MPH — A Hybrid Parallel Machine

[1991] Proceedings, Advanced Computer Technology, Reliable Systems and Applications, 1991

We review the main research issues and problems in the area of general-purpose, massively parallel MIMD computers. It will be shown that the successful exploitation of this class of systems depends on the ability to de ne and experiment with design methodologies taking into account several aspects: abstract machine architecture, physical machine architecture, parallelizing and restructuring tools, and machine independent parallel languages. We report on our research experience in this area, and in particular our work in the Pisa Parallel Processing Project.

… of the Conference on Design of …, 2006

Wiley-Interscience eBooks, 2004

Having covered the essential issues in the design and analysis of uniprocessors and pointing out the main limitations of a single-stream machine, we begin in this chapter to pursue the issue of multiple processors. Here a number of processors (two or more) are connected in a manner that allows them to share the simultaneous execution of a single task. The main argument for using multiprocessors is to create powerful computers by simply connecting many existing smaller ones. A multiprocessor is expected to reach a faster speed than the fastest uniprocessor. In addition, a multiprocessor consisting of a number of single uniprocessors is expected to be more cost-effective than building a high-performance single processor. An additional advantage of a multiprocessor consisting of n processors is that if a single processor fails, the remaining fault-free n 2 1 processors should be able to provide continued service, albeit with degraded performance. Our coverage in this chapter starts with a section on the general concepts and terminology used. We then point to the different topologies used for interconnecting multiple processors. Different classification schemes for computer architectures are then introduced and analyzed. We then introduce a topology-based taxonomy for interconnection networks. Two memory-organization schemes for MIMD (multiple instruction multiple data) multiprocessors are also introduced. Our coverage in this chapter ends with a touch on the analysis and performance metrics for multiprocessors. It should be noted that interested readers are referred to more elaborate discussions on multiprocessors in Chapters 2 and 3 of our book on Advanced Computer Architecture and Parallel Processing (see reference list).

2014 International Conference on Parallel Distributed and Grid Computing, 2014

Multiprocessor architecture is the main resource to speed up applications by incorporating parallelism among various processing elements. The success of multiprocessor system depends how much efficiently the concurrent processes are managed on the system. This paper proposes a novel multiprocessor architecture which is less complex, easily extensible and inherits most of the desirable topological properties. The proposed system is capable to manage the distributing of parallel tasks efficiently when appropriate scheduling schemes are implemented on it. The comparative study shows that the proposed architecture could be used effectively in various multi-processing applications.

Parallel and …, 2005

Though there have been substantial progress, the current status of parallel computing is still inmature. No single model of parallel computation has yet come to dominate developments in parallel computing in the way that the von Neumann model ...

In this paper we have studied several works on direct network architectures which are well-built contestant for useful in many successful cost-effective, experimental massive parallel computers and well scale up shared memory of multiprocessors. The uniqueness of direct networks, as reflected by the communication latency and routing latency metrics are significant to the performance of such systems. A multiprocessor system can be used for the wormhole routing for the most capable switching method and has been adopted in several new massive parallel computers. This technique is unique technical challenges in routing and flow control in particular system, and avoid deadlock. The highly scale up network is a combination of topology and hypercube. Due to the being of concurrent multiple mesh and hypercubes, this network provides a great architectural support for parallel processing. The growth of the network is more efficient in terms of communication, interconnection network is scaled up the network and will be more reliable and also the unreliability of the interconnection network to get minimized. This is very desirable characteristic for the interconnection network as the network remains equipped for more failure of adjoining nodes or links in parallel computer architecture. Formulations to optimize the performance of throughput of networks through queuing theory M\M\1 concept.

2012

This paper describes about computer architectural classification. These architectural schemes are given by Flynn, Feng, Handler and Shores. Flynn's classification is based on multiplicity of instruction stream and data stream in a computer system. Feng's classification is mainly based on serial and parallel processing in the computer system. Handler's classification is calculated on the basis of degree of parallelism and pipelining in system levels. Shores's classification is based on constituent element in the system. Parallel processing has emerged as a key enabling technology in modern computers, driven by the everincreasing demand for higher performance, lower costs, and sustained productivity in real-life applications. Concurrent events are taking place in today's high performance computers due to the common practice of multiprogramming, multiprocessing, or multicomputing. Parallelism can be in the form of look ahead, pipelining vectorization concurrency, simultaneity, data parallelism, partitioning, interleaving, overlapping, multiplicity, replication, time sharing, space sharing, multitasking, multiprogramming, multithreading, and distributed computing at different processing levels. Parallel computing is a form of computation in which many calculations are carried out simultaneously, operating on the principle that large problems can often be divided into smaller ones, which are then solved concurrently. CLASSIFICATION

Proceedings of The IEEE

This is a good time for parallel-computer development and research in both academia and industry. The performance improvements predicted by Moore's Law has proven itself quite accurate over many years. However, the doubling of processor performance every 18 months cannot keep up with the growing demand of many applications. The performance of database applications has been doubling every 9-10 months. At last, parallel-computer technology has come to play an important role in the commercial marketplace.

Page 1. Hypercubes are General-Purpose Multiprocessors with High Speedup Marina Chen, Yale Erik DeBenedictis, Bell Labs Geoffrey Fox, Caltech Jingke Li, Yale David Walker, Caltech ABSTRACT This is a submission for the Gordon Bell Award for multiprocessor speedup ill the general purpose category. The entry is for the Hypercube architecture. Program PEs Speedup QCD Simulation 512 458 Circuit Simulation 128 39 LU Decomposition 128 98 1.

TJPRC, 2014

In this paper was represented parallel computers. The problems in parallel computing