56,612 research outputs found

    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

    Softer perspectives on enhancing the patient experience using IS/IT

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    Purpose – This paper aims to argue that the implementation of the Choose and Book system has failed due to the inability of project sponsors to appreciate the complex and far-reaching softer implications of the implementation, especially in a complex organisation such as the NHS, which has multifarious stakeholders. Design/methodology/approach – The authors use practice-oriented research to try and isolate key parameters. These parameters are compared with existing conventional thinking in a number of focused areas. Findings – Like many previous NHS initiatives, the focus of this system is in its obvious link to patients. However we find that although this project has cultural, social and organisational implications, programme managers and champions of the Connecting for Health programme emphasised the technical domains to IS/IT adoption. Research limitations/implications – This paper has been written in advance of a fully implemented Choose and Book system. Practical implications – The paper requests that more attention be paid to the softer side of IS/IT delivery, implementation, introduction and adoption. Originality/value – The paper shows that patient experience within the UK healthcare sector is still well below what is desired

    An Approach for the Empirical Validation of Software Complexity Measures

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    Software metrics are widely accepted tools to control and assure software quality. A large number of software metrics with a variety of content can be found in the literature; however most of them are not adopted in industry as they are seen as irrelevant to needs, as they are unsupported, and the major reason behind this is due to improper empirical validation. This paper tries to identify possible root causes for the improper empirical validation of the software metrics. A practical model for the empirical validation of software metrics is proposed along with root causes. The model is validated by applying it to recently proposed and well known metrics

    Integrated Solution Support System for Water Management

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    Solving water management problems involves technical, social, economic, political and legal challenges and thus requires an integrated approach involving people from different backgrounds and roles. The integrated approach has been given a prominent role within the European Union¿s Water Framework Directive (WFD). The WFD requires an integrated approach in water management to achieve good ecological status of all water bodies. It consists amongst others of the following main planning stages: describing objectives, assessing present state, identifying gaps between objectives and present state, developing management plan, implementing measures and evaluating their impacts. The directive prescribes broad participation and consultation to achieve its objectives. Besides the obvious desktop software, such an integrated approach can benefit from using a variety of support tools. In addition to tools for specific tasks such as numerical models and questionnaires, knowledge bases on options and process support tools may be utilized. Water stress, defined as the lack of water of appropriate quality is one issue related to, but not specifically addressed by the WFD. However, like in the WFD, a participatory approach could be used to mitigate water stress. Similarly various tools can or need to be used in such a complex process. In the AquaStress Integrated project the Integrated Solution Support System (I3S ¿ I-triple-S) is developed. One of the cornerstones of the approach taken in AquaStress is that organizing available knowledge provides sufficient information to improve the possibility to make a water stress mitigation process truly end-user driven, meaning that dedicated local information is only collected after specific need is expressed by the stakeholders in the process. The novelty of the I3S lies in the combination of such knowledge stored in knowledge-bases, with adaptable workflow management facilities and with specific task-oriented tools ¿ all originating from different sources. This paper describes the I3S

    Do System Test Cases Grow Old?

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    Companies increasingly use either manual or automated system testing to ensure the quality of their software products. As a system evolves and is extended with new features the test suite also typically grows as new test cases are added. To ensure software quality throughout this process the test suite is continously executed, often on a daily basis. It seems likely that newly added tests would be more likely to fail than older tests but this has not been investigated in any detail on large-scale, industrial software systems. Also it is not clear which methods should be used to conduct such an analysis. This paper proposes three main concepts that can be used to investigate aging effects in the use and failure behavior of system test cases: test case activation curves, test case hazard curves, and test case half-life. To evaluate these concepts and the type of analysis they enable we apply them on an industrial software system containing more than one million lines of code. The data sets comes from a total of 1,620 system test cases executed a total of more than half a million times over a time period of two and a half years. For the investigated system we find that system test cases stay active as they age but really do grow old; they go through an infant mortality phase with higher failure rates which then decline over time. The test case half-life is between 5 to 12 months for the two studied data sets.Comment: Updated with nicer figs without border around the

    Cloud engineering is search based software engineering too

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    Many of the problems posed by the migration of computation to cloud platforms can be formulated and solved using techniques associated with Search Based Software Engineering (SBSE). Much of cloud software engineering involves problems of optimisation: performance, allocation, assignment and the dynamic balancing of resources to achieve pragmatic trade-offs between many competing technical and business objectives. SBSE is concerned with the application of computational search and optimisation to solve precisely these kinds of software engineering challenges. Interest in both cloud computing and SBSE has grown rapidly in the past five years, yet there has been little work on SBSE as a means of addressing cloud computing challenges. Like many computationally demanding activities, SBSE has the potential to benefit from the cloud; ‘SBSE in the cloud’. However, this paper focuses, instead, of the ways in which SBSE can benefit cloud computing. It thus develops the theme of ‘SBSE for the cloud’, formulating cloud computing challenges in ways that can be addressed using SBSE
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