I am a PhD student in Electrical Engineering at the University of Kansas. My research focuses on time predictability in embedded real-time systems with an emphasis on the memory interference. I earned my master's degree at the University of Tehran. There, I worked on new approximate hardware designs for low-power digital signal processing.
Projects on GitHub
List of papers on Google Scholar
Farzad Farshchi, Qijing Huang, and Heechul Yun, "Integrating NVIDIA Deep Learning Accelerator (NVDLA) with RISC-V SoC on FireSim", Workshop on Energy Efficient Machine Learning and Cognitive Computing for Embedded Applications (EMC2), 2019.
Jacob Michael Fustos, Farzad Farshchi, and Heechul Yun, "SpectreGuard: An Efficient Data-Centric Defense Mechanism against Spectre Attacks", to appear in Design Automation Conference (DAC), 2019.
Farzad Farshchi, Prathap Kumar Valsan, Renato Mancuso, and Heechul Yun, "Deterministic Memory Abstraction and Supporting Multicore System Architecture", Euromicro Conference on Real-Time Systems (ECRTS), 2018.
Prathap Kumar Valsan, Heechul Yun, and Farzad Farshchi, "Addressing Isolation Challenges of Non-Blocking Caches for Multicore Real-Time Systems", Real-Time Systems Journal, Vol: 53, Issue: 5, pp: 673–708, 2017.
Prathap Kumar Valsan, Heechul Yun, and Farzad Farshchi, "Taming Non-Blocking Caches to Improve Isolation in Multicore Real-Time Systems", IEEE Intl. Conference on Real-Time and Embedded Technology and Applications Symposium (RTAS), 2016. Best paper award.
Farzad Farshchi, Muhammad Saeed Abrishami, and Sied Mehdi Fakhraie, "New Approximate Multiplier for Low-Power Digital Signal Processing", CSI Int. Symp. on Computer Architecture and Digital Systems (CADS), 2013.