1,351 research outputs found

    Coarse-grained reconfigurable array architectures

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    Coarse-Grained ReconïŹgurable Array (CGRA) architectures accelerate the same inner loops that beneïŹt from the high ILP support in VLIW architectures. By executing non-loop code on other cores, however, CGRAs can focus on such loops to execute them more efïŹciently. This chapter discusses the basic principles of CGRAs, and the wide range of design options available to a CGRA designer, covering a large number of existing CGRA designs. The impact of different options on ïŹ‚exibility, performance, and power-efïŹciency is discussed, as well as the need for compiler support. The ADRES CGRA design template is studied in more detail as a use case to illustrate the need for design space exploration, for compiler support and for the manual ïŹne-tuning of source code

    Intelligent systems engineering with reconfigurable computing

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    Intelligent computing systems comprising microprocessor cores, memory and reconfigurable user-programmable logic represent a promising technology which is well-suited for applications such as digital signal and image processing, cryptography and encryption, etc. These applications employ frequently recursive algorithms which are particularly appropriate when the underlying problem is defined in recursive terms and it is difficult to reformulate it as an iterative procedure. It is known, however, that hardware description languages (such as VHDL) as well as system-level specification languages (such as Handel-C) that are usually employed for specifying the required functionality of reconfigurable systems do not provide a direct support for recursion. In this paper a method allowing recursive algorithms to be easily described in Handel-C and implemented in an FPGA (field-programmable gate array) is proposed. The recursive search algorithm for the knapsack problem is considered as an exampleApplications in Artificial Intelligence - Knowledge EngineeringRed de Universidades con Carreras en InformĂĄtica (RedUNCI

    Minimum maximum reconfiguration cost problem

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    This paper discusses the problem of minimizing the reconfiguration cost of some types of reconfigurable systems. A formal definition of the problem and a proof of its NP-completeness are provided. In addition, an Integer Linear Programming formulation is proposed. The proposed problem has been used for optimizing a design stage of Finite Virtual State Machines

    The Design of a System Architecture for Mobile Multimedia Computers

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    This chapter discusses the system architecture of a portable computer, called Mobile Digital Companion, which provides support for handling multimedia applications energy efficiently. Because battery life is limited and battery weight is an important factor for the size and the weight of the Mobile Digital Companion, energy management plays a crucial role in the architecture. As the Companion must remain usable in a variety of environments, it has to be flexible and adaptable to various operating conditions. The Mobile Digital Companion has an unconventional architecture that saves energy by using system decomposition at different levels of the architecture and exploits locality of reference with dedicated, optimised modules. The approach is based on dedicated functionality and the extensive use of energy reduction techniques at all levels of system design. The system has an architecture with a general-purpose processor accompanied by a set of heterogeneous autonomous programmable modules, each providing an energy efficient implementation of dedicated tasks. A reconfigurable internal communication network switch exploits locality of reference and eliminates wasteful data copies

    Fine-grained parallelization of fitness functions in bioinformatics optimization problems: gene selection for cancer classification and biclustering of gene expression data

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    ANTECEDENTES: las metaheurĂ­sticas se utilizan ampliamente para resolver grandes problemas de optimizaciĂłn combinatoria en bioinformĂĄtica debido al enorme conjunto de posibles soluciones. Dos problemas representativos son la selecciĂłn de genes para la clasificaciĂłn del cĂĄncer y el agrupamiento de los datos de expresiĂłn gĂ©nica. En la mayorĂ­a de los casos, estas metaheurĂ­sticas, asĂ­ como otras tĂ©cnicas no lineales, aplican una funciĂłn de adecuaciĂłn a cada soluciĂłn posible con una poblaciĂłn de tamaño limitado, y ese paso involucra latencias mĂĄs altas que otras partes de los algoritmos, lo cual es la razĂłn por la cual el tiempo de ejecuciĂłn de las aplicaciones dependerĂĄ principalmente del tiempo de ejecuciĂłn de la funciĂłn de aptitud. AdemĂĄs, es habitual encontrar formulaciones aritmĂ©ticas de punto flotante para las funciones de fitness. De esta manera, una paralelizaciĂłn cuidadosa de estas funciones utilizando la tecnologĂ­a de hardware reconfigurable acelerarĂĄ el cĂĄlculo, especialmente si se aplican en paralelo a varias soluciones de la poblaciĂłn. RESULTADOS: una paralelizaciĂłn de grano fino de dos funciones de aptitud de punto flotante de diferentes complejidades y caracterĂ­sticas involucradas en el biclustering de los datos de expresiĂłn gĂ©nica y la selecciĂłn de genes para la clasificaciĂłn del cĂĄncer permitiĂł obtener mayores aceleraciones y cĂłmputos de potencia reducida con respecto a los microprocesadores habituales. CONCLUSIONES: Los resultados muestran mejores rendimientos utilizando tecnologĂ­a de hardware reconfigurable en lugar de los microprocesadores habituales, en tĂ©rminos de tiempo de consumo y consumo de energĂ­a, no solo debido a la paralelizaciĂłn de las operaciones aritmĂ©ticas, sino tambiĂ©n gracias a la evaluaciĂłn de aptitud concurrente para varios individuos de la poblaciĂłn en La metaheurĂ­stica. Esta es una buena base para crear soluciones aceleradas y de bajo consumo de energĂ­a para escenarios informĂĄticos intensivos.BACKGROUND: Metaheuristics are widely used to solve large combinatorial optimization problems in bioinformatics because of the huge set of possible solutions. Two representative problems are gene selection for cancer classification and biclustering of gene expression data. In most cases, these metaheuristics, as well as other non-linear techniques, apply a fitness function to each possible solution with a size-limited population, and that step involves higher latencies than other parts of the algorithms, which is the reason why the execution time of the applications will mainly depend on the execution time of the fitness function. In addition, it is usual to find floating-point arithmetic formulations for the fitness functions. This way, a careful parallelization of these functions using the reconfigurable hardware technology will accelerate the computation, specially if they are applied in parallel to several solutions of the population. RESULTS: A fine-grained parallelization of two floating-point fitness functions of different complexities and features involved in biclustering of gene expression data and gene selection for cancer classification allowed for obtaining higher speedups and power-reduced computation with regard to usual microprocessors. CONCLUSIONS: The results show better performances using reconfigurable hardware technology instead of usual microprocessors, in computing time and power consumption terms, not only because of the parallelization of the arithmetic operations, but also thanks to the concurrent fitness evaluation for several individuals of the population in the metaheuristic. This is a good basis for building accelerated and low-energy solutions for intensive computing scenarios.‱ Ministerio de EconomĂ­a y Competitividad y Fondos FEDER. Contrato TIN2012-30685 (I+D+i) ‱ Gobierno de Extremadura. Ayuda GR15011 para grupos TIC015 ‱ CONICYT/FONDECYT/REGULAR/1160455. Beca para Ricardo Soto GuzmĂĄn ‱ CONICYT/FONDECYT/REGULAR/1140897. Beca para Broderick CrawfordpeerReviewe

    Domain-specific and reconfigurable instruction cells based architectures for low-power SoC

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    Mapping DSP algorithms to a reconfigurable architecture Adaptive Wireless Networking (AWGN)

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    This report will discuss the Adaptive Wireless Networking project. The vision of the Adaptive Wireless Networking project will be given. The strategy of the project will be the implementation of multiple communication systems in dynamically reconfigurable heterogeneous hardware. An overview of a wireless LAN communication system, namely HiperLAN/2, and a Bluetooth communication system will be given. Possible implementations of these systems in a dynamically reconfigurable architecture are discussed. Suggestions for future activities in the Adaptive Wireless Networking project are also given
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