928 resultados para Parallel processing (Electronic computers) - Research


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The presence of non-linear loads at a point in the distribution system may deform voltage waveform due to the consumption of non-sinusoidal currents. The use of active power filters allows significant reduction of the harmonic content in the supply current. However, the processing of digital control structures for these filters may require high performance hardware, particularly for reference currents calculation. This work describes the development of hardware structures with high processing capability for application in active power filters. In this sense, it considers an architecture that allows parallel processing using programmable logic devices. The developed structure uses a hybrid model using a DSP and an FPGA. The DSP is used for the acquisition of current and voltage signals, calculation of fundamental current related controllers and PWM generation. The FPGA is used for intensive signal processing, such as the harmonic compensators. In this way, from the experimental analysis, significant reductions of the processing time are achieved when compared to traditional approaches using only DSP. The experimental results validate the designed structure and these results are compared with other ones from architectures reported in the literature.

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This paper examines scheduling problems in which the setup phase of each operation needs to be attended by a single server, common for all jobs and different from the processing machines. The objective in each situation is to minimize the makespan. For the processing system consisting of two parallel dedicated machines we prove that the problem of finding an optimal schedule is NP-hard in the strong sense even if all setup times are equal or if all processing times are equal. For the case of m parallel dedicated machines, a simple greedy algorithm is shown to create a schedule with the makespan that is at most twice the optimum value. For the two machine case, an improved heuristic guarantees a tight worst-case ratio of 3/2. We also describe several polynomially solvable cases of the later problem. The two-machine flow shop and the open shop problems with a single server are also shown to be NP-hard in the strong sense. However, we reduce the two-machine flow shop no-wait problem with a single server to the Gilmore-Gomory traveling salesman problem and solve it in polynomial time. (c) 2000 John Wiley & Sons, Inc.

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We consider a problem of scheduling jobs on m parallel machines. The machines are dedicated, i.e., for each job the processing machine is known in advance. We mainly concentrate on the model in which at any time there is one unit of an additional resource. Any job may be assigned the resource and this reduces its processing time. A job that is given the resource uses it at each time of its processing. No two jobs are allowed to use the resource simultaneously. The objective is to minimize the makespan. We prove that the two-machine problem is NP-hard in the ordinary sense, describe a pseudopolynomial dynamic programming algorithm and convert it into an FPTAS. For the problem with an arbitrary number of machines we present an algorithm with a worst-case ratio close to 3/2, and close to 3, if a job can be given several units of the resource. For the problem with a fixed number of machines we give a PTAS. Virtually all algorithms rely on a certain variant of the linear knapsack problem (maximization, minimization, multiple-choice, bicriteria). © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008

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In this paper, we provide a unified approach to solving preemptive scheduling problems with uniform parallel machines and controllable processing times. We demonstrate that a single criterion problem of minimizing total compression cost subject to the constraint that all due dates should be met can be formulated in terms of maximizing a linear function over a generalized polymatroid. This justifies applicability of the greedy approach and allows us to develop fast algorithms for solving the problem with arbitrary release and due dates as well as its special case with zero release dates and a common due date. For the bicriteria counterpart of the latter problem we develop an efficient algorithm that constructs the trade-off curve for minimizing the compression cost and the makespan.

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Huelse, M, Barr, D R W, Dudek, P: Cellular Automata and non-static image processing for embodied robot systems on a massively parallel processor array. In: Adamatzky, A et al. (eds) AUTOMATA 2008, Theory and Applications of Cellular Automata. Luniver Press, 2008, pp. 504-510. Sponsorship: EPSRC

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In this paper, we study a problem of scheduling and batching on two machines in a flow-shop and open-shop environment. Each machine processes operations in batches, and the processing time of a batch is the sum of the processing times of the operations in that batch. A setup time, which depends only on the machine, is required before a batch is processed on a machine, and all jobs in a batch remain at the machine until the entire batch is processed. The aim is to make batching and sequencing decisions, which specify a partition of the jobs into batches on each machine, and a processing order of the batches on each machine, respectively, so that the makespan is minimized. The flow-shop problem is shown to be strongly NP-hard. We demonstrate that there is an optimal solution with the same batches on the two machines; we refer to these as consistent batches. A heuristic is developed that selects the best schedule among several with one, two, or three consistent batches, and is shown to have a worst-case performance ratio of 4/3. For the open-shop, we show that the problem is NP-hard in the ordinary sense. By proving the existence of an optimal solution with one, two or three consistent batches, a close relationship is established with the problem of scheduling two or three identical parallel machines to minimize the makespan. This allows a pseudo-polynomial algorithm to be derived, and various heuristic methods to be suggested.

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The scheduling problem of minimizing the makespan for m parallel dedicated machines under single resource constraints is considered. For different variants of the problem the complexity status is established. Heuristic algorithms employing the so-called group technology approach are presented and their worst-case behavior is examined. Finally, a polynomial time approximation scheme is presented for the problem with fixed number of machines.

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An important factor for high-speed optical communication is the availability of ultrafast and low-noise photodetectors. Among the semiconductor photodetectors that are commonly used in today’s long-haul and metro-area fiber-optic systems, avalanche photodiodes (APDs) are often preferred over p-i-n photodiodes due to their internal gain, which significantly improves the receiver sensitivity and alleviates the need for optical pre-amplification. Unfortunately, the random nature of the very process of carrier impact ionization, which generates the gain, is inherently noisy and results in fluctuations not only in the gain but also in the time response. Recently, a theory characterizing the autocorrelation function of APDs has been developed by us which incorporates the dead-space effect, an effect that is very significant in thin, high-performance APDs. The research extends the time-domain analysis of the dead-space multiplication model to compute the autocorrelation function of the APD impulse response. However, the computation requires a large amount of memory space and is very time consuming. In this research, we describe our experiences in parallelizing the code in MPI and OpenMP using CAPTools. Several array partitioning schemes and scheduling policies are implemented and tested. Our results show that the code is scalable up to 64 processors on a SGI Origin 2000 machine and has small average errors.

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Parallel processing techniques have been used in the past to provide high performance computing resources for activities such as Computational Fluid Dynamics. This is normally achieved using specialized hardware and software, the expense of which would be difficult to justify for many fire engineering practices. In this paper, we demonstrate how typical office-based PCs attached to a local area network have the potential to offer the benefits of parallel processing with minimal costs associated with the purchase of additional hardware or software. A dynamic load balancing scheme was devised to allow the effective use of the software on heterogeneous PC networks. This scheme ensured that the impact between the parallel processing task and other computer users on the network was minimized thus allowing practical parallel processing within a conventional office environment. Copyright © 2006 John Wiley & Sons, Ltd.

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Computer egress simulation has potential to be used in large scale incidents to provide live advice to incident commanders. While there are many considerations which must be taken into account when applying such models to live incidents, one of the first concerns the computational speed of simulations. No matter how important the insight provided by the simulation, numerical hindsight will not prove useful to an incident commander. Thus for this type of application to be useful, it is essential that the simulation can be run many times faster than real time. Parallel processing is a method of reducing run times for very large computational simulations by distributing the workload amongst a number of CPUs. In this paper we examine the development of a parallel version of the buildingEXODUS software. The parallel strategy implemented is based on a systematic partitioning of the problem domain onto an arbitrary number of sub-domains. Each sub-domain is computed on a separate processor and runs its own copy of the EXODUS code. The software has been designed to work on typical office based networked PCs but will also function on a Windows based cluster. Two evaluation scenarios using the parallel implementation of EXODUS are described; a large open area and a 50 story high-rise building scenario. Speed-ups of up to 3.7 are achieved using up to six computers, with high-rise building evacuation simulation achieving run times of 6.4 times faster than real time.

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TiAl castings are prone to various defects including bubbles entrained during the turbulent filling of moulds. The present research has exploited the principles of the Durville tilt casting technique to develop a novel process in which the Induction Skull Melting (ISM) of TiAl alloys in a vacuum chamber has been combined with controlled tilt pouring to achieve the tranquil transfer of the metal into a hot ceramic shell mould. Practical casting equipment has been developed to evaluate the feasibility of this process in parallel with the development of novel software to simulate and optimize it. The PHYSICA CFD code was used to simulate the filling, heat transfer and solidification during tilt pouring using a number of free surface modelling techniques, including the novel Counter Diffusion Method (CDM). In view of the limited superheat, particular attention was paid to the mould design to minimize heat loss and gas entrainment caused by interaction between the counter-flowing metal and gas streams. The model has been validated against real-time X-ray movies of the tilt casting of aluminium and against TiAl blade castings. Modelling has contributed to designing a mould to promote progressive filling of the casting and has led to the use of a parabolic tilting cycle to balance the competing requirements for rapid filling to minimize the loss of superheat and slow filling minimize the turbulence-induced defects.

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In this chapter we look at JOSTLE, the multilevel graph-partitioning software package, and highlight some of the key research issues that it addresses. We first outline the core algorithms and place it in the context of the multilevel refinement paradigm. We then look at issues relating to its use as a tool for parallel processing and, in particular, partitioning in parallel. Since its first release in 1995, JOSTLE has been used for many mesh-based parallel scientific computing applications and so we also outline some enhancements such as multiphase mesh-partitioning, heterogeneous mapping and partitioning to optimise subdomain shape

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The use of flexible substrates is growing in many applications such as computer peripherals, hand held devices, telecommunications, automotive, aerospace, etc. The drive to adopt flexible circuits is due to their ability to reduce size, weight, assembly time and cost of the final product.They also accommodate flexibility by allowing relative movement between component parts and provide a route for three dimensional packaging. This paper will describe some of the current research results from the Flex-No-Lead project, a European Commission sponsored research program. The principle aim of this project is to investigate the processing, performance, and reliability of flexible substrates when subjected to new environmentally friendly, lead-free soldering technologies. This paper will discuss the impact of specific design variables on performance and reliability. In particular the paper will focus on copper track designs, substrate material, dielectric material and solder-mask defined joints.

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We consider a variety of preemptive scheduling problems with controllable processing times on a single machine and on identical/uniform parallel machines, where the objective is to minimize the total compression cost. In this paper, we propose fast divide-and-conquer algorithms for these scheduling problems. Our approach is based on the observation that each scheduling problem we discuss can be formulated as a polymatroid optimization problem. We develop a novel divide-and-conquer technique for the polymatroid optimization problem and then apply it to each scheduling problem. We show that each scheduling problem can be solved in $ \O({\rm T}_{\rm feas}(n) \times\log n)$ time by using our divide-and-conquer technique, where n is the number of jobs and Tfeas(n) denotes the time complexity of the corresponding feasible scheduling problem with n jobs. This approach yields faster algorithms for most of the scheduling problems discussed in this paper.

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Recent research efforts of parallel processing on non-dedicated clusters have focused on high execution performance, parallelism management, transparent access to resources, and making clusters easy to use. However, as a collection of independent computers used by multiple users, clusters are susceptible to failure. This paper shows the development of a coordinated checkpointing facility for the GENESIS cluster operating system. This facility was developed by exploiting existing operating system services. High performance and low overheads are achieved by allowing the processes of a parallel application to continue executing during the creation of checkpoints, while maintaining low demands on cluster resources by using coordinated checkpointing.