Narrow Results

This paper describes research conducted at ONERA using the Transputer as building block for experimentation in the field of scientific multiprocessing. The first part describes our experimental systems based on T800–20 Transputers and gives performance measurements of some kernel operations. The second part is devoted to the implementation of two simulation codes on a network of forty Transputers. The first concerns a finite element dynamic analysis of a large scale structural problem. The aim is to compute the dynamic response of a clamped cylindrical beam subjected to a time dependent force. The second code simulates the behaviour of particles in an accelerator. This chromaticity correction code, called PATRICIA [17], has been adapted to our multi-Transputer system. All these experiments were conducted using OCCAM2, the parallel programming language of the Transputer.

The parallelization of a structurally inhomogeneous Metropolis Monte Carlo particle/ potential problem was studied in an application to solvent clusters. The program was ported to a small parallel-processor system consisting of five T800–20 transputers. Different topologies are discussed. The optimum topology depends on the size of the computational problem; for our problem size it is a modified tree structure. Benchmarks are given for a transputer farm, and compared with results obtained on various scalar and vector processors.

This paper discusses an experiment with a dataflow execution model for logic programs implemented on the transputer. The execution model is supported by a dataflow virtual machine, on which the execution mechanism for AND/OR-parallelism is developed. The real-time evaluation shows that small scale parallelism can be exploited from the dataflow graphs compiled from the logic programs. A conventional dataflow architecture supporting the implemented model has been emulated on a multitransputer system.

Transputers are commonly used in low cost computation-intensive applications, such as image processing and signal analysis. Symbolic processing and AI applications on transputers require a different programming environment. This paper reports the effort made to implement BaLinda Lisp, a parallel Lisp dialect, on transputer arrays. BaLinda Lisp supports the FUTURE construct to initiate parallel execution threads, speculative constructs to spawn parallel tasks for results that may be required, and tuple space operations to enforce the proper communication, synchronization, mutual exclusion and shared variable access for parallel tasks. A suite of application programs has been tested on the resulting interpreter and some performance results are presented. The results demonstrate that the interpreter achieves realistic parallelism and provides a high speed symbolic processing environment on transputers. The implementation strategies are described in this paper, focusing on how to support the novel features of BaLinda Lisp. The advantages and disadvantages inherent in the transputer architecture that affect the design of the interpreter are also discussed.

Informatics and Scientific Computing approach parallel processing in a different way. We briefly describe the different points of view of both camps. Next we concentrate on a case study in the area of scientific computing. The problem chosen is from Physical Chemistry (self-consistent field computation). We describe the problem, the sequential solution, the parallelization strategy and present the performance values we have achieved. Our implementation is based on a 60-node transputer system, available at the Parallel Processing Laboratory in Basel.

Genetic algorithms are search or classification algorithms based on natural models. They present a high degree of internal parallelism. We developed two versions, differing in the way the population is organized and we studied and compared their characteristics and performances when applied to the optimization of multidimensional function problems. All the implementations are realized on transputer networks.

We present a new method for the solution of partial differential equations. In contrast to the usual approach which needs in the 2-D case grid points, our combination technique works with only grid points, where h_n denotes the employed grid size. The accuracy of the obtained solution deteriorates only slightly from to for a sufficiently smooth solution. Additionally, the new method is perfectly suited for parallelization. On a machine with processors we get in practice an overall parallel complexity of only . The method can be generalized to higher dimensions. Then, the gain is expected to be even more dramatic. For the two-dimensional case, we report the results of numerical experiments obtained on a Transputer system and on the CRAY Y-MP.

A transputer-based parallel processing paradjgm for real-time extraction of road traffic data from video images of roadway scenes is proposed. The model can monitor three lanes of motorway traffic in real-time by processing images from two windows associated with each lane. Parallel algorithms are distributed among a network of transputers to perform similar and/or different tasks concerning image data analysis and traffic data extraction. The model can be expanded to cover more lanes or duplicated to monitor a further multi-lane carriageway.

This paper presents an algorithm for multiple alignment of sequences of proteins and nucleic acids on loosely-coupled MIMD machines. An inherently parallel algorithm is devised and implemented on a transputer-based multiprocessor platform. The results indicate the possibility of scalable performance.