Chris (Shaopeng) Lin

Office: BA5214 University of Toronto

Email: shaopenglin@cs.toronto.edu

I am a Ph.D. student in the Department of Computer Science (DCS) at the University of Toronto (UofT), working with Prof. Gururaj Saileshwar in the Securing Systems via Trustworthy Hardware (SITH) Lab.

I am seeking internship opportunities in Systems & ML Security, HPC, or Compilers for Summer 2026. Please feel free to reach out if you’re interested.

My research interests span hardware, memory, and machine learning (ML) security, compiler optimizations, and ML systems and accelerators. Currently, I focus on Rowhammer attacks and defenses, as well as securing ML systems against emerging threat vectors. My earlier work demonstrated the feasibility of Rowhammer attacks on NVIDIA GPUs, which can be exploited to degrade deep learning models. I have also contributed to enhancing Per-Row Activation Counting (PRAC), a state-of-the-art Rowhammer defense. More recently, I’ve been exploring compiler and hardware techniques to attack or protect large language model (LLM) training and inference pipelines, as well as parallel computing systems.

As a software engineer, I have a strong interest in low-level and hardware-centric programming, with over two years of experience in C/C++ and Python. I also have experience in compiler engineering and Qt-based GUI development. I previously interned at Huawei Canada and participated in Google Summer of Code (GSOC) through open-source contributions. In my spare time, I enjoy working on Android apps, graphics computing, and game development.

Before starting my Ph.D. at the University of Toronto, I earned a B.S. in Computer Science from the University of Toronto Scarborough in 2024. I have also served as a Teaching Assistant at UTSC for over three years.

During my down time, I am a competent Badminton 🏸 Player :). I actively play the Monster Hunter Series 🐉⚔️, Hollow Knight (Silk Song Hype) 💀, Balatro 🃏, and Arknights 🛥️. I am also happily married ❤️💍❤️ with Linghe (Flora) Zhao.

News

Nov 07, 2025	GPUHammer won the 🏅North America Best Paper Award at CSAW 2025!
Aug 13, 2025	GPUHammer, our work on demonstrating Rowhammer on NVIDIA GPUs has been accepted at USENIX Security 2025!
Jun 21, 2025	Presented my “first” first authored work, CnC-PRAC, at DRAMSec 2025!
Mar 04, 2025	QPRAC won the 🏅Distinguished Artifact Award at HPCA 2025!
Mar 01, 2025	QPRAC, my first collaborated paper has been accepted at HPCA 2025!
Sep 01, 2024	Graduated from UTSC and joining UofT for Ph.D. in CS!
Apr 25, 2024	Awarded the 2024 University of Toronto Excellence Award (UTEA)!

Selected Publications

USENIX Security
GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Chris S. Lin, Joyce Qu, and Gururaj Saileshwar

In Proceedings of the 34th USENIX Conference on Security Symposium, Seattle, WA, USA, 2025

CSAW’25 (North America) Best Paper Award 🏅

Abs arXiv Bib Code Website

Rowhammer is a read disturbance vulnerability in modern DRAM that causes bit-flips, compromising security and reliability. While extensively studied on Intel and AMD CPUs with DDR and LPDDR memories, its impact on GPUs using GDDR memories, critical for emerging machine learning applications, remains unexplored. Rowhammer attacks on GPUs face unique challenges: (1) proprietary mapping of physical memory to GDDR banks and rows, (2) high memory latency and faster refresh rates that hinder effective hammering, and (3) proprietary mitigations in GDDR memories, difficult to reverse-engineer without FPGA-based test platforms.We introduce GPUHammer, the first Rowhammer attack on NVIDIA GPUs with GDDR6 DRAM. GPUHammer proposes novel techniques to reverse-engineer GDDR DRAM row mappings, and employs GPU-specific memory access optimizations to amplify hammering intensity and bypass mitigations. Thus, we demonstrate the first successful Rowhammer attack on a discrete GPU, injecting up to 8 bit-flips across 4 DRAM banks on an NVIDIA A6000 with GDDR6 memory. We also show how an attacker can use these to tamper with ML models, causing significant accuracy drops (up to 80%).
@inproceedings{GPUHammer, author = {Lin, Chris S. and Qu, Joyce and Saileshwar, Gururaj}, booktitle = {Proceedings of the 34th USENIX Conference on Security Symposium}, title = {GPUHammer: Rowhammer Attacks on GPU Memories are Practical}, year = {2025}, isbn = {978-1-939133-52-6}, publisher = {USENIX Association}, address = {USA}, articleno = {294}, numpages = {20}, location = {Seattle, WA, USA}, series = {SEC '25} }

HPCA

QPRAC: Towards Secure and Practical PRAC-based Rowhammer Mitigation using Priority Queues

Jeonghyun Woo, Shaopeng Chris Lin, Prashant J. Nair, Aamer Jaleel, and Gururaj Saileshwar

In 2025 IEEE International Symposium on High Performance Computer Architecture (HPCA), 2025

Distinguished Artifact Award 🏅

DOI arXiv Bib Code

@inproceedings{QRPAC,
  author = {Woo, Jeonghyun and Lin, Shaopeng Chris and Nair, Prashant J. and Jaleel, Aamer and Saileshwar, Gururaj},
  booktitle = {2025 IEEE International Symposium on High Performance Computer Architecture (HPCA)},
  title = {QPRAC: Towards Secure and Practical PRAC-based Rowhammer Mitigation using Priority Queues},
  year = {2025},
  volume = {},
  number = {},
  pages = {1021-1037},
  keywords = {Hands;Protocols;Prevention and mitigation;Random access memory;Computer architecture;Security;Proposals;Guidelines;dram;reliability;security;rowhammer;per row activation counting},
  doi = {10.1109/HPCA61900.2025.00080},
}