کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
710469 892110 2016 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Investigation of Q-learning applied to DVFS management of a System-on-Chip
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مکانیک محاسباتی
پیش نمایش صفحه اول مقاله
Investigation of Q-learning applied to DVFS management of a System-on-Chip
چکیده انگلیسی

This paper presents a new Q-learning based strategy to manage Dynamic Voltage Frequency Scaling (DVFS) on a system on chip (SoC) such that the energy consumption is reduced. We address software applications with throughput constraints. The proposed Q-learning formulation has two main advantages: it has a reduced state space to limit the overhead and it embeds a new reward function tailored for throughput-constrained applications. The DVFS manager is evaluated on a test chip executing an HMAX object recognition application. We perform an experimental investigation of the main Q-learning parameters. The results suggest that the proposed method reduces the energy consumed with up to 44% at the cost of occasionally increasing the number of throughput violations, when compared to two state-of-the-art feedback controllers that address the same application domain.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: IFAC-PapersOnLine - Volume 49, Issue 5, 2016, Pages 278–284
نویسندگان
, , , ,