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BEGIN:VEVENT
DTSTAMP:20220715T000512Z
LOCATION:Level 2 Lobby
DTSTART;TZID=America/Los_Angeles:20220713T180000
DTEND;TZID=America/Los_Angeles:20220713T190000
UID:dac_DAC 2022_sess263_WIP203@linklings.com
SUMMARY:A Domain-Specific System-On-Chip Design for Energy Efficient Weara
 ble Edge AI Applications
DESCRIPTION:Networking Reception, Work-in-Progress Poster\n\nA Domain-Spec
 ific System-On-Chip Design for Energy Efficient Wearable Edge AI Applicati
 ons\n\nTuncel, Krishnakumar, Chithra, Kim, Ogras\n\nWearable applications 
 collect a significant amount of streaming sensor data. Transmitting the ra
 w data to the cloud wastes the narrow energy budget. Edge AI platforms mus
 t balance two competing requirements: (1) Maximizing the energy efficiency
  using targeted hardware accelerators; and (2) providing developers versat
 ility using general purpose cores for arbitrary applications. Towards this
  goal, we present an open-source domain-specific programmable system-on-ch
 ip that combines a RISC-V core with a meticulously determined set of accel
 erators targeting wearable applications. Thorough experimental evaluations
  on an FPGA prototype show 3.6--7.3x higher energy-efficiency and faster e
 xecution time than SW implementations of six applications with real-life u
 se-cases.
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