activity
20202026
most citedMitigating Edge Machine Learning Inference Bottlenecks: An Empirical Study on Accelerating Google Edge Models

20 citations · 75 across the 29 of their papers we have counts for

collaborators

39 papers

cs.AR2026

FLINT: Efficiently Leveraging High Bandwidth Flash for Capacity-Scalable LLM Inference Acceleration

Geraldo F. Oliveira, Arash Tavakkol, Xiangyu Zhu +10

LLM inference is increasingly constrained by accelerator memory capacity rather than compute throughput. This constraint is especially acute in single-accelerator and small-node in…

cs.AR2025

In-DRAM True Random Number Generation Using Simultaneous Multiple-Row Activation: An Experimental Study of Real DRAM Chips

Ismail Emir Yuksel, Ataberk Olgun, F. Nisa Bostanci +5

In this work, we experimentally demonstrate that it is possible to generate true random numbers at high throughput and low latency in commercial off-the-shelf (COTS) DRAM chips by…

cs.AR2025

New Tools, Programming Models, and System Support for Processing-in-Memory Architectures

Geraldo F. Oliveira

Our goal in this dissertation is to provide tools, programming models, and system support for PIM architectures (with a focus on DRAM-based solutions), to ease the adoption of PIM…

cs.AR2025

PIMDAL: Mitigating the Memory Bottleneck in Data Analytics using a Real Processing-in-Memory System

Manos Frouzakis, Juan Gómez-Luna, Geraldo F. Oliveira +2

Database Management Systems (DBMSs) are crucial for efficient data management and analytics, and are used in several different application domains. Due to the increasing volume of…

cs.AR2025

Variable Read Disturbance: An Experimental Analysis of Temporal Variation in DRAM Read Disturbance

Ataberk Olgun, F. Nisa Bostanci, Ismail Emir Yuksel +6

Modern DRAM chips are subject to read disturbance errors. State-of-the-art read disturbance mitigations rely on accurate and exhaustive characterization of the read disturbance thr…

cs.CR2025

Chronus: Understanding and Securing the Cutting-Edge Industry Solutions to DRAM Read Disturbance

Oğuzhan Canpolat, A. Giray Yağlıkçı, Geraldo F. Oliveira +6

We 1) present the first rigorous security, performance, energy, and cost analyses of the state-of-the-art on-DRAM-die read disturbance mitigation method, Per Row Activation Countin…