.png){kind=icon}
.png){kind=icon}
Return
Energy Efficient Mobile Service Computing With Differential Spintronic-C-Elements: A Logic-in-Memory Asynchronous Computing Paradigm
.png){kind=icon}
PRE
AI
DOI：10.1109/ACCESS.2019.2911098.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
During recent years, researchers throughout academia and industry have been advancing the theory, designing, and applications of mobile service computing through the Internet of Things (IoT). Research interest in mobile service computing stems from its performance, security, reliability, and power consumption. Hence, ultra-low power integrated circuits are essential for mobile service computing that can offer the advantages of low power for computational tasks in the IoT that is driven by the restricting constraints of power consumption and autonomy in both computation and idle phases. To attain the benefits of ultra-low power circuits, the energy-consuming and computational intense demands are imposed by the underlying processing and memory devices on which the conventional ultra-low power integrated circuit can benefit substantially from innovative hardware designs. Logic-in-Memory (LIM) architectures are considered as the potential approaches to attain goals within area and energy constraints starting with the lowest layers of the hardware stack. In this paper, we propose and implement the LIM asynchronous computing paradigm for energy-efficient mobile service computing. The results indicate that the proposed design achieves 38% leakage reduction and 30% accuracy improvement compared to the state-of-the-art non-volatile asynchronous circuits. At the system level, we compare our designs with various commercial microprocessors. The experimental results show that the asynchronous processors attain a four-fold throughput increase relative to their synchronous counterparts under these operating constraints. Therefore, the proposed design offers an approach toward tangible benefits of the battery-constrained embedded mobile service computing.
Keywords:
Mobile service computing
in-memory computing
spintronic C-element
image processing
asynchronous circuit
post-CMOS devices
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.6
Papers:
9.8W
Citations:
29.4W
Organization
View more organizations