Abhirup Vijay Gunakar
Computer science
Hometown: Tempe, Arizona, United States
Graduation date: Spring 2025
FURI | Spring 2025
Detecting Data Races Using Enhanced Memory Protection Keys
Data races in multi-threaded programs can lead to unpredictable behavior, security vulnerabilities, and system failures. Existing dynamic race detection tools impose high overhead, making them impractical for large-scale applications. This research enhances the KARD race detection framework by integrating Extended Protection Keys (EPK), expanding protection domains from 16 to 7,680 to improve detection accuracy and scalability. Benchmark evaluations using PARSEC and SPLASH-2x will assess execution time and memory efficiency. The findings will contribute to cloud computing, aerospace, and financial systems, offering a scalable solution for secure, high-performance concurrent computing. Future research will focus on optimizing kernel-level synchronization mechanisms and OS-level concurrency models to further mitigate race conditions in modern multi-threaded architectures.
Mentor: Adil Ahmad
It’s hip to be square.
Students presenting projects at the Fulton Forge Student Research Expo are encouraged to download this personal QR code and include it within your poster. This allows expo attendees to explore more about your project and about you in the future.
Right click the image to save it to your computer.