Verification and FPGA circuits of a block-2 fast path-based predictor

This paper formally derives a new path-based neural branch prediction algorithm (FPP) into blocks of size two for a lower hardware solution while maintaining similar input-output characteristic to the algorithm. The blocked solution, here referred to as B2P algorithm, is obtained using graph theory and retiming methods. Verification approaches were exercised to show that prediction performances obtained from the FPP and B2P algorithms differ within one mis-prediction per thousand instructions using a known framework for branch prediction evaluation. For a chosen FPGA device, circuits generated from the B2P algorithm showed average area savings of over 25% against circuits for the FPP algorithm with similar time performances thus making the proposed blocked predictor superior from a practical viewpoint.

Experiences applying OVM 2.0 to an 8B/10B RTL design

The SystemVerilog implementation of the Open Verification Methodology (OVM) is exercised on an 8b/10b RTL open core design in the hope of being a simple yet complete exercise to expose the key features of OVM. Emphasis is put onto the actual usage of the verification components rather than a complete verification flow aiming at being of help to readers unfamiliar with OVM seeking to apply the methodology to their own designs. A link that takes you to the complete code is given to reinforce this aim. We found the methodology easy to use but intimidating at first glance specially for someone with little experience in object oriented programming. However it is clear to see the flexibility, portability and reusability of verification code once you manage to give some first steps.

A clocking technique with power savings in virtex-based pipelined designs

This paper presents the evaluation in power consumption of a clocking technique for pipelined designs. The technique shows a dynamic power consumption saving of around 30% over a conventional global clocking mechanism. The results were obtained from a series of experiments of a systolic circuit implemented in Virtex-II devices. The conversion from a global-clocked pipelined design to the proposed technique is straightforward, preserving the original datapath design. The savings can be used immediately either as a power reduction benefit or to increase the frequency of operation of a design for the same power consumption.

The control of dynamical systems by neural networks

In this paper the use of neural networks for the control of dynamical systems is considered. Both identification and feedback control aspects are discussed as well as the types of system for which neural networks can provide a useful technique. Multi-layer Perceptron and Radial Basis function neural network types are looked at, with an emphasis on the latter. It is shown how basis function centre selection is a critical part of the implementation process and that multivariate clustering algorithms can be an extremely useful tool for finding centres.

TCL/TK for EDA tools

Tcl/Tk scripting language has become the de-facto standard for EDA tools. This paper explains how to start working with Tcl/Tk using simple examples. Two complete applications are presented to show in more detail the capabilities of the language. In one script average power consumption of a digital system is automated. A second script creates a virtual display driven by the simulation of a graphic card.

Generic construction of monitors for floating point unit designs

This paper proposes a set of well defined steps to design functional verification monitors intended to verify Floating Point Units (FPU) described in HDL. The first step consists on defining the input and output domain coverage. Next, the corner cases are defined. Finally, an already verified reference model is used in order to test the correctness of the Device Under Verification (DUV). As a case study a monitor for an IEEE754-2008 compliant design is implemented. This monitor is built to be easily instantiated into verification frameworks such as OVM. Two different designs were verified reaching complete input coverage and successful compliant results.

An evolutionary computing approach to minimize dynamic hedging error

The objective of our present paper is to derive a computationally efficient genetic pattern learning algorithm to evolutionarily derive the optimal rebalancing weights (i.e. dynamic hedge ratios) to engineer a structured financial product out of a multiasset, best-of option. The stochastic target function is formulated as an expected squared cost of hedging (tracking) error which is assumed to be partly dependent on the governing Markovian process underlying the individual asset returns and partly on
randomness i.e. pure white noise. A simple haploid genetic algorithm is advanced as an alternative numerical scheme, which is deemed to be
computationally more efficient than numerically deriving an explicit solution to the formulated optimization model. An extension to our proposed scheme is suggested by means of adapting the Genetic Algorithm parameters based on fuzzy logic controllers.

Adaptive intelligent energy management system of plug-in hybrid electric vehicle

Efficient energy management in hybrid vehicles is the key for reducing fuel consumption and emissions. To capitalize on the benefits of using PHEVs (Plug-in Hybrid Electric Vehicles), an intelligent energy management system is developed and evaluated in this paper. Models of vehicle engine, air conditioning, powertrain, and hybrid electric drive system are first developed. The effect of road parameters such as bend direction and road slope angle as well as environmental factors such as wind (direction and speed) and thermal conditions are also modeled. Due to the nonlinear and complex nature of the interactions between PHEV-Environment-Driver components, a soft computing based intelligent management system is developed using three fuzzy logic controllers. The crucial fuzzy engine controller within the intelligent energy management system is made adaptive by using a hybrid multi-layer adaptive neuro-fuzzy inference system with genetic algorithm optimization. For adaptive learning, a number of datasets were created for different road conditions and a hybrid learning algorithm based on the least squared error estimate using the gradient descent method was proposed. The proposed adaptive intelligent energy management system can learn while it is running and makes proper adjustments during its operation. It is shown that the proposed intelligent energy management system is improving the performance of other existing systems. © 2014 Elsevier Ltd.

Aplicação de opções reais em projetos de automação : um estudo de caso na indústria de cerveja

Projetos de automação industrial são avaliados financeiramente através dos métodos bastante utilizados de Valor Presente Líquido (VPL) e Taxa Interna de Retorno (TIR). Estudos recentes mostram uma tendência para a utilização de outros métodos para realizar esta avaliação. Este trabalho explora o método alternativo de Opções Reais para avaliação desses projetos que busca se aproximar mais do mundo real considerando maior incerteza e flexibilidade do que o VPL. Inicialmente será feita uma revisão de literatura focando o método binomial dentro de Opções Reais. A metodologia proposta é um estudo de caso de um projeto no mercado de cerveja no Brasil, utilizando como fonte uma empresa multinacional de grande porte fornecedora desse projeto. Posteriormente será feita uma análise financeira primeiramente utilizando somente o VPL e posteriormente incorporando o método binomial de Opções Reais, resultando no VPL estendido. O objetivo é precificar a flexibilidade das Opções Reais presentes no contrato de fornecimento do projeto em estudo que normalmente não são consideradas. Com isso pretende-se verificar se o método binomial de Opções Reais faz real diferença no projeto em estudo.

Desenvolvimento de um sistema Inteligente para a análise de cartas dinamométricas no método de elevação por bombeio mecânico

The artificial lifting of oil is needed when the pressure of the reservoir is not high enough so that the fluid contained in it can reach the surface spontaneously. Thus the increase in energy supplies artificial or additional fluid integral to the well to come to the surface. The rod pump is the artificial lift method most used in the world and the dynamometer card (surface and down-hole) is the best tool for the analysis of a well equipped with such method. A computational method using Artificial Neural Networks MLP was and developed using pre-established patterns, based on its geometry, the downhole card are used for training the network and then the network provides the knowledge for classification of new cards, allows the fails diagnose in the system and operation conditions of the lifting system. These routines could be integrated to a supervisory system that collects the cards to be analyzed

Reconfiguração dinâmica de estratégias distribuídas em dispositivos foundation fieldbus para a otimização de processos na indústria do petróleo

The petrochemical industry has as objective obtain, from crude oil, some products with a higher commercial value and a bigger industrial utility for energy purposes. These industrial processes are complex, commonly operating with large production volume and in restricted operation conditions. The operation control in optimized and stable conditions is important to keep obtained products quality and the industrial plant safety. Currently, industrial network has been attained evidence when there is a need to make the process control in a distributed way. The Foundation Fieldbus protocol for industrial network, for its interoperability feature and its user interface organized in simple configuration blocks, has great notoriety among industrial automation network group. This present work puts together some benefits brought by industrial network technology to petrochemical industrial processes inherent complexity. For this, a dynamic reconfiguration system for intelligent strategies (artificial neural networks, for example) based on the protocol user application layer is proposed which might allow different applications use in a particular process, without operators intervention and with necessary guarantees for the proper plant functioning

Gerenciamento de alarmes em plataformas marítimas de produção de hidrocarbonetos: metodologia e estudo de caso

In the operational context of industrial processes, alarm, by definition, is a warning to the operator that an action with limited time to run is required, while the event is a change of state information, which does not require action by the operator, therefore should not be advertised, and only stored for analysis of maintenance, incidents and used for signaling / monitoring (EEMUA, 2007). However, alarms and events are often confused and improperly configured similarly by developers of automation systems. This practice results in a high amount of pseudo-alarms during the operation of industrial processes. The high number of alarms is a major obstacle to improving operational efficiency, making it difficult to identify problems and increasing the time to respond to abnormalities. The main consequences of this scenario are the increased risk to personal safety, facilities, environment deterioration and loss of production. The aim of this paper is to present a philosophy for setting up a system of supervision and control, developed with the aim of reducing the amount of pseudo-alarms and increase reliability of the information that the system provides. A real case study was conducted in the automation system of the offshore production of hydrocarbons from Petrobras in Rio Grande do Norte, in order to validate the application of this new methodology. The work followed the premises of the tool presented in ISA SP18.2. 2009, called "life cycle alarm . After the implementation of methodology there was a significant reduction in the number of alarms

Desenvolvimento de sistemas embarcados para redes de sensores e atuadores sem fio aplicadas em unidades de elevação de petróleo do tipo Plunger-Lift

The Wireless Sensor Networks (WSN) methods applied to the lifting of oil present as an area with growing demand technical and scientific in view of the optimizations that can be carried forward with existing processes. This dissertation has as main objective to present the development of embedded systems dedicated to a wireless sensor network based on IEEE 802.15.4, which applies the ZigBee protocol, between sensors, actuators and the PLC (Programmable Logic Controller), aiming to solve the present problems in the deployment and maintenance of the physical communication of current elevation oil units based on the method Plunger-Lift. Embedded systems developed for this application will be responsible for acquiring information from sensors and control actuators of the devices present at the well, and also, using the Modbus protocol to make this network becomes transparent to the PLC responsible for controlling the production and delivery information for supervisory SISAL

Protocolo multiciclos para automação hospitalar sobre Multicast com IEEE 802.3 utilizando

The concepts of the industrial automation are being incorporated in the medical area, in other words, they also pass to be applied in the hospital automation. In this sense, researches have been developed and have usually been approached several of the problems that are pertinent to the processes that can be automated in the hospital environment. Considering that in the automation processes, an imperative factor is the communication, because the systems are usually distributed, the network for data transference becomes itself an important point in these processes. Because this network should be capable to provide the exchange of data and to guarantee the demands that are imposed by the automation process. In this context, this doctorate thesis proposed, specified, analyzed and validated the Multicycles Protocol for Hospital Automation (MP-HA), which is customized to assist the demands in these automation processes, seeking to guarantee the determinism in the communications and to optimize the factor of use of the mean of transmission