Sorting Integers on the AP1000

Sorting is one of the classic problems of computer science. Whilst well understood on sequential machines, the diversity of architectures amongst parallel systems means that algorithms do not perform uniformly on all platforms. This document describes the implementation of a radix based algorithm for sorting positive integers on a Fujitsu AP1000 Supercomputer, which was constructed as an entry in the Joint Symposium on Parallel Processing (JSPP) 1994 Parallel Software Contest (PSC94). Brief consideration is also given to a full radix sort conducted in parallel across the machine.Comment: 1994 Project Report, 23 page

AP/Linux - initial implementation

The AP1000+ is a distributed-memory parallel computer based on SuperSPARC processors, which incorporates message-passing hardware which can be accessed safely from user mode. We are in the process of porting the Linux kernel to this machine and extending it to support execution of parallel programs. This report outlines the motivation and background of this effort, and describes the current status and future directions for the work. The reader may also refer to our WWW page at http://cap.anu.edu.au/cap/projects/linux for up to date information on the progress of the port

Parallel computing in information retrieval - An updated review

The progress of parallel computing in Information Retrieval (IR) is reviewed. In particular we stress the importance of the motivation in using parallel computing for Text Retrieval. We analyse parallel IR systems using a classification due to Rasmussen [1] and describe some parallel IR systems. We give a description of the retrieval models used in parallel Information Processing.. We describe areas of research which we believe are needed

Automatic visual recognition using parallel machines

Invariant features and quick matching algorithms are two major concerns in the area of automatic visual recognition. The former reduces the size of an established model database, and the latter shortens the computation time. This dissertation, will discussed both line invariants under perspective projection and parallel implementation of a dynamic programming technique for shape recognition. The feasibility of using parallel machines can be demonstrated through the dramatically reduced time complexity. In this dissertation, our algorithms are implemented on the AP1000 MIMD parallel machines. For processing an object with a features, the time complexity of the proposed parallel algorithm is O(n), while that of a uniprocessor is O(n2). The two applications, one for shape matching and the other for chain-code extraction, are used in order to demonstrate the usefulness of our methods. Invariants from four general lines under perspective projection are also discussed in here. In contrast to the approach which uses the epipolar geometry, we investigate the invariants under isotropy subgroups. Theoretically speaking, two independent invariants can be found for four general lines in 3D space. In practice, we show how to obtain these two invariants from the projective images of four general lines without the need of camera calibration. A projective invariant recognition system based on a hypothesis-generation-testing scheme is run on the hypercube parallel architecture. Object recognition is achieved by matching the scene projective invariants to the model projective invariants, called transfer. Then a hypothesis-generation-testing scheme is implemented on the hypercube parallel architecture

Satisfiability Test with Synchronous Simulated Annealing on the Fujitsu AP1000 Massively-Parallel Multiprocessor

Solving the hard Satisfiability Problem is time consuming even for modest-sized problem instances. Solving the Random L-SAT Problem is especially difficult due to the ratio of clauses to variables. This report presents a parallel synchronous simulated annealing method for solving the Random L-SAT Problem on a large-scale distributed-memory multiprocessor. In particular, we use a parallel synchronous simulated annealing procedure, called Generalized Speculative Computation, which guarantees the same decision sequence as sequential simulated annealing. To demonstrate the performance of the parallel method, we have selected problem instances varying in size from 100-variables/425-clauses to 5000-variables/21,250-clauses. Experimental results on the AP1000 multiprocessor indicate that our approach can satisfy 99.9 percent of the clauses while giving almost a 70-fold speedup on 500 processors

A parallel architecture for query processing over a terabyte of text

The Parallel Document Retrieval Engine (PADRE) has previously demonstrated that full text scanning methods supported by parallel hardware permit powerful query constructors and rapid response to changing document collections. Extensions to PADRE have been designed and implemented which make use of parallel secondary storage to allow each processing node to handle data up to 32 times the size of its primary memory. Using the largest purchasable machine on which PADRE currently runs, these increase the maximum possible collection size to one terabyte. This paper addresses the practicality of achieving this limit and the extent to which the performance, responsiveness, functionality and scalability of the full text scanning PADRE are preserved in the extended version

The design and implementation of a parallel document retrieval engine

Document retrieval as traditionally formulated is an inherently parallel task because the document collection can be divided into N sub-collections each of which may be searched independently. Document retrieval software can potentially exploit the power and capacity of a large-scale parallel machine to improve speed, to extend the size of the largest collection which can be processed, to respond quickly to changes in the document collection and/or to increase the power and expressivity of the retrieval query language. This paper includes discussion of the issues involved in the design of a practical parallel document retrieval engine for a distributed-memory multicomputer and a description of the implementation of PADRE, a retrieval engine for the Fujitsu AP1000. Performance results are presented and scope of applicability of the techniques is discussed

Physics-based multiscale coupling for full core nuclear reactor simulation

Numerical simulation of nuclear reactors is a key technology in the quest for improvements in efficiency, safety, and reliability of both existing and future reactor designs. Historically, simulation of an entire reactor was accomplished by linking together multiple existing codes that each simulated a subset of the relevant multiphysics phenomena. Recent advances in the MOOSE (Multiphysics Object Oriented Simulation Environment) framework have enabled a new approach: multiple domain-specific applications, all built on the same software framework, are efficiently linked to create a cohesive application. This is accomplished with a flexible coupling capability that allows for a variety of different data exchanges to occur simultaneously on high performance parallel computational hardware. Examples based on the KAIST-3A benchmark core, as well as a simplified Westinghouse AP-1000 configuration, demonstrate the power of this new framework for tackling—in a coupled, multiscale manner—crucial reactor phenomena such as CRUD-induced power shift and fuel shuffle.Massachusetts Institute of Technology. Department of Nuclear Science and EngineeringIdaho National Laboratory (Contract DE-AC07-05ID14517