965 resultados para Application specific architectures


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This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

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This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding the management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

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In recent future, wireless sensor networks (WSNs) will experience a broad high-scale deployment (millions of nodes in the national area) with multiple information sources per node, and with very specific requirements for signal processing. In parallel, the broad range deployment of WSNs facilitates the definition and execution of ambitious studies, with a large input data set and high computational complexity. These computation resources, very often heterogeneous and driven on-demand, can only be satisfied by high-performance Data Centers (DCs). The high economical and environmental impact of the energy consumption in DCs requires aggressive energy optimization policies. These policies have been already detected but not successfully proposed. In this context, this paper shows the following on-going research lines and obtained results. In the field of WSNs: energy optimization in the processing nodes from different abstraction levels, including reconfigurable application specific architectures, efficient customization of the memory hierarchy, energy-aware management of the wireless interface, and design automation for signal processing applications. In the field of DCs: energy-optimal workload assignment policies in heterogeneous DCs, resource management policies with energy consciousness, and efficient cooling mechanisms that will cooperate in the minimization of the electricity bill of the DCs that process the data provided by the WSNs.

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In recent future, wireless sensor networks ({WSNs}) will experience a broad high-scale deployment (millions of nodes in the national area) with multiple information sources per node, and with very specific requirements for signal processing. In parallel, the broad range deployment of {WSNs} facilitates the definition and execution of ambitious studies, with a large input data set and high computational complexity. These computation resources, very often heterogeneous and driven on-demand, can only be satisfied by high-performance Data Centers ({DCs}). The high economical and environmental impact of the energy consumption in {DCs} requires aggressive energy optimization policies. These policies have been already detected but not successfully proposed. In this context, this paper shows the following on-going research lines and obtained results. In the field of {WSNs}: energy optimization in the processing nodes from different abstraction levels, including reconfigurable application specific architectures, efficient customization of the memory hierarchy, energy-aware management of the wireless interface, and design automation for signal processing applications. In the field of {DCs}: energy-optimal workload assignment policies in heterogeneous {DCs}, resource management policies with energy consciousness, and efficient cooling mechanisms that will cooperate in the minimization of the electricity bill of the DCs that process the data provided by the WSNs.

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Paper submitted to 10th IEEE International Conference on Electronics, Circuits and Systems (ICECS), Sharjah, Emiratos Árabes, 2003.

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Recent integrated circuit technologies have opened the possibility to design parallel architectures with hundreds of cores on a single chip. The design space of these parallel architectures is huge with many architectural options. Exploring the design space gets even more difficult if, beyond performance and area, we also consider extra metrics like performance and area efficiency, where the designer tries to design the architecture with the best performance per chip area and the best sustainable performance. In this paper we present an algorithm-oriented approach to design a many-core architecture. Instead of doing the design space exploration of the many core architecture based on the experimental execution results of a particular benchmark of algorithms, our approach is to make a formal analysis of the algorithms considering the main architectural aspects and to determine how each particular architectural aspect is related to the performance of the architecture when running an algorithm or set of algorithms. The architectural aspects considered include the number of cores, the local memory available in each core, the communication bandwidth between the many-core architecture and the external memory and the memory hierarchy. To exemplify the approach we did a theoretical analysis of a dense matrix multiplication algorithm and determined an equation that relates the number of execution cycles with the architectural parameters. Based on this equation a many-core architecture has been designed. The results obtained indicate that a 100 mm(2) integrated circuit design of the proposed architecture, using a 65 nm technology, is able to achieve 464 GFLOPs (double precision floating-point) for a memory bandwidth of 16 GB/s. This corresponds to a performance efficiency of 71 %. Considering a 45 nm technology, a 100 mm(2) chip attains 833 GFLOPs which corresponds to 84 % of peak performance These figures are better than those obtained by previous many-core architectures, except for the area efficiency which is limited by the lower memory bandwidth considered. The results achieved are also better than those of previous state-of-the-art many-cores architectures designed specifically to achieve high performance for matrix multiplication.

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This thesis deals with Context Aware Services, Smart Environments, Context Management and solutions for Devices and Service Interoperability. Multi-vendor devices offer an increasing number of services and end-user applications that base their value on the ability to exploit the information originating from the surrounding environment by means of an increasing number of embedded sensors, e.g. GPS, compass, RFID readers, cameras and so on. However, usually such devices are not able to exchange information because of the lack of a shared data storage and common information exchange methods. A large number of standards and domain specific building blocks are available and are heavily used in today's products. However, the use of these solutions based on ready-to-use modules is not without problems. The integration and cooperation of different kinds of modules can be daunting because of growing complexity and dependency. In this scenarios it might be interesting to have an infrastructure that makes the coexistence of multi-vendor devices easy, while enabling low cost development and smooth access to services. This sort of technologies glue should reduce both software and hardware integration costs by removing the trouble of interoperability. The result should also lead to faster and simplified design, development and, deployment of cross-domain applications. This thesis is mainly focused on SW architectures supporting context aware service providers especially on the following subjects: - user preferences service adaptation - context management - content management - information interoperability - multivendor device interoperability - communication and connectivity interoperability Experimental activities were carried out in several domains including Cultural Heritage, indoor and personal smart spaces – all of which are considered significant test-beds in Context Aware Computing. The work evolved within european and national projects: on the europen side, I carried out my research activity within EPOCH, the FP6 Network of Excellence on “Processing Open Cultural Heritage” and within SOFIA, a project of the ARTEMIS JU on embedded systems. I worked in cooperation with several international establishments, including the University of Kent, VTT (the Technical Reserarch Center of Finland) and Eurotech. On the national side I contributed to a one-to-one research contract between ARCES and Telecom Italia. The first part of the thesis is focused on problem statement and related work and addresses interoperability issues and related architecture components. The second part is focused on specific architectures and frameworks: - MobiComp: a context management framework that I used in cultural heritage applications - CAB: a context, preference and profile based application broker which I designed within EPOCH Network of Excellence - M3: "Semantic Web based" information sharing infrastructure for smart spaces designed by Nokia within the European project SOFIA - NoTa: a service and transport independent connectivity framework - OSGi: the well known Java based service support framework The final section is dedicated to the middleware, the tools and, the SW agents developed during my Doctorate time to support context-aware services in smart environments.

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Nowadays the production of increasingly complex and electrified vehicles requires the implementation of new control and monitoring systems. This reason, together with the tendency of moving rapidly from the test bench to the vehicle, leads to a landscape that requires the development of embedded hardware and software to face the application effectively and efficiently. The development of application-based software on real-time/FPGA hardware could be a good answer for these challenges: FPGA grants parallel low-level and high-speed calculation/timing, while the Real-Time processor can handle high-level calculation layers, logging and communication functions with determinism. Thanks to the software flexibility and small dimensions, these architectures can find a perfect collocation as engine RCP (Rapid Control Prototyping) units and as smart data logger/analyser, both for test bench and on vehicle application. Efforts have been done for building a base architecture with common functionalities capable of easily hosting application-specific control code. Several case studies originating in this scenario will be shown; dedicated solutions for protype applications have been developed exploiting a real-time/FPGA architecture as ECU (Engine Control Unit) and custom RCP functionalities, such as water injection and testing hydraulic brake control.

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Conferência: IEEE 24th International Conference on Application-Specific Systems, Architectures and Processors (ASAP)- Jun 05-07, 2013

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Actualment un típic embedded system (ex. telèfon mòbil) requereix alta qualitat per portar a terme tasques com codificar/descodificar a temps real; han de consumir poc energia per funcionar hores o dies utilitzant bateries lleugeres; han de ser el suficientment flexibles per integrar múltiples aplicacions i estàndards en un sol aparell; han de ser dissenyats i verificats en un període de temps curt tot i l’augment de la complexitat. Els dissenyadors lluiten contra aquestes adversitats, que demanen noves innovacions en arquitectures i metodologies de disseny. Coarse-grained reconfigurable architectures (CGRAs) estan emergent com a candidats potencials per superar totes aquestes dificultats. Diferents tipus d’arquitectures han estat presentades en els últims anys. L’alta granularitat redueix molt el retard, l’àrea, el consum i el temps de configuració comparant amb les FPGAs. D’altra banda, en comparació amb els tradicionals processadors coarse-grained programables, els alts recursos computacionals els permet d’assolir un alt nivell de paral•lelisme i eficiència. No obstant, els CGRAs existents no estant sent aplicats principalment per les grans dificultats en la programació per arquitectures complexes. ADRES és una nova CGRA dissenyada per I’Interuniversity Micro-Electronics Center (IMEC). Combina un processador very-long instruction word (VLIW) i un coarse-grained array per tenir dues opcions diferents en un mateix dispositiu físic. Entre els seus avantatges destaquen l’alta qualitat, poca redundància en les comunicacions i la facilitat de programació. Finalment ADRES és un patró enlloc d’una arquitectura concreta. Amb l’ajuda del compilador DRESC (Dynamically Reconfigurable Embedded System Compile), és possible trobar millors arquitectures o arquitectures específiques segons l’aplicació. Aquest treball presenta la implementació d’un codificador MPEG-4 per l’ADRES. Mostra l’evolució del codi per obtenir una bona implementació per una arquitectura donada. També es presenten les característiques principals d’ADRES i el seu compilador (DRESC). Els objectius són de reduir al màxim el nombre de cicles (temps) per implementar el codificador de MPEG-4 i veure les diferents dificultats de treballar en l’entorn ADRES. Els resultats mostren que els cícles es redueixen en un 67% comparant el codi inicial i final en el mode VLIW i un 84% comparant el codi inicial en VLIW i el final en mode CGA.

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Reusability has become more popular factor in modern software engineering. This is mainly because object-orientation has brought methods that allow reusing more easily. Today more and more application developer thinks how they can reuse already existing applications in their work. If the developer wants to use existing components outside the current project, he can use design patterns, class libraries or frameworks. These provide solution for specific or general problems that has been already encountered. Application frameworks are collection of classes that provides base for the developer. Application frameworks are mostly implementation phase tools, but can also be used in application design. The main purpose of the frameworks is separate domain specific functionalities from the application specific. Usually the frameworks are divided into two categories: black and white box. Difference between those categories is the way the reuse is done. The application frameworks provide properties that can be examined and compared between different frameworks. These properties are: extensibility, reusability, modularity and scalability. These examine how framework will handle different platforms, changes in framework, increasing demand for resources, etc. Generally application frameworks do have these properties in good level. When comparing general purpose framework and more specific purpose framework, the main difference can be located in reusability of frameworks. It is mainly because the framework designed to specific domain can have constraints from external systems and resources. With general purpose framework these are set by the application developed based on the framework.

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As the development of integrated circuit technology continues to follow Moore’s law the complexity of circuits increases exponentially. Traditional hardware description languages such as VHDL and Verilog are no longer powerful enough to cope with this level of complexity and do not provide facilities for hardware/software codesign. Languages such as SystemC are intended to solve these problems by combining the powerful expression of high level programming languages and hardware oriented facilities of hardware description languages. To fully replace older languages in the desing flow of digital systems SystemC should also be synthesizable. The devices required by modern high speed networks often share the same tight constraints for e.g. size, power consumption and price with embedded systems but have also very demanding real time and quality of service requirements that are difficult to satisfy with general purpose processors. Dedicated hardware blocks of an application specific instruction set processor are one way to combine fast processing speed, energy efficiency, flexibility and relatively low time-to-market. Common features can be identified in the network processing domain making it possible to develop specialized but configurable processor architectures. One such architecture is the TACO which is based on transport triggered architecture. The architecture offers a high degree of parallelism and modularity and greatly simplified instruction decoding. For this M.Sc.(Tech) thesis, a simulation environment for the TACO architecture was developed with SystemC 2.2 using an old version written with SystemC 1.0 as a starting point. The environment enables rapid design space exploration by providing facilities for hw/sw codesign and simulation and an extendable library of automatically configured reusable hardware blocks. Other topics that are covered are the differences between SystemC 1.0 and 2.2 from the viewpoint of hardware modeling, and compilation of a SystemC model into synthesizable VHDL with Celoxica Agility SystemC Compiler. A simulation model for a processor for TCP/IP packet validation was designed and tested as a test case for the environment.

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Caches are known to consume up to half of all system power in embedded processors. Co-optimizing performance and power of the cache subsystems is therefore an important step in the design of embedded systems, especially those employing application specific instruction processors. In this project, we propose an analytical cache model that succinctly captures the miss performance of an application over the entire cache parameter space. Unlike exhaustive trace driven simulation, our model requires that the program be simulated once so that a few key characteristics can be obtained. Using these application-dependent characteristics, the model can span the entire cache parameter space consisting of cache sizes, associativity and cache block sizes. In our unified model, we are able to cater for direct-mapped, set and fully associative instruction, data and unified caches. Validation against full trace-driven simulations shows that our model has a high degree of fidelity. Finally, we show how the model can be coupled with a power model for caches such that one can very quickly decide on pareto-optimal performance-power design points for rapid design space exploration.