Abstract:
Mobile, wearable, and implantable devices integrate an increasing number and variety of sensors, such as microphones, image sensors, and accelerometers. These devices spe...Show MoreMetadata
Abstract:
Mobile, wearable, and implantable devices integrate an increasing number and variety of sensors, such as microphones, image sensors, and accelerometers. These devices spend substantial amounts of time reading the sensors within them, incurring significant data transfer from the sensor to the processor. The high capacitance of sensor-to-processor interconnects, high data rates of modern sensors and frequent usage of applications that use sensors result in significant energy dissipation for sensory data transfer. The contribution of sensing to power consumption is only expected to increase as more and more high-performance sensors are embedded in a single device. To address this challenge, we propose AxSerBus, a quality-configurable approximate serial bus that exploits the locality of sensory data and the error resiliency of sensing applications to reduce energy dissipation. AxSerBus significantly reduces signal transitions by encoding the differences of sensory data in three encoding modes, depending on the magnitude of the differences: very small differences are zeroed out, incurring no energy dissipation; intermediate differences are encoded using special low-transition count patterns; and for high differences, the absolute value (not the difference) of the data is transmitted. Compared with previous schemes, the proposed multi-level encoding results in more data being encoded using low-energy patterns. In addition, in the intermediate difference encoding mode, the differences are encoded in an approximate manner, and the approximation bounds are proportional to the magnitude of the differences. Since small differences are more frequent than large differences in sensory data, the proposed encoding scheme also minimizes quality degradation. We demonstrate that AxSerBus achieves superior energy vs. quality trade-offs compared with previous schemes. We also present a low-overhead heuristic scheme for dynamic quality configuration. In an image processing application, A...
Published in: IEEE Journal on Emerging and Selected Topics in Circuits and Systems ( Volume: 8, Issue: 3, September 2018)