1,570 research outputs found

    Elastic systems

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    Elastic systems provide tolerance to the variations in computation and communication delays. The incorporation of elasticity opens new opportunities for optimization using new correct-by-construction transformations that cannot be applied to rigid non-elastic systems. The basics of synchronous and asynchronous elastic systems will be reviewed. A set of behavior-preserving transformations will be presented: retiming, recycling, early evaluation, variable-latency units and speculative execution. The application of these transformations for performance and power optimization will be discussed. Finally, a novel framework for microarchitectural exploration will be introduced, showing that the optimal pipelining of a circuit can be automatically obtained by using the previous transformations.Peer ReviewedPostprint (published version

    A Multifunctional Processing Board for the Fast Track Trigger of the H1 Experiment

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    The electron-proton collider HERA is being upgraded to provide higher luminosity from the end of the year 2001. In order to enhance the selectivity on exclusive processes a Fast Track Trigger (FTT) with high momentum resolution is being built for the H1 Collaboration. The FTT will perform a 3-dimensional reconstruction of curved tracks in a magnetic field of 1.1 Tesla down to 100 MeV in transverse momentum. It is able to reconstruct up to 48 tracks within 23 mus in a high track multiplicity environment. The FTT consists of two hardware levels L1, L2 and a third software level. Analog signals of 450 wires are digitized at the first level stage followed by a quick lookup of valid track segment patterns. For the main processing tasks at the second level such as linking, fitting and deciding, a multifunctional processing board has been developed by the ETH Zurich in collaboration with Supercomputing Systems (Zurich). It integrates a high-density FPGA (Altera APEX 20K600E) and four floating point DSPs (Texas Instruments TMS320C6701). This presentation will mainly concentrate on second trigger level hardware aspects and on the implementation of the algorithms used for linking and fitting. Emphasis is especially put on the integrated CAM (content addressable memory) functionality of the FPGA, which is ideally suited for implementing fast search tasks like track segment linking.Comment: 6 pages, 4 figures, submitted to TN

    Policies of System Level Pipeline Modeling

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    Pipelining is a well understood and often used implementation technique for increasing the performance of a hardware system. We develop several SystemC/C++ modeling techniques that allow us to quickly model, simulate, and evaluate pipelines. We employ a small domain specific language (DSL) based on resource usage patterns that automates the drudgery of boilerplate code needed to configure connectivity in simulation models. The DSL is embedded directly in the host modeling language SystemC/C++. Additionally we develop several techniques for parameterizing a pipeline's behavior based on policies of function, communication, and timing (performance modeling)

    Communication costs in a multi-tiered MPSoC

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    The amount of digital processing required for phased array beamformers is very large. It requires many parallel processors, which can be organized in a multi-tiered structure. Communication costs differ for each of the stages in such an architecture. For example, communication costs from the antenna front-end to the first processing stages is costly because of the amount of connections and data rate. Furthermore there is a trade-off between sequential processing exploiting locality of reference versus exploiting parallelism but adding communication costs. Thus, the optimal architecture depends on the importance that is given to the different measures.\ud \ud A model is presented to determine the partitioning of a (beamforming) system based on communication costs. It is shown that different solutions can be explored based on the cost model and the incorporated quantitative and qualitative measures. Determining the importance of each measure is subjective to the situation and application. In this work a simple beamforming application is used optimised for energy efficiency
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