Parallel Computers and Complex Systems

We present an overview of the state of the art and future trends in high performance parallel and distributed computing, and discuss techniques for using such computers in the simulation of complex problems in computational science. The use of high performance parallel computers can help improve our understanding of complex systems, and the converse is also true --- we can apply techniques used for the study of complex systems to improve our understanding of parallel computing. We consider parallel computing as the mapping of one complex system --- typically a model of the world --- into another complex system --- the parallel computer. We study static, dynamic, spatial and temporal properties of both the complex systems and the map between them. The result is a better understanding of which computer architectures are good for which problems, and of software structure, automatic partitioning of data, and the performance of parallel machines

Parallel Computation on Hypercube-Like Machines.

The hypercube interconnection network has been recognized to be very suitable for a parallel computing architecture due to its attractive topological properties. Recently, several modified hypercubes have been propose to improve the performance of a hypercube. This dissertation deals with two modified hypercubes, the X-hypercube and the Z-cube. The X-hypercube is a variant of the hypercube, with the same amount of hardware but a diameter of only $\lceil$(n + 1)/2$\rceil$ in a hypercube of dimension n. The Z-cube has only 75 percent of the edges of a hypercube with the same number vertices and the same diameter as the hypercube. In this dissertation, we investigate some topological properties and the effectiveness of the X-hypercube and the Z-cube in their combinatorial and computational aspects. We give the optimal or nearly optimal data communication algorithms including routing, broadcasting, and census function for the X-hypercube and the Z-cube. We also give the optimal embedding algorithms between the X-hypercube and the hypercube. It is shown that the average distance between vertices in a X-hypercube is roughly 13/16 of that in a hypercube. This implies that a X-hypercube achieves the better average communication performance than a hypercube. In addition, a set of fundamental SIMD algorithms for a X-hypercube is given. Our results indicate that the X-hypercube makes an improvement in performance over the hypercube, but not as much as the reduction in a diameter, and the Z-cube is a good alternative for the hypercube as far as the VLSI implementation is of major concern

A C* development environment for the Meiko CS-2 multicomputer

With sequential computing technology reaching its speed limits, parallel processing is emerg­ing as the key to very-high-speed computation. However, developing a parallel program is by no means a simple task; neither is analyzing the performance of parallel programs. C* is a high-level data-parallel language that hides explicit message passing and provides an easy-to-understand virtual view of parallel computation. C* is a portable language for which a retargetable compiler has been implemented for mesh-connected MIMD multicom­puters. Together with the compiler, a C* run.time library has been implemented using Intel NXlib. This project is aimed at developing a Cstar Development Environment-CSD for the Meiko CS-2 multicomputer. It includes three tasks. One is building a Meiko specific ver­sion of the C* run-time library, another is comparing the performance of the Meiko version with the performance of the original one, and the last is developing a graphical tool for C* programming and performance analysis. This paper introduces the instruments in CSDE and discusses in some detail the major implementation issues

Small-world interconnection networks for large parallel computer systems

The use of small-world graphs as interconnection networks of multicomputers is proposed and analysed in this work. Small-world interconnection networks are constructed by adding (or modifying) edges to an underlying local graph. Graphs with a rich local structure but with a large diameter are shown to be the most suitable candidates for the underlying graph. Generation models based on random and deterministic wiring processes are proposed and analysed. For the random case basic properties such as degree, diameter, average length and bisection width are analysed, and the results show that a fast transition from a large diameter to a small diameter is experienced when the number of new edges introduced is increased. Random traffic analysis on these networks is undertaken, and it is shown that although the average latency experiences a similar reduction, networks with a small number of shortcuts have a tendency to saturate as most of the traffic flows through a small number of links. An analysis of the congestion of the networks corroborates this result and provides away of estimating the minimum number of shortcuts required to avoid saturation. To overcome these problems deterministic wiring is proposed and analysed. A Linear Feedback Shift Register is used to introduce shortcuts in the LFSR graphs. A simple routing algorithm has been constructed for the LFSR and extended with a greedy local optimisation technique. It has been shown that a small search depth gives good results and is less costly to implement than a full shortest path algorithm. The Hilbert graph on the other hand provides some additional characteristics, such as support for incremental expansion, efficient layout in two dimensional space (using two layers), and a small fixed degree of four. Small-world hypergraphs have also been studied. In particular incomplete hypermeshes have been introduced and analysed and it has been shown that they outperform the complete traditional implementations under a constant pinout argument. Since it has been shown that complete hypermeshes outperform the mesh, the torus, low dimensional m-ary d-cubes (with and without bypass channels), and multi-stage interconnection networks (when realistic decision times are accounted for and with a constant pinout), it follows that incomplete hypermeshes outperform them as well

High performance systems

This document provides a written compilation of the presentations and viewgraphs from the 1994 Conference on High Speed Computing given at the High Speed Computing Conference, {open_quotes}High Performance Systems,{close_quotes} held at Gleneden Beach, Oregon, on April 18 through 21, 1994