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OpenAlex topic

Parallel Computing and Optimization Techniques

This page lists works and academicians tagged with an OpenAlex topic. It is not a YÖKSİS primary or secondary field.

OpenAlex 1,191 works 59 author topics

Works

1,191 works

  1. YÖKSİS SJR Q1 JCR Q2 OpenAlex top 1% OpenAlex 99.4%

    Efficient application scheduling is critical for achieving high performance in heterogeneous computing environments. The application scheduling problem has been shown to be NP-complete in general cases as well as in several restricted cases. Because of its key importance, this problem has been extensively studied and…

  2. YÖKSİS SJR Q1 JCR Q1 OpenAlex top 1% OpenAlex 99.9%

    No abstract yet.

  3. OpenAlex top 1% OpenAlex 99.9%

    We address power-aware scheduling of periodic tasks to reduce CPU energy consumption in hard real-time systems through dynamic voltage scaling. Our intertask voltage scheduling solution includes three components: 1) a static (offline) solution to compute the optimal speed, assuming worst-case workload for each arrival…

  4. OpenAlex top 1% OpenAlex 99.9%

    In this paper we address power-aware scheduling of periodic hard real-time tasks using dynamic voltage scaling. Our solution includes three parts: (a) a static (off-line) solution to compute the optimal speed, assuming worst-case workload for each arrival, (b) an on-line speed reduction mechanism to reclaim energy by…

  5. OpenAlex top 10% OpenAlex 97.8%

    In this paper, we address the problem of partitioning periodic real-time tasks in a multiprocessor platform by considering both feasibility and energy-awareness perspectives: our objective is to compute the feasible partitioning that results in minimum energy consumption on multiple identical processors by using varia…

  6. OpenAlex top 1% OpenAlex 99.6%

    Deep networks are state-of-the-art models used for understanding the content of images, videos, audio and raw input data. Current computing systems are not able to run deep network models in real-time with low power consumption. In this paper we present nn-X: a scalable, low-power coprocessor for enabling real-time ex…

  7. OpenAlex top 10% OpenAlex 96.6%

    Optimizations aimed at improving the efficiency of on-chip memories are extremely important. We propose a compiler-controlled dynamic on-chip scratch-pad memory (SPM) management framework that uses both loop and data transformations. Experimental results obtained using a generic cost model indicate significant reducti…

  8. YÖKSİS SJR Q3 JCR Q3 OpenAlex top 1% OpenAlex 100.0%

    No abstract yet.

  9. YÖKSİS SJR Q1 JCR Q2 OpenAlex top 1% OpenAlex 99.7%

    In embedded computing, cost, power, and performance constraints call for the design of specialized processors, rather than for the use of the existing off-the-shelf solutions. While the design of these application-specific CPUs could be tackled from scratch, a cheaper and more effective option is that of extending the…

  10. OpenAlex top 10% OpenAlex 98.8%

    In this paper, we provide an efficient solution for periodic real-time tasks with (potentially) different power consumption characteristics. We show that a task T/sub i/ can run at a constant speed S/sub i/ at every instance without hurting optimality. We sketch an O(n/sup 2/ log n) algorithm to compute the optimal S/…

  11. OpenAlex top 10% OpenAlex 98.1%

    Create low power, higher performance circuits with shorter design times using this practical guide to asynchronous design. This practical alternative to conventional synchronous design enables performance close to full-custom designs with design times that approach commercially available ASIC standard cell flows. It i…

  12. OpenAlex top 1% OpenAlex 99.8%

    This article presents a survey of energy-aware scheduling algorithms proposed for real-time systems. The analysis presents the main results starting from the middle 1990s until today, showing how the proposed solutions evolved to address the evolution of the platform's features and needs. The survey first presents a t…

Academicians

59 academicians