99,935 research outputs found

    Efficient resources assignment schemes for clustered multithreaded processors

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    New feature sizes provide larger number of transistors per chip that architects could use in order to further exploit instruction level parallelism. However, these technologies bring also new challenges that complicate conventional monolithic processor designs. On the one hand, exploiting instruction level parallelism is leading us to diminishing returns and therefore exploiting other sources of parallelism like thread level parallelism is needed in order to keep raising performance with a reasonable hardware complexity. On the other hand, clustering architectures have been widely studied in order to reduce the inherent complexity of current monolithic processors. This paper studies the synergies and trade-offs between two concepts, clustering and simultaneous multithreading (SMT), in order to understand the reasons why conventional SMT resource assignment schemes are not so effective in clustered processors. These trade-offs are used to propose a novel resource assignment scheme that gets and average speed up of 17.6% versus Icount improving fairness in 24%.Peer ReviewedPostprint (published version

    Power efficient job scheduling by predicting the impact of processor manufacturing variability

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    Modern CPUs suffer from performance and power consumption variability due to the manufacturing process. As a result, systems that do not consider such variability caused by manufacturing issues lead to performance degradations and wasted power. In order to avoid such negative impact, users and system administrators must actively counteract any manufacturing variability. In this work we show that parallel systems benefit from taking into account the consequences of manufacturing variability when making scheduling decisions at the job scheduler level. We also show that it is possible to predict the impact of this variability on specific applications by using variability-aware power prediction models. Based on these power models, we propose two job scheduling policies that consider the effects of manufacturing variability for each application and that ensure that power consumption stays under a system-wide power budget. We evaluate our policies under different power budgets and traffic scenarios, consisting of both single- and multi-node parallel applications, utilizing up to 4096 cores in total. We demonstrate that they decrease job turnaround time, compared to contemporary scheduling policies used on production clusters, up to 31% while saving up to 5.5% energy.Postprint (author's final draft

    Architectural support for task dependence management with flexible software scheduling

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    The growing complexity of multi-core architectures has motivated a wide range of software mechanisms to improve the orchestration of parallel executions. Task parallelism has become a very attractive approach thanks to its programmability, portability and potential for optimizations. However, with the expected increase in core counts, finer-grained tasking will be required to exploit the available parallelism, which will increase the overheads introduced by the runtime system. This work presents Task Dependence Manager (TDM), a hardware/software co-designed mechanism to mitigate runtime system overheads. TDM introduces a hardware unit, denoted Dependence Management Unit (DMU), and minimal ISA extensions that allow the runtime system to offload costly dependence tracking operations to the DMU and to still perform task scheduling in software. With lower hardware cost, TDM outperforms hardware-based solutions and enhances the flexibility, adaptability and composability of the system. Results show that TDM improves performance by 12.3% and reduces EDP by 20.4% on average with respect to a software runtime system. Compared to a runtime system fully implemented in hardware, TDM achieves an average speedup of 4.2% with 7.3x less area requirements and significant EDP reductions. In addition, five different software schedulers are evaluated with TDM, illustrating its flexibility and performance gains.This work has been supported by the RoMoL ERC Advanced Grant (GA 321253), by the European HiPEAC Network of Excellence, by the Spanish Ministry of Science and Innovation (contracts TIN2015-65316-P, TIN2016-76635-C2-2-R and TIN2016-81840-REDT), by the Generalitat de Catalunya (contracts 2014-SGR-1051 and 2014-SGR-1272), and by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 671697 and No. 671610. M. Moretó has been partially supported by the Ministry of Economy and Competitiveness under Juan de la Cierva postdoctoral fellowship number JCI-2012-15047.Peer ReviewedPostprint (author's final draft

    Smart objects as building blocks for the internet of things

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    The combination of the Internet and emerging technologies such as nearfield communications, real-time localization, and embedded sensors lets us transform everyday objects into smart objects that can understand and react to their environment. Such objects are building blocks for the Internet of Things and enable novel computing applications. As a step toward design and architectural principles for smart objects, the authors introduce a hierarchy of architectures with increasing levels of real-world awareness and interactivity. In particular, they describe activity-, policy-, and process-aware smart objects and demonstrate how the respective architectural abstractions support increasingly complex application

    On perceptual expertise

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    Expertise is a cognitive achievement that clearly involves experience and learning, and often requires explicit, time-consuming training specific to the relevant domain. It is also intuitive that this kind of achievement is, in a rich sense, genuinely perceptual. Many experts—be they radiologists, bird watchers, or fingerprint examiners—are better perceivers in the domain(s) of their expertise. The goal of this paper is to motivate three related claims, by substantial appeal to recent empirical research on perceptual expertise: Perceptual expertise is genuinely perceptual and genuinely cognitive, and this phenomenon reveals how we can become epistemically better perceivers. These claims are defended against sceptical opponents that deny significant top-down or cognitive effects on perception, and opponents who maintain that any such effects on perception are epistemically pernicious

    Healing the liminal space: a student project on the Nicosia buffer zone

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    On 17th October 2008 twelve sixth year architecture students from the School of Planning, Architecture and Civil Engineering at the Queen’s University Belfast were granted unprecedented access by the United Nations to enter the buffer zone of Nicosia’s walled city. This was a unique opportunity to experience and survey the selected sites for their senior theses design proposals which targeted the liminal space contained in the buffer zone since its complete physical division in 1974 and aimed at reuniting the walled city through urban design and architecture. This paper firstly explains the context of the study and the role of the Nicosia Master Plan in reshaping Nicosia’s urban growth. It then summarizes students’ experience conducting the two the field trips to Nicosia. And finally it presents the design contributions from the 12 students, the design challenges they faced and the important topics that emerged
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