13 citations · 57 across the 75 of their papers we have counts for
16 papers · 2 filters
DCC: Data-Centric Compilation of Machine Learning Kernels for Processing-In-Memory Architectures
Peiming Yang, Sankeerth Durvasula, Ivan Fernandez +4
High-performance Host processors can integrate Processing-In-Memory (PIM) devices, which can accelerate memory-intensive kernels of Machine Learning (ML) models, including Large La…
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…
ColumnDisturb: Understanding Column-based Read Disturbance in Real DRAM Chips and Implications for Future Systems
İsmail Emir Yüksel, Ataberk Olgun, F. Nisa Bostancı +3
We experimentally demonstrate a new widespread read disturbance phenomenon, ColumnDisturb, in real commodity DRAM chips. By repeatedly opening or keeping a DRAM row (aggressor row)…
Cleaning up the Mess: Re-Evaluating the Real-System Modeling Accuracy of Ramulator 2.0
F. Nisa Bostanci, Haocong Luo, Ataberk Olgun +4
A MICRO 2024 best paper runner-up publication (the Mess paper) with all three artifact badges awarded (including ``Reproducible'') proposes a new benchmark to evaluate real and sim…
MARS: Processing-In-Memory Acceleration of Raw Signal Genome Analysis Inside the Storage Subsystem
Melina Soysal, Konstantina Koliogeorgi, Can Firtina +8
Raw signal genome analysis (RSGA) has emerged as a promising approach to enable real-time genome analysis by directly analyzing raw electrical signals. However, rapid advancements…
EasyDRAM: An FPGA-based Infrastructure for Fast and Accurate End-to-End Evaluation of Emerging DRAM Techniques
Oğuzhan Canpolat, Ataberk Olgun, David Novo +2
DRAM is a critical component of modern computing systems. Recent works propose numerous techniques (that we call DRAM techniques) to enhance DRAM-based computing systems' throughpu…
PuDHammer: Experimental Analysis of Read Disturbance Effects of Processing-using-DRAM in Real DRAM Chips
Ismail Emir Yuksel, Akash Sood, Ataberk Olgun +6
Processing-using-DRAM (PuD) is a promising paradigm for alleviating the data movement bottleneck using DRAM's massive internal parallelism and bandwidth to execute very wide operat…
Accelerating Triangle Counting with Real Processing-in-Memory Systems
Lorenzo Asquini, Manos Frouzakis, Juan Gómez-Luna +3
Triangle Counting (TC) is a procedure that involves enumerating the number of triangles within a graph. It has important applications in numerous fields, such as social or biologic…
Memory-Centric Computing: Solving Computing's Memory Problem
Onur Mutlu, Ataberk Olgun, Ismail Emir Yuksel
Computing has a huge memory problem. The memory system, consisting of multiple technologies at different levels, is responsible for most of the energy consumption, performance bott…
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…
SAGe: A Lightweight Algorithm-Architecture Co-Design for Mitigating the Data Preparation Bottleneck in Large-Scale Genome Sequence Analysis
Nika Mansouri Ghiasi, Talu Güloglu, Harun Mustafa +8
Genome sequence analysis, which examines the DNA sequences of organisms, drives advances in many critical medical and biotechnological fields. Given its importance and the exponent…
Harmonia: Enhancing Data Placement and Migration in Hybrid Storage Systems via Multi-Agent Reinforcement Learning
Rakesh Nadig, Vamanan Arulchelvan, Rahul Bera +7
Modern high-performance computing (HPC) environments rely on hybrid storage systems (HSS) that combine multiple storage devices with diverse latency, bandwidth, endurance, and capa…
PAPI: Exploiting Dynamic Parallelism in Large Language Model Decoding with a Processing-In-Memory-Enabled Computing System
Yintao He, Haiyu Mao, Christina Giannoula +6
Large language models (LLMs) are widely used for natural language understanding and text generation. An LLM model relies on a time-consuming step called LLM decoding to generate ou…
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…
Understanding RowHammer Under Reduced Refresh Latency: Experimental Analysis of Real DRAM Chips and Implications on Future Solutions
Yahya Can Tuğrul, A. Giray Yağlıkçı, İsmail Emir Yüksel +6
RowHammer is a major read disturbance mechanism in DRAM where repeatedly accessing (hammering) a row of DRAM cells (DRAM row) induces bitflips in physically nearby DRAM rows (victi…
Proteus: Enabling High-Performance Processing-Using-DRAM with Dynamic Bit-Precision, Adaptive Data Representation, and Flexible Arithmetic
Geraldo F. Oliveira, Mayank Kabra, Yuxin Guo +8
Processing-using-DRAM (PUD) is a paradigm where the analog operational properties of DRAM are used to perform bulk logic operations. While PUD promises high throughput at low energ…