8,413 research outputs found

    Scoping Study for a Realistic Driving Simulator: Final Report.

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    1. INTRODUCTION This report documents the results of a study carried out between December 1989 and March 1990 to determine the most suitable equipment to be purchased for building a driving simulator at the Institute for Transport Studies at the University of Leeds. This "scoping study" was intended to accomplish three main tasks: 1. A review of existing facilities both in the UK and elsewhere in Europe to ascertain what has already been achieved and what is the current state of the art. 2. Initial discussions with potential users on desired features to be built in to the simulator. 3. Discussions with equipment suppliers in the light of what was found out in Tasks 1 and 2, so that the appropriate equipment could be specified. The report documents in subsequent sections the findings of the first two tasks. It then summarizes the conclusions that were reached on the overall simulator design, on the required features of the simulator and on the effort required to develop an operational simulator from the various hardware components. Finally, recommendations are made on the equipment to be purchased in the light of the recommended configuration, the discussion with equipment suppliers under Task 3 and the budget allocated

    The Glasgow raspberry pi cloud: a scale model for cloud computing infrastructures

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    Data Centers (DC) used to support Cloud services often consist of tens of thousands of networked machines under a single roof. The significant capital outlay required to replicate such infrastructures constitutes a major obstacle to practical implementation and evaluation of research in this domain. Currently, most research into Cloud computing relies on either limited software simulation, or the use of a testbed environments with a handful of machines. The recent introduction of the Raspberry Pi, a low-cost, low-power single-board computer, has made the construction of a miniature Cloud DCs more affordable. In this paper, we present the Glasgow Raspberry Pi Cloud (PiCloud), a scale model of a DC composed of clusters of Raspberry Pi devices. The PiCloud emulates every layer of a Cloud stack, ranging from resource virtualisation to network behaviour, providing a full-featured Cloud Computing research and educational environment

    PROFET: modeling system performance and energy without simulating the CPU

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    The approaching end of DRAM scaling and expansion of emerging memory technologies is motivating a lot of research in future memory systems. Novel memory systems are typically explored by hardware simulators that are slow and often have a simplified or obsolete abstraction of the CPU. This study presents PROFET, an analytical model that predicts how an application's performance and energy consumption changes when it is executed on different memory systems. The model is based on instrumentation of an application execution on actual hardware, so it already takes into account CPU microarchitectural details such as the data prefetcher and out-of-order engine. PROFET is evaluated on two real platforms: Sandy Bridge-EP E5-2670 and Knights Landing Xeon Phi platforms with various memory configurations. The evaluation results show that PROFET's predictions are accurate, typically with only 2% difference from the values measured on actual hardware. We release the PROFET source code and all input data required for memory system and application profiling. The released package can be seamlessly installed and used on high-end Intel platforms.Peer ReviewedPostprint (author's final draft

    Parallel simulation of Population Dynamics P systems: updates and roadmap

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    Population Dynamics P systems are a type of multienvironment P systems that serve as a formal modeling framework for real ecosystems. The accurate simulation of these probabilisticmodels, e.g. with Direct distribution based on Consistent Blocks Algorithm, entails large run times. Hence, parallel platforms such as GPUs have been employed to speedup the simulation. In 2012, the first GPU simulator of PDP systems was presented. However, it was able to run only randomly generated PDP systems. In this paper, we present current updates made on this simulator, involving an input modu le for binary files and an output module for CSV files. Finally, the simulator has been experimentally validated with a real ecosystem model, and its performance has been tested with two high-end GPUs: Tesla C1060 and K40.Ministerio de EconomĂ­a y Competitividad TIN2012-37434Junta de AndalucĂ­a P08-TIC-0420
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