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Many-core processors exhibit hundreds to thousands of cores, which can execute lots of multi-threaded tasks in parallel. Restrictive power dissipation capacity of a many-core prevents all its executing tasks from operating at their peak performance together. Furthermore, the ability of a task to exploit part of the power budget allocated to it depends upon its current execution phase. This mandates...
Low-power approximate adders provide basic building blocks for approximate computing hardware that have shown remarkable energy efficiency for error-resilient applications (like image/video processing, computer vision, etc.), especially for battery-driven portable systems. In this paper, we present a novel scalable, fast yet accurate analytical method to evaluate the output error probability of multi-bit...
We present a scalable Dynamic Power Management (DPM) schem e where malleable applications may change their degree of parallelism at run time depending upon the workload and performance constraints. We employ a per-application predictive power manager that autonomously controls the power states of the cores with the goal of energy efficiency. Furthermore, our DPM allows the applications to lend their...
Power management for Kilo-core processors have become an intricate problem due to the scalability issues and mixed-workloads of massively multi-threaded applications. This paper highlights the power related issues in Kilo-core processors and presents two emerging trends towards agent-based distributed and self-adaptive power management for Kilo-core processors. Agent-based power management allows...
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