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DTSTART:19700308T020000
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DTSTAMP:20211208T164413Z
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DTSTART;TZID=America/Los_Angeles:20211209T133000
DTEND;TZID=America/Los_Angeles:20211209T135000
UID:dac_DAC 2021_sess102_RESEARCH393@linklings.com
SUMMARY:gGuard: Enabling Leakage-Resilient Memory Isolation in GPU-acceler
 ated Autonomous Embedded Systems
DESCRIPTION:Research Manuscript\n\ngGuard: Enabling Leakage-Resilient Memo
 ry Isolation in GPU-accelerated Autonomous Embedded Systems\n\nYadlapalli\
 n\nGraphics processing units (GPUs)  are being widely used as co-processor
 s for performance acceleration in many autonomous embedded systems such as
  robotics and  autonomous vehicles. However, current GPU hardware and syst
 ems software, including GPU device drivers, compilers, and operating syste
 ms, do not implement proper memory protection mechanisms due to performanc
 e and proprietary reasons, causing severe  vulnerabilities such as informa
 tion leakage. In this paper, we present gGuard, a leakage-resilient GPU me
 mory management system with strong isolation.\n\nTopic: Autonomous Systems
 \n\nVirtual Program: Presented In-Person
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