Constrained Energy Optimization in Heterogeneous Platforms using Generalized Scaling Models

abstract: Mobile platforms are becoming highly heterogeneous by combining a powerful multiprocessor system-on-chip (MpSoC) with numerous resources including display, memory, power management IC (PMIC), battery and wireless modems into a compact package. Furthermore, the MpSoC itself is a heterogeneo...

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Other Authors: Gupta, Ujjwal (Author)
Format: Dissertation
Language:English
Published: 2014
Subjects:
Online Access:http://hdl.handle.net/2286/R.I.25831
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spelling ndltd-asu.edu-item-258312018-06-22T03:05:19Z Constrained Energy Optimization in Heterogeneous Platforms using Generalized Scaling Models abstract: Mobile platforms are becoming highly heterogeneous by combining a powerful multiprocessor system-on-chip (MpSoC) with numerous resources including display, memory, power management IC (PMIC), battery and wireless modems into a compact package. Furthermore, the MpSoC itself is a heterogeneous resource that integrates many processing elements such as CPU cores, GPU, video, image, and audio processors. As a result, optimization approaches targeting mobile computing needs to consider the platform at various levels of granularity. Platform energy consumption and responsiveness are two major considerations for mobile systems since they determine the battery life and user satisfaction, respectively. In this work, the models for power consumption, response time, and energy consumption of heterogeneous mobile platforms are presented. Then, these models are used to optimize the energy consumption of baseline platforms under power, response time, and temperature constraints with and without introducing new resources. It is shown, the optimal design choices depend on dynamic power management algorithm, and adding new resources is more energy efficient than scaling existing resources alone. The framework is verified through actual experiments on Qualcomm Snapdragon 800 based tablet MDP/T. Furthermore, usage of the framework at both design and runtime optimization is also presented. Dissertation/Thesis Gupta, Ujjwal (Author) Ogras, Umit Y. (Advisor) Ozev, Sule (Committee member) Chakrabarti, Chaitali (Committee member) Arizona State University (Publisher) Electrical engineering Computer engineering Energy consumption Mobile platoforms MpSoC Optimization eng 91 pages Masters Thesis Electrical Engineering 2014 Masters Thesis http://hdl.handle.net/2286/R.I.25831 http://rightsstatements.org/vocab/InC/1.0/ All Rights Reserved 2014
collection NDLTD
language English
format Dissertation
sources NDLTD
topic Electrical engineering
Computer engineering
Energy consumption
Mobile platoforms
MpSoC
Optimization
spellingShingle Electrical engineering
Computer engineering
Energy consumption
Mobile platoforms
MpSoC
Optimization
Constrained Energy Optimization in Heterogeneous Platforms using Generalized Scaling Models
description abstract: Mobile platforms are becoming highly heterogeneous by combining a powerful multiprocessor system-on-chip (MpSoC) with numerous resources including display, memory, power management IC (PMIC), battery and wireless modems into a compact package. Furthermore, the MpSoC itself is a heterogeneous resource that integrates many processing elements such as CPU cores, GPU, video, image, and audio processors. As a result, optimization approaches targeting mobile computing needs to consider the platform at various levels of granularity. Platform energy consumption and responsiveness are two major considerations for mobile systems since they determine the battery life and user satisfaction, respectively. In this work, the models for power consumption, response time, and energy consumption of heterogeneous mobile platforms are presented. Then, these models are used to optimize the energy consumption of baseline platforms under power, response time, and temperature constraints with and without introducing new resources. It is shown, the optimal design choices depend on dynamic power management algorithm, and adding new resources is more energy efficient than scaling existing resources alone. The framework is verified through actual experiments on Qualcomm Snapdragon 800 based tablet MDP/T. Furthermore, usage of the framework at both design and runtime optimization is also presented. === Dissertation/Thesis === Masters Thesis Electrical Engineering 2014
author2 Gupta, Ujjwal (Author)
author_facet Gupta, Ujjwal (Author)
title Constrained Energy Optimization in Heterogeneous Platforms using Generalized Scaling Models
title_short Constrained Energy Optimization in Heterogeneous Platforms using Generalized Scaling Models
title_full Constrained Energy Optimization in Heterogeneous Platforms using Generalized Scaling Models
title_fullStr Constrained Energy Optimization in Heterogeneous Platforms using Generalized Scaling Models
title_full_unstemmed Constrained Energy Optimization in Heterogeneous Platforms using Generalized Scaling Models
title_sort constrained energy optimization in heterogeneous platforms using generalized scaling models
publishDate 2014
url http://hdl.handle.net/2286/R.I.25831
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