A system for routing arbitrary directed graphs on SIMD architectures

There are many problems which can be described in terms of directed graphs that contain a large number of vertices where simple computations occur using data from connecting vertices. A method is given for parallelizing such problems on an SIMD machine model that is bit-serial and uses only nearest neighbor connections for communication. Each vertex of the graph will be assigned to a processor in the machine. Algorithms are given that will be used to implement movement of data along the arcs of the graph. This architecture and algorithms define a system that is relatively simple to build and can do graph processing. All arcs can be transversed in parallel in time O(T), where T is empirically proportional to the diameter of the interconnection network times the average degree of the graph. Modifying or adding a new arc takes the same time as parallel traversal

Introduction to a system for implementing neural net connections on SIMD architectures

Neural networks have attracted much interest recently, and using parallel architectures to simulate neural networks is a natural and necessary application. The SIMD model of parallel computation is chosen, because systems of this type can be built with large numbers of processing elements. However, such systems are not naturally suited to generalized communication. A method is proposed that allows an implementation of neural network connections on massively parallel SIMD architectures. The key to this system is an algorithm permitting the formation of arbitrary connections between the neurons. A feature is the ability to add new connections quickly. It also has error recovery ability and is robust over a variety of network topologies. Simulations of the general connection system, and its implementation on the Connection Machine, indicate that the time and space requirements are proportional to the product of the average number of connections per neuron and the diameter of the interconnection network

Multistage interconnection networks : improved routing algorithms and fault tolerance

Multistage interconnection networks for use by multiprocessor systems are optimal in terms of the number of switching element, but the routing algorithms used to set up these networks are suboptimal in terms of time. The network set-up time and reliability are the major factors to affect the performance of multistage interconnection networks. This work improves routing on Benes and Clos networks as well as the fault tolerant capability. The permutation representation is examined as well as the Clos and Benes networks. A modified edge coloring algorithm is applied to the regular bipartite multigraph which represents a Clos network. The looping and parallel looping algorithms are examined and a modified Tree-Connected Computer is adopted to execute a bidirectional parallel looping algorithm for Benes networks. A new fault tolerant Clos network is presented

Parallel and Distributed Computing

The 14 chapters presented in this book cover a wide variety of representative works ranging from hardware design to application development. Particularly, the topics that are addressed are programmable and reconfigurable devices and systems, dependability of GPUs (General Purpose Units), network topologies, cache coherence protocols, resource allocation, scheduling algorithms, peertopeer networks, largescale network simulation, and parallel routines and algorithms. In this way, the articles included in this book constitute an excellent reference for engineers and researchers who have particular interests in each of these topics in parallel and distributed computing

Fault-tolerant interconnection networks for multiprocessor systems

Interconnection networks represent the backbone of multiprocessor systems. A failure in the network, therefore, could seriously degrade the system performance. For this reason, fault tolerance has been regarded as a major consideration in interconnection network design. This thesis presents two novel techniques to provide fault tolerance capabilities to three major networks: the Baseline network, the Benes network and the Clos network. First, the Simple Fault Tolerance Technique (SFT) is presented. The SFT technique is in fact the result of merging two widely known interconnection mechanisms: a normal interconnection network and a shared bus. This technique is most suitable for networks with small switches, such as the Baseline network and the Benes network. For the Clos network, whose switches may be large for the SFT, another technique is developed to produce the Fault-Tolerant Clos (FTC) network. In the FTC, one switch is added to each stage. The two techniques are described and thoroughly analyzed

Flexible LDPC Decoder Architectures

Flexible channel decoding is getting significance with the increase in number of wireless standards and modes within a standard. A flexible channel decoder is a solution providing interstandard and intrastandard support without change in hardware. However, the design of efficient implementation of flexible low-density parity-check (LDPC) code decoders satisfying area, speed, and power constraints is a challenging task and still requires considerable research effort. This paper provides an overview of state-of-the-art in the design of flexible LDPC decoders. The published solutions are evaluated at two levels of architectural design: the processing element (PE) and the interconnection structure. A qualitative and quantitative analysis of different design choices is carried out, and comparison is provided in terms of achieved flexibility, throughput, decoding efficiency, and area (power) consumption

Tree Machines: Architectures and Algorithms A Survey Paper

Recent advances in very large scale integrated (VLSI) circuit technology have lead to a surge in research aimed at finding new computer organizations that support a great deal of concurrency computer organizations based on tree structures appear well-suited to several kinds of parallel computations. In this paper we will discuss the performance of tree machines as well as Issues related to their implementation in VLSI. Examples of tree machines are presented, with an emphasis on the way the processing elements communicate in the machine. A taxonomy of tree algorithms based on a taxonomy of parallel algorithms proposed by Kung in 1979 is Introduced. Examples of tree algorithms are also given

The connection machine

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1988.Bibliography: leaves 134-157.by William Daniel Hillis.Ph.D

Architecture and Analysis for Next Generation Mobile Signal Processing.

Mobile devices have proliferated at a spectacular rate, with more than 3.3 billion active cell phones in the world. With sales totaling hundreds of billions every year, the mobile phone has arguably become the dominant computing platform, replacing the personal computer. Soon, improvements to today’s smart phones, such as high-bandwidth internet access, high-definition video processing, and human-centric interfaces that integrate voice recognition and video-conferencing will be commonplace. Cost effective and power efficient support for these applications will be required. Looking forward to the next generation of mobile computing, computation requirements will increase by one to three orders of magnitude due to higher data rates, increased complexity algorithms, and greater computation diversity but the power requirements will be just as stringent to ensure reasonable battery lifetimes. The design of the next generation of mobile platforms must address three critical challenges: efficiency, programmability, and adaptivity. The computational efficiency of existing solutions is inadequate and straightforward scaling by increasing the number of cores or the amount of data-level parallelism will not suffice. Programmability provides the opportunity for a single platform to support multiple applications and even multiple standards within each application domain. Programmability also provides: faster time to market as hardware and software development can proceed in parallel; the ability to fix bugs and add features after manufacturing; and, higher chip volumes as a single platform can support a family of mobile devices. Lastly, hardware adaptivity is necessary to maintain efficiency as the computational characteristics of the applications change. Current solutions are tailored specifically for wireless signal processing algorithms, but lose their efficiency when other application domains like high definition video are processed. This thesis addresses these challenges by presenting analysis of next generation mobile signal processing applications and proposing an advanced signal processing architecture to deal with the stringent requirements. An application-centric design approach is taken to design our architecture. First, a next generation wireless protocol and high definition video is analyzed and algorithmic characterizations discussed. From these characterizations, key architectural implications are presented, which form the basis for the advanced signal processor architecture, AnySP.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/86344/1/mwoh_1.pd