Investigation of reduced hypercube (RH) networks : embedding and routing capabilities

The choice of a topology for the interconnection of resources in a distributed-memory parallel computing system is a major design decision. The direct binary hypercube has been widely used for this purpose due to its low diameter and its ability to efficiently emulate other important structures. The aforementioned strong properties of the hypercube come at the cost of high VLSI complexity due to the increase in the number of communication ports and channels per node with an increase in the total number of nodes. The reduced hypercube (RH) topology, which is obtained by a uniform reduction in the number of links for each hypercube node, yields lower complexity interconnection networks compared to hypercubes with the same number of nodes, thus permitting the construction of larger parallel systems. Furthermore, it has been shown that the RH at a lower cost achieves performance comparable to that of a regular hypercube with the same number of nodes. A very important issue for the viability of the RH is to investigate the efficiency of embedding frequently used topologies into it. This thesis proposes embedding algorithms for three very important topologies, namely the ring, the torus and the binary tree. The performance of the proposed algorithms is analyzed and compared to that of equivalent embedding algorithms for the regular hypercube. It is shown that these topologies are emulated efficiently on the RH. Additionally, two already proposed routing algorithms for the RH are evaluated through simulation results

New Fault Tolerant Multicast Routing Techniques to Enhance Distributed-Memory Systems Performance

Distributed-memory systems are a key to achieve high performance computing and the most favorable architectures used in advanced research problems. Mesh connected multicomputer are one of the most popular architectures that have been implemented in many distributed-memory systems. These systems must support communication operations efficiently to achieve good performance. The wormhole switching technique has been widely used in design of distributed-memory systems in which the packet is divided into small flits. Also, the multicast communication has been widely used in distributed-memory systems which is one source node sends the same message to several destination nodes. Fault tolerance refers to the ability of the system to operate correctly in the presence of faults. Development of fault tolerant multicast routing algorithms in 2D mesh networks is an important issue. This dissertation presents, new fault tolerant multicast routing algorithms for distributed-memory systems performance using wormhole routed 2D mesh. These algorithms are described for fault tolerant routing in 2D mesh networks, but it can also be extended to other topologies. These algorithms are a combination of a unicast-based multicast algorithm and tree-based multicast algorithms. These algorithms works effectively for the most commonly encountered faults in mesh networks, f-rings, f-chains and concave fault regions. It is shown that the proposed routing algorithms are effective even in the presence of a large number of fault regions and large size of fault region. These algorithms are proved to be deadlock-free. Also, the problem of fault regions overlap is solved. Four essential performance metrics in mesh networks will be considered and calculated; also these algorithms are a limited-global-information-based multicasting which is a compromise of local-information-based approach and global-information-based approach. Data mining is used to validate the results and to enlarge the sample. The proposed new multicast routing techniques are used to enhance the performance of distributed-memory systems. Simulation results are presented to demonstrate the efficiency of the proposed algorithms

A new-generation class of parallel architectures and their performance evaluation

The development of computers with hundreds or thousands of processors and capability for very high performance is absolutely essential for many computation problems, such as weather modeling, fluid dynamics, and aerodynamics. Several interconnection networks have been proposed for parallel computers. Nevertheless, the majority of them are plagued by rather poor topological properties that result in large memory latencies for DSM (Distributed Shared-Memory) computers. On the other hand, scalable networks with very good topological properties are often impossible to build because of their prohibitively high VLSI (e.g., wiring) complexity. Such a network is the generalized hypercube (GH). The GH supports full-connectivity of its nodes in each dimension and is characterized by outstanding topological properties. In addition, low-dimensional GHs have very large bisection widths. We propose in this dissertation a new class of processor interconnections, namely HOWs (Highly Overlapping Windows), that are more generic than the GH, are highly scalable, and have comparable performance. We analyze the communications capabilities of 2-D HOW systems and demonstrate that in practical cases HOW systems perform much better than binary hypercubes for important communications patterns. These properties are in addition to the good scalability and low hardware complexity of HOW systems. We present algorithms for one-to-one, one-to-all broadcasting, all-to-all broadcasting, one-to-all personalized, and all-to-all personalized communications on HOW systems. These algorithms are developed and evaluated for several communication models. In addition, we develop techniques for the efficient embedding of popular topologies, such as the ring, the torus, and the hypercube, into 1-D and 2-D HOW systems. The objective is to show that 2-D HOW systems are not only scalable and easy to implement, but they also result in good embedding of several classical topologies