Vision processing on traditional architectures is inefficient due to energy-expensive off-chip data movement. Many researchers advocate pushing processing close to the sensor to substantially reduce data movement. However, continuous near-sensor processing raises sensor temperature, impairing imaging/vision fidelity. We characterize the thermal implications of using 3D stacked image sensors with near-sensor vision processing units. Our characterization reveals that near-sensor processing reduces system power but degrades image quality. For reasonable image fidelity, the sensor temperature needs to stay below a threshold, situationally determined by application needs. Fortunately, our characterization also identifies opportunities—unique to the needs of near-sensor processing—to regulate temperature based on dynamic visual task requirements and rapidly increase capture quality on demand. Based on our characterization, we propose and investigate two thermal management strategies—stop-capture-go and seasonal migration—for imaging-aware thermal management. For our evaluated tasks, our policies save up to 53% of system power with negligible performance impact and sustained image fidelity.
Energy-efficient visual sensing is extremely important to enable battery powered mobile and IoT applications. While several scheduling techniques have been proposed to save the digital power of sensing, the analog power [1] of capturing an image still remains a daunting barrier for a camera's energy-efficiency. To that end, we characterize the power and performance implications of analog voltage scaling on off-the-shelf image sensors. Our characterization reveals that while reducing the analog voltage supplied to image sensor helps promote sensor power efficiency, it also impairs imaging fidelity, specifically by making images brighter and noisier. Furthermore, we find that brighter and noisier images situationally affect the task accuracy of vision applications. In this poster, we propose an investigation towards a system that adaptively scales analog voltage to optimize sensor energy, while respecting the fidelity needs of visual tasks.
CCS CONCEPTS• Computer systems organization → Reconfigurable computing.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.