On the performance of routing algorithms in wormhole-switched multicomputer networks

This paper presents a comparative performance study of adaptive and deterministic routing algorithms in wormhole-switched hypercubes and investigates the performance vicissitudes of these routing schemes under a variety of network operating conditions. Despite the previously reported results, our results show that the adaptive routing does not consistently outperform the deterministic routing even for high dimensional networks. In fact, it appears that the superiority of adaptive routing is highly dependent to the broadcast traffic rate generated at each node and it begins to deteriorate by growing the broadcast rate of generated message

General broadcasting algorithms in one-port wormhole routed hypercubes

Wormhole routing has been accepted as an efficient switching mechanism in point-to-point interconnection networks. Here the network resource, i.e. node buffers and communication channels, are effectively utilized to deliver message across the network; We consider the problem of broadcasting a message in the hypercue equipped with the wormhole switching mechanism. The model is a generalization of an earlier work and considers a broadcast path-length of {dollar}m\ (1\leq m\leq n{dollar}) in the n-cube with a single-port communication capability. In this thesis, the scheme of e-cube and a Gray code path routing and intermediate reception capability have been adopted in order to solve the problem of broadcasting in one-port wormhole routed hypercubes. Two methods have been suggested; one is based on utilizing the Gray codes (Gray code path-based routing), while the other is based on the recursive partitioning of the cube (cube-based routing). The number of routing steps in both methods are compared to those in the previous results, as well as to the lower bounds derived based on the path-length m assumption. A cube-based and a path-based algorithm give {dollar}T(R)+(k\sb{c}+1)T(m){dollar} and {dollar}k\sb{G} +T(m){dollar} routing steps, respectively. By comparison with routing steps of both algorithms, the performance of the path-based algorithm shows better than that of the cube-based; The results of this work are significant and can be used for immediate implementation in contemporary machines most of which are equipped with wormhole routing and serial communication capability

Replication Techniques for Speeding up Parallel Applications on Distributed Systems

This paper discusses the design choices involved in replicating objects and their effect on performance. Important issues are: how to maintain consistency among different copies of an object; how to implement changes to objects; and which strategy for object replication to use. We have implemented several options to determine which ones are most efficient

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

Efficient hypercube communications

Hypercube algorithms may be developed for a variety of communication-intensive tasks such as sending a message from one node to another, broadcasting a message from one node to all others, broadcasting a message from each node to all others, all-to-all personalized communication, one-to-all personalized communication, and exchanging messages between nodes via fixed permutations. All these communication patterns are special cases of many-to-many personalized communication. The problem of many-to-many personalized communication is investigated here. Two routing algorithms for many-to-many personalized communication are presented here. The algorithms proposed yield very high performance with respect to the number of time steps and packet transmissions. The first algorithm yields high performance through attempts to equibalance the number of messages at intermediate nodes. This technique tries to avoid creating a bottleneck at any node and thus reduces the total communication time. The second algorithm yields high performance through one-step time-lookahead equibalancing. It chooses from the candidate intermediate nodes the one which will probably have the minimum number of messages in the next cycle

Parallel Programming Using Shared Objects and Broadcasting

The two major design approaches taken to build distributed and parallel computer systems, multiprocessing and multicomputing, are discussed. A model that combines the best properties of both multiprocessor and multicomputer systems, easy-to-build hardware, and a conceptually simple programming model is presented. Using this model, a programmer defines and invokes operations on shared objects, the runtime system handles reads and writes on these objects, and the reliable broadcast layer implements indivisible updates to objects using the sequencing protocol. The resulting system is easy to program, easy to build, and has acceptable performance on problems with a moderate grain size in which reads are much more common than writes. Orca, a procedural language whose sequential constructs are roughly similar to languages like C or Modula 2 but which also supports parallel processes and shared objects and has been used to develop applications for the prototype system, is described

A Comparison of Two Paradigms for Distributed Shared Memory

This paper compares two paradigms for Distributed Shared Memory on loosely coupled computing systems: the shared data-object model as used in Orca, a programming language specially designed for loosely coupled computing systems and the Shared Virtual Memory model. For both paradigms two systems are described, one using only point-to-point messages, the other using broadcasting as well. The two paradigms and their implementations are described briefly. Their performances on four applications are compared: the travelling-salesman problem, alpha-beta search, matrix multiplication and the all-pairs shortest paths problem. The relevant measurements were obtained on a system consisting of 10 MC68020 processors connected by an Ethernet. For comparison purposes, the applications have also been run on a system with physical shared memory. In addition, the paper gives measurements for the first two applications above when Remote Procedure Call is used as the communication mechanism. The measurements show that both paradigms can be used efficiently for programming large-grain parallel applications, with significant speed-ups. The structured shared data-object model achieves the highest speed-ups and is easiest to program and to debug. KEYWORDS: Amoeba Distributed shared memory Distributed programming Orc

Distributed Programming with Shared Data

Until recently, at least one thing was clear about parallel programming: tightly coupled (shared memory) machines were programmed in a language based on shared variables and loosely coupled (distributed) systems were programmed using message passing. The explosive growth of research on distributed systems and their languages, however, has led to several new methodologies that blur this simple distinction. Operating system primitives (e.g., problem-oriented shared memory, Shared Virtual Memory, the Agora shared memory) and languages (e.g., Concurrent Prolog, Linda, Emerald) for programming distributed systems have been proposed that support the shared variable paradigm without the presence of physical shared memory. In this paper we will look at the reasons for this evolution, the resemblances and differences among these new proposals, and the key issues in their design and implementation. It turns out that many implementations are based on replication of data. We take this idea one step further, and discuss how automatic replication (initiated by the run time system) can be used as a basis for a new model, called the shared data-object model, whose semantics are similar to the shared variable model. Finally, we discuss the design of a new language for distributed programming, Orca, based on the shared data-object model. 1

The Effect Of Hot Spots On The Performance Of Mesh--Based Networks

Direct network performance is affected by different design parameters which include number of virtual channels, number of ports, routing algorithm, switching technique, deadlock handling technique, packet size, and buffer size. Another factor that affects network performance is the traffic pattern. In this thesis, we study the effect of hotspot traffic on system performance. Specifically, we study the effect of hotspot factor, hotspot number, and hot spot location on the performance of mesh-based networks. Simulations are run on two network topologies, both the mesh and torus. We pay more attention to meshes because they are widely used in commercial machines. Comparisons between oblivious wormhole switching and chaotic packet switching are reported. Overall packet switching proved to be more efficient in terms of throughput when compared to wormhole switching. In the case of uniform random traffic, it is shown that the differences between chaotic and oblivious routing are indistinguishable. Networks with low number of hotspots show better performance. As the number of hotspots increases network latency tends to increase. It is shown that when the hotspot factor increases, performance of packet switching is better than that of wormhole switching. It is also shown that the location of hotspots affects network performance particularly with the oblivious routers since their achieved latencies proved to be more vulnerable to changes in the hotspot location. It is also shown that the smaller the size of the network the earlier network saturation occurs. Further, it is shown that the chaos router’s adaptivity is useful in this case. Finally, for tori, performance is not greatly affected by hotspot presence. This is mostly due to the symmetric nature of tori