[FLASHNET]: Leveraging ML-augmented I/O in Linux

Hi! I’m Justin, an undergraduate at the University of Chicago. As part of the Flashnet project my proposal under the mentorship of Daniar Kurniawan and Haryadi S. Gunawi aims to port the Flashnet model into the Linux kernel.

In this attempt, I will borrow architecture/design choices from LAKE (to take advantage of its integration of ML-focused hardware acceleration in the kernel) and evaluation criteria from LinnOS to test for model inference accuracy. I also plan to support latency “bucket” inference output to improve accuracy. Ultimately, my goal is to gain further insight into best practices for integrating ML models into real-life operating systems like Linux and to inform general design choices for the Flashnet pipeline.

Justin Shin
Justin Shin
Student at University of Chicago

Justin Shin is a contributor to the “Summer of Reproducibility-23” open source program.