8.2 Hot Topic Session: No Power? No Problem! Exploiting Non-Volatility in Energy Constrained Environments

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Date: Wednesday, March 29, 2017
Time: 17:00 - 18:30
Location / Room: 4BC

Organisers:
Xiaobo Sharon Hu, University of Notre Dame, US, Contact X. Sharon Hu
Michael Niemier, University of Notre Dame, US, Contact Michael Niemier

Chair:
Michael Niemier, University of Notre Dame, US, Contact Michael Niemier

Co-Chair:
Pierre-Emmanuel Gaillardon, University of Utah, US, Contact Pierre-Emmanuel Gaillardon

With the rapid growth of the internet of things (IoT), demands for battery-less systems are ever increasing. Systems that can be powered by ambient energy sources would offer new opportunities and capabilities for personal entertainment, self-powered, computational systems have obvious societal benefits when deployed for medical monitoring, environmental sensing, etc. This hot topic session considers the current landscape of energy harvesting computing systems and highlights the need for power neutral systems. Subsequent presentations showcase emerging non-volatile memory and logic technologies that could enable battery-less computing systems.

TimeLabelPresentation Title
Authors
17:008.2.1ENERGY-DRIVEN COMPUTING: RETHINKING THE DESIGN OF ENERGY HARVESTING SYSTEMS (Paper/SoftConf ID: 7021)
Speaker:
Geoff Merrett, University of Southampton, GB
Authors:
Geoff Merrett and Bashir Al-Hashimi, University of Southampton, GB
Abstract
Energy harvesting computing has been gaining increasing traction over the past decade, fueled by technological developments and rising demand for autonomous and battery-free systems. Energy harvesting introduces numerous challenges to embedded systems but, arguably the greatest, is the required transition from an energy source that typically provides virtually unlimited power for a reasonable period of time until it becomes exhausted, to a power source that is highly unpredictable and dynamic (both spatially and temporally, and with a range spanning many orders of magnitude). The typical approach to overcome this is the addition of intermediate energy storage/buffering to smooth out the temporal dynamics of both power supply and consumption. This has the advantage that, if correctly sized, the system 'looks like' a battery-powered system; however, it also adds volume, mass, cost and complexity and, if not sized correctly, unreliability. In this paper, we consider energy-driven computing, where systems are designed from the outset to operate from an energy harvesting source. Such systems typically contain little or no additional energy storage (instead relying on tiny parasitic and decoupling capacitance), alleviating the aforementioned issues. Examples of energy-driven computing include transient systems (which power down when the supply disappears and efficiently continue execution when it returns) and power-neutral systems (which operate directly from the instantaneous power harvested, gracefully modulating their consumption and performance to match the supply). In this paper, we introduce a taxonomy of energy-driven computing, articulating how power-neutral, transient, and energy-driven systems present a different class of computing to conventional approaches.

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17:308.2.2NONVOLATILE PROCESSORS: WHY IS IT TRENDING? (Paper/SoftConf ID: 7022)
Speaker:
Vijaykrishnan Narayanan, Penn State University, US
Authors:
Fang Su1, Kaisheng Ma2, Xueqing Li2, Tongda Wu1, Yongpan Liu1 and Vijaykrishnan Narayanan2
1Tsinghua University, CN; 2Penn State University, US
Abstract
Energy harvesting has become a promising solution to power up Internet-of-Things (IoT) devices. In this scenario, the constrained power budget and frequent absence of ambient energy cause severe reliability issues and performance degradation on conventional CMOS computing circuits. Fortunately, the advent of nonvolatile processor (NVP) opens the possibility to compute continuously using an intermittent power supply. It is considered as a key component of the next generation IoT edge devices. In this work, we provide insights to the evolution of the NVP and its application in real world scenarios. Efforts on improving the performance of NVP and future research prospects are also discussed in this paper.

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18:008.2.3ADVANCED SPINTRONIC MEMORY AND LOGIC FOR NON-VOLATILE PROCESSORS (Paper/SoftConf ID: 7023)
Speaker:
X. Sharon Hu, University of Notre Dame, US
Authors:
Robert Perricone1, Ibrahim Ahmed2, Zhaoxin Liang2, Meghna Mankalale3, X. Sharon Hu1, Chris H. Kim2, Michael Niemier1, Sachin Sapatnekar2 and Jian-Ping Wang2
1University of Notre Dame, US; 2University of Minnesota, US; 3University Of Minnesota, US
Abstract
Many ultra-low power Internet of things (IoT) systems may be powered by energy harvested from ambient sources (e.g., solar radiation, thermal gradients, and WiFi). However, these energy sources can vary significantly in terms of their strengths and on/off patterns. For volatile systems, the intermittent nature of the energy sources necessitates the use of backup/recovery schemes to guarantee computational correctness and forward progress, which incur performance, area and energy overhead. Non-volatile (NV) processors based on spintronic devices, such as Spin-Transfer Torque (STT) memory and All-Spin-Logic (ASL), are more attractive alternatives. These NV devices are capable of achieving forward progress without relying on backup/recovery schemes. This work establishes a general framework for evaluating NV device-based processors for energy harvesting applications. Results demonstrate that NV spintronic processors can achieve significant energy savings (up to 83X) versus a hybrid CMOS (computation) and STT-RAM (backup) implementation.

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18:30End of session