From the 1 of 27 linked papers with an AI index.
27 papers
Demystifying DRAM Read Disturbance: Bridging the Gap Between Experimental Characterization and Device-Level Modeling of RowHammer and RowPress Phenomena
Haocong Luo, Longda Zhou, Ataberk Olgun +5
The paper links experimental observations of DRAM read‑disturbance errors (RowHammer and RowPress) with detailed device‑level models using TCAD simulations, identifying gaps and up…
ColumnKeeper: Efficient Solutions to the ColumnDisturb Vulnerability in DRAM-based Systems
Andreas Kosmas Kakolyris, F. Nisa Bostanci, Ataberk Olgun +7
Modern DRAM chips are vulnerable to read disturbance phenomena such as RowHammer and RowPress, which induce bitflips after accessing nearby rows a certain number of times (the read…
Clutch: High Performance Vector-Scalar Comparison using DRAM via Chunked Temporal Coding
Daichi Tokuda, Tatsuya Kubo, Ismail Emir Yuksel +8
Vector-scalar comparison is a fundamental computation primitive that compares each element in a vector against a single scalar value. It is widely used in various data-intensive wo…
DejaVu: Why You Should Write to Your DRAM Rows Twice, Carefully
Haocong Luo, İsmail Emir Yüksel, Ataberk Olgun +4
We provide the first experimental demonstration of DejaVu, a phenomenon where the data previously written to DRAM cells affects DRAM's vulnerability to read disturbance. Our experi…
Ramulator 2.1: A Composable Memory System Simulator for Modern DRAM Systems
Haocong Luo, F. Nisa Bostancı, Ataberk Olgun +4
Ramulator 2.1 is a major overhaul of Ramulator 2.0 that substantially improves the simulator in three directions: 1) support of modern and emerging DRAM and memory-controller featu…
Memory-Centric Computing: Security Benefits and Challenges of Processing-in-DRAM
Ismail Emir Yuksel, F. Nisa Bostanci, Ataberk Olgun +1
Today's computing systems are processor-centric: they require frequent data movement between processing elements (e.g., CPU) and main memory (DRAM), leading to significant ineffici…