8,921 research outputs found

    BEEBS: Open Benchmarks for Energy Measurements on Embedded Platforms

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    This paper presents and justifies an open benchmark suite named BEEBS, targeted at evaluating the energy consumption of embedded processors. We explore the possible sources of energy consumption, then select individual benchmarks from contemporary suites to cover these areas. Version one of BEEBS is presented here and contains 10 benchmarks that cover a wide range of typical embedded applications. The benchmark suite is portable across diverse architectures and is freely available. The benchmark suite is extensively evaluated, and the properties of its constituent programs are analysed. Using real hardware platforms we show case examples which illustrate the difference in power dissipation between three processor architectures and their related ISAs. We observe significant differences in the average instruction dissipation between the architectures of 4.4x, specifically 170uW/MHz (ARM Cortex-M0), 65uW/MHz (Adapteva Epiphany) and 88uW/MHz (XMOS XS1-L1)

    Evaluation of the parallel computational capabilities of embedded platforms for critical systems

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    Modern critical systems need higher performance which cannot be delivered by the simple architectures used so far. Latest embedded architectures feature multi-cores and GPUs, which can be used to satisfy this need. In this thesis we parallelise relevant applications from multiple critical domains represented in the GPU4S benchmark suite, and perform a comparison of the parallel capabilities of candidate platforms for use in critical systems. In particular, we port the open source GPU4S Bench benchmarking suite in the OpenMP programming model, and we benchmark the candidate embedded heterogeneous multi-core platforms of the H2020 UP2DATE project, NVIDIA TX2, NVIDIA Xavier and Xilinx Zynq Ultrascale+, in order to drive the selection of the research platform which will be used in the next phases of the project. Our result indicate that in terms of CPU and GPU performance, the NVIDIA Xavier is the highest performing platform

    MLPerf Inference Benchmark

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    Machine-learning (ML) hardware and software system demand is burgeoning. Driven by ML applications, the number of different ML inference systems has exploded. Over 100 organizations are building ML inference chips, and the systems that incorporate existing models span at least three orders of magnitude in power consumption and five orders of magnitude in performance; they range from embedded devices to data-center solutions. Fueling the hardware are a dozen or more software frameworks and libraries. The myriad combinations of ML hardware and ML software make assessing ML-system performance in an architecture-neutral, representative, and reproducible manner challenging. There is a clear need for industry-wide standard ML benchmarking and evaluation criteria. MLPerf Inference answers that call. In this paper, we present our benchmarking method for evaluating ML inference systems. Driven by more than 30 organizations as well as more than 200 ML engineers and practitioners, MLPerf prescribes a set of rules and best practices to ensure comparability across systems with wildly differing architectures. The first call for submissions garnered more than 600 reproducible inference-performance measurements from 14 organizations, representing over 30 systems that showcase a wide range of capabilities. The submissions attest to the benchmark's flexibility and adaptability.Comment: ISCA 202

    Life Cycle Assessment Practices: Benchmarking Selected European Automobile Manufacturers

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    With the rise of environmental concerns in the general public, re-appropriated by influential politicians, Life Cycle Assessment (LCA) has become a widely used set of tools for the management of all impacts on environment by industrial products. LCA is carried out at the very early stages of product research, development and design. This is particularly true in the automobile industry where vehicle manufacturers Original Equipment Manufacturers (OEMs) are launching several new or re-vamped models each year. The automobile industry is therefore a very emblematic sector for best practices of LCA. The paper is based on available literature and interviews with top LCA professionals in Germany-based OEMsLife cycle assessment; automobile; best practices

    Lean and green – a systematic review of the state of the art literature

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    The move towards greener operations and products has forced companies to seek alternatives to balance efficiency gains and environmental friendliness in their operations and products. The exploration of the sequential or simultaneous deployment of lean and green initiatives is the results of this balancing action. However, the lean-green topic is relatively new, and it lacks of a clear and structured research definition. Thus, this paper’s main contribution is the offering of a systematic review of the existing literature on lean and green, aimed at providing guidance on the topic, uncovering gaps and inconsistencies in the literature, and finding new paths for research. The paper identifies and structures, through a concept map, six main research streams that comprise both conceptual and empirical research conducted within the context of various organisational functions and industrial sectors. Important issues for future research are then suggested in the form of research questions. The paper’s aim is to also contribute by stimulating scholars to further study this area in depth, which will lead to a better understanding of the compatibility and impact on organisational performance of lean and green initiatives. It also holds important implications for industrialists, who can develop a deeper and richer knowledge on lean and green to help them formulate more effective strategies for their deployment

    Trade Liberalization, Technical Change and Firm Level Restructuring in the South African Automotive Component Sector

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    This paper examines the interplay between trade liberalization and the processes of learning, technical change and capability development in the South African automotive component sector. Using case studies based on firm level interviews conducted at various points since 1992, it illustrates how the technological capabilities of the industry were shaped by protection, and how this in turn mediated responses to trade liberalization initially via internal restructuring and more recently in the phase of internationalization and growing foreign ownership. In essence, the paper presents a ‘before and after’ picture of firm level responses to liberalization.- auto-parts, foreign direct investment, industrial policy, South Africa, technology, trade

    Grand Challenges of Traceability: The Next Ten Years

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    In 2007, the software and systems traceability community met at the first Natural Bridge symposium on the Grand Challenges of Traceability to establish and address research goals for achieving effective, trustworthy, and ubiquitous traceability. Ten years later, in 2017, the community came together to evaluate a decade of progress towards achieving these goals. These proceedings document some of that progress. They include a series of short position papers, representing current work in the community organized across four process axes of traceability practice. The sessions covered topics from Trace Strategizing, Trace Link Creation and Evolution, Trace Link Usage, real-world applications of Traceability, and Traceability Datasets and benchmarks. Two breakout groups focused on the importance of creating and sharing traceability datasets within the research community, and discussed challenges related to the adoption of tracing techniques in industrial practice. Members of the research community are engaged in many active, ongoing, and impactful research projects. Our hope is that ten years from now we will be able to look back at a productive decade of research and claim that we have achieved the overarching Grand Challenge of Traceability, which seeks for traceability to be always present, built into the engineering process, and for it to have "effectively disappeared without a trace". We hope that others will see the potential that traceability has for empowering software and systems engineers to develop higher-quality products at increasing levels of complexity and scale, and that they will join the active community of Software and Systems traceability researchers as we move forward into the next decade of research

    Grand Challenges of Traceability: The Next Ten Years

    Full text link
    In 2007, the software and systems traceability community met at the first Natural Bridge symposium on the Grand Challenges of Traceability to establish and address research goals for achieving effective, trustworthy, and ubiquitous traceability. Ten years later, in 2017, the community came together to evaluate a decade of progress towards achieving these goals. These proceedings document some of that progress. They include a series of short position papers, representing current work in the community organized across four process axes of traceability practice. The sessions covered topics from Trace Strategizing, Trace Link Creation and Evolution, Trace Link Usage, real-world applications of Traceability, and Traceability Datasets and benchmarks. Two breakout groups focused on the importance of creating and sharing traceability datasets within the research community, and discussed challenges related to the adoption of tracing techniques in industrial practice. Members of the research community are engaged in many active, ongoing, and impactful research projects. Our hope is that ten years from now we will be able to look back at a productive decade of research and claim that we have achieved the overarching Grand Challenge of Traceability, which seeks for traceability to be always present, built into the engineering process, and for it to have "effectively disappeared without a trace". We hope that others will see the potential that traceability has for empowering software and systems engineers to develop higher-quality products at increasing levels of complexity and scale, and that they will join the active community of Software and Systems traceability researchers as we move forward into the next decade of research
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