Shared versus distributed memory multiprocessors

The question of whether multiprocessors should have shared or distributed memory has attracted a great deal of attention. Some researchers argue strongly for building distributed memory machines, while others argue just as strongly for programming shared memory multiprocessors. A great deal of research is underway on both types of parallel systems. Special emphasis is placed on systems with a very large number of processors for computation intensive tasks and considers research and implementation trends. It appears that the two types of systems will likely converge to a common form for large scale multiprocessors

Fault tolerant clos network

Multistage interconnection networks, or MINs, provide paths between functional modules in multiprocessor systems. The MINs are usually segmented into several stages. Each stage connects inputs to appropriate links of the next stage so that the cumulative effect of all the stages satisfies input-output connection requirements. This thesis deals with a fault tolerant Clos network. The fault tolerance technique involves addition of extra switches per stage to compensate for any switch failure The reliability analysis of both ordinary and fault tolerant Clos networks is presented. The optimal number of extra switches required to get the best reliability results has been analyzed

Parallel Architectures and Parallel Algorithms for Integrated Vision Systems

Computer vision is regarded as one of the most complex and computationally intensive problems. An integrated vision system (IVS) is a system that uses vision algorithms from all levels of processing to perform for a high level application (e.g., object recognition). An IVS normally involves algorithms from low level, intermediate level, and high level vision. Designing parallel architectures for vision systems is of tremendous interest to researchers. Several issues are addressed in parallel architectures and parallel algorithms for integrated vision systems

Expanded delta networks for very large parallel computers

In this paper we analyze a generalization of the traditional delta network, introduced by Patel [21], and dubbed Expanded Delta Network (EDN). These networks provide in general multiple paths that can be exploited to reduce contention in the network resulting in increased performance. The crossbar and traditional delta networks are limiting cases of this class of networks. However, the delta network does not provide the multiple paths that the more general expanded delta networks provide, and crossbars are to costly to use for large networks. The EDNs are analyzed with respect to their routing capabilities in the MIMD and SIMD models of computation.The concepts of capacity and clustering are also addressed. In massively parallel SIMD computers, it is the trend to put a larger number processors on a chip, but due to I/O constraints only a subset of the total number of processors may have access to the network. This is introduced as a Restricted Access Expanded Delta Network of which the MasPar MP-1 router network is an example

Multiplus: a modular high-performance multiprocessor

The MULTIPLUS project is currently under development at NCE/UFRJ, Brazil, aims at the study of parallel processing problems in MIMD environments. The project includes the development of a parallel shared-memory architecture and a UNIX-like operating operating system called MULTIPLIX. The MULTIPLUS achitecture uses an inverted n-cube multistage network to interconnect clusters of processing nodes designed around a double-bus system. As a consequence, the architecture is partitionable and modular. It cas easily and efficiently supportconfigurations ranging from workstations to powerful parallel supercomputers with up to 2048 processing nodes. The MULTIPLix operating system provides MULTIPLUS with an efficient computing environment for parallel scientific applications. MULTIPLIX uses the concept of thread, implements busy-waiting synchronization primitives very efficiently and carefully considers data locality and scientific processing requirements in the policies adopted for memory management and thread scheduling.O projeto MULTIPLUS, que está atualmente em desenvolvimento no NCE/UFRJ, objetiva o estudo de problemas de processamento paralelo em ambiente MIMD. O projeto inclui o desenvolvimento de uma arquitetura paralela com memória compartilhada e um sistema operacional tipo UNIX chamado MULTIPLIX. A arquitetura do MULTIPLUS usa uma rede de interconexão multiestágio do tipo n-cubo invertido para interligar clusters de nós de processamento projetados em torno de um sistema de barramento duplo. Como consequência a arquitetura é patrocinável e modular. Ela pode suportar eficientemente configurações cobrindo um espectro que vai desde estações de trabalho até poderosos supercomputadores contendo 2048 nós de processamento trabalhando em paralelo. O sistema operacional MULTIPLIX provê o MULTIPLUS com um ambiente eficiente de computação para aplicações científicas paralelas.O MULTIPLIX usa o conceito de "thread", implementa primitivas de sincronização de espera ocupara muito eficientemente e considera fortemente aspectos de localidade dos dados e requisitos de processamento científico nas políticas adotadas para gerenciamento de memória e escalonamento de "threads"

Modeling of Topologies of Interconnection Networks based on Multidimensional Multiplicity

Modern SoCs are becoming more complex with the integration of heterogeneous components (IPs). For this purpose, a high performance interconnection medium is required to handle the complexity. Hence NoCs come into play enabling the integration of more IPs into the SoC with increased performance. These NoCs are based on the concept of Interconnection networks used to connect parallel machines. In response to the MARTE RFP of the OMG, a notation of multidimensional multiplicity has been proposed which permits to model repetitive structures and topologies. This report presents a modeling methodology based on this notation that can be used to model a family of Interconnection Networks called Delta Networks which in turn can be used for the construction of NoCs

A low-cost high-speed twin-prefetching DSP-based shared-memory system for real-time image processing applications

This dissertation introduces, investigates, and evaluates a low-cost high-speed twin-prefetching DSP-based bus-interconnected shared-memory system for real-time image processing applications. The proposed architecture can effectively support 32 DSPs in contrast to a maximum of 4 DSPs supported by existing DSP-based bus- interconnected systems. This significant enhancement is achieved by introducing two small programmable fast memories (Twins) between the processor and the shared bus interconnect. While one memory is transferring data from/to the shared memory, the other is supplying the core processor with data. The elimination of the traditional direct linkage of the shared bus and processor data bus makes feasible the utilization of a wider shared bus i.e., shared bus width becomes independent of the data bus width of the processors. The fast prefetching memories and the wider shared bus provide additional bus bandwidth into the system, which eliminates large memory latencies; such memory latencies constitute the major drawback for the performance of shared-memory multiprocessors. Furthermore, in contrast to existing DSP-based uniprocessor or multiprocessor systems the proposed architecture does not require all data to be placed on on-chip or off-chip expensive fast memory in order to reach or maintain peak performance. Further, it can maintain peak performance regardless of whether the processed image is small or large. The performance of the proposed architecture has been extensively investigated executing computationally intensive applications such as real-time high-resolution image processing. The effect of a wide variety of hardware design parameters on performance has been examined. More specifically tables and graphs comprehensively analyze the performance of 1, 2, 4, 8, 16, 32 and 64 DSP-based systems, for a wide variety of shared data interconnect widths such as 32, 64, 128, 256 and 512. In addition, the effect of the wide variance of temporal and spatial locality (present in different applications) on the multiprocessor\u27s execution time is investigated and analyzed. Finally, the prefetching cache-size was varied from a few kilobytes to 4 Mbytes and the corresponding effect on the execution time was investigated. Our performance analysis has clearly showed that the execution time converges to a shallow minimum i.e., it is not sensitive to the size of the prefetching cache. The significance of this observation is that near optimum performance can be achieved with a small (16 to 300 Kbytes) amount of prefetching cache