Session 3B: Mobile Applications ASPLOS’18, March 24–28, 2018, Williamsburg, VA, USA Potluck: Cross-Application Approximate Deduplication for Computation-Intensive Mobile Applications Peizhen Guo Wenjun Hu Yale University Yale University
[email protected] [email protected] Abstract 1 Introduction Emerging mobile applications, such as cognitive assistance Many emerging mobile applications increasingly interact and augmented reality (AR) based gaming, are increasingly with the environment, process large amounts of sensory in- computation-intensive and latency-sensitive, while running put, and assist the mobile user with a range of tasks. For on resource-constrained devices. The standard approaches example, a personal assistance application can “see” the to addressing these involve either ooading to a cloud(let) environment and generate alerts or audio information for or local system optimizations to speed up the computation, visually-impaired users [8]. A driving assistance applica- often trading o computation quality for low latency. tion [44] can render 3D scenes overlaid on the physical en- Instead, we observe that these applications often operate vironment to help the driver to visualize the surroundings on similar input data from the camera feed and share com- beyond the immediate views. These applications are usually mon processing components, both within the same (type of) computation-intensive and latency-sensitive, while running applications and across dierent ones. Therefore, dedupli- on resource-constrained devices. cating processing across applications could deliver the best The standard approaches to resolving these challenges of both worlds. involve either ooading to a cloud(let) [18, 21, 40, 43] or local In this paper, we present Potluck, to achieve approximate system optimizations to speed up the computation [15, 32], deduplication.