Stagioni: Temperature management to enable near-sensor processing for performance, fidelity, and energy-efficiency of vision and imaging workloads
|Abstract||Vision processing on traditional architectures is inefficient due to energy-expensive off-chip data movements. Many researchers advocate pushing processing close to the sensor to substantially reduce data movements. However, continuous near-sensor processing raises the sensor temperature, impairing the fidelity of imaging/vision tasks.
The work characterizes the thermal implications of using 3D stacked image sensors with near-sensor vision processing units. The 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, the characterization also identifi... (more)
|Contributor||Kodukula, Venkatesh (Author) / LiKamWa, Robert (Advisor) / Chakrabarti, Chaitali (Committee member) / Brunhaver, John (Committee member) / Arizona State University (Publisher)|
|Subject||Computer engineering / Computer science / Electrical engineering / continuous mobile vision / near-sensor processing / runtime / thermal noise|
|Note||Masters Thesis Computer Engineering 2019|
|Collaborating Institutions||Graduate College / ASU Library|
|Additional Formats||MODS / OAI Dublin Core / RIS|