy system strategy and the gray code strategy and then propose a new strategy that outperforms the first by (n-k+1) and the second by (n-k+1)/2 in cube recognition. Furthermore, our strategy is suitable for static as well as dynamic processors allocation and it results in a less system fragmentation, more subcubes recognition, and higher fault tolerance. We also introduce an extension to our strategy that will enhance the performance drastically so that our algorithm together with the extension will outperform the buddy system by a factor of [k(n-k)+1] and the gray strategy by [k(n-k)+1]/2 in cube recognition. The implementation details of these algorithms are also described

Investigation of the robustness of star graph networks

The star interconnection network has been known as an attractive alternative to n-cube for interconnecting a large number of processors. It possesses many nice properties, such as vertex/edge symmetry, recursiveness, sublogarithmic degree and diameter, and maximal fault tolerance, which are all desirable when building an interconnection topology for a parallel and distributed system. Investigation of the robustness of the star network architecture is essential since the star network has the potential of use in critical applications. In this study, three different reliability measures are proposed to investigate the robustness of the star network. First, a constrained two-terminal reliability measure referred to as Distance Reliability (DR) between the source node u and the destination node I with the shortest distance, in an n-dimensional star network, Sn, is introduced to assess the robustness of the star network. A combinatorial analysis on DR especially for u having a single cycle is performed under different failure models (node, link, combined node/link failure). Lower bounds on the special case of the DR: antipode reliability, are derived, compared with n-cube, and shown to be more fault-tolerant than n-cube. The degradation of a container in a Sn having at least one operational optimal path between u and I is also examined to measure the system effectiveness in the presence of failures under different failure models. The values of MTTF to each transition state are calculated and compared with similar size containers in n-cube. Meanwhile, an upper bound under the probability fault model and an approximation under the fixed partitioning approach on the ( n-1)-star reliability are derived, and proved to be similarly accurate and close to the simulations results. Conservative comparisons between similar size star networks and n-cubes show that the star network is more robust than n-cube in terms of ( n-1)-network reliability

Implementation of processor allocation in an N-Cube multiprocessor on Macintosh

The processor allocation in an n-dimensional hypercube multiprocessor using buddy strategy, gray code strategy, and a new strategy is implemented on Macintosh. Our implementations show that when processor relinquishment is not considered (i.e. static allocation), all these strategies are optimal in the sense that each incoming request sequence is always assigned to a minimal subcube. Our implementations also show that the gray code strategy outperforms the buddy strategy in detecting the availability of subcubes, and furthermore, when some faulty processors are considered or processors are allocated dynamically, the new strategy does better than the buddy strategy or gray code strategy in subcube recognition

Processor allocation for partitionable multiprocessor systems

The processor allocation problem in an n-dimensional hypercube multipro-cessor is similar to the conventional memory allocation problem. The main objective is to maximize the utilization of available resources as well as minimize the inherent system fragmentation. In this thesis, a new processor allocation strategy is proposed, and compared with the existing strategies, such as, the Buddy strategy, the Single Gray Code strategy (SGC), the Multiple Gray Code (MGC), and the Maximal Set of Subcubes (MSS). We will show that our proposed processor allocation strategy outperforms the existing strategies, by having the advantage of being able to allocate unused processors to other jobs/algorithms