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Seungyong Lee 0005

dblp:339/0103 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0000-0002-7348-5454ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Memory systems · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Memory systems
memory disaggregation
0.812024
Computational CXL-Memory Solution for Accelerating Memory-Intensive Applications · HPCA 2024
Memory systems › processing-in-memory
near-data processing
0.812024
Computational CXL-Memory Solution for Accelerating Memory-Intensive Applications · HPCA 2024
Memory systems
processing-in-memory
0.812024
Computational CXL-Memory Solution for Accelerating Memory-Intensive Applications · HPCA 2024
Memory systems › memory management
memory sharing
0.212024
Computational CXL-Memory Solution for Accelerating Memory-Intensive Applications · HPCA 2024

Methods — techniques the papers use, named apart from their topics

prototype demonstration · 0.8
YearPublicationVenuePosition
2024 Computational CXL-Memory Solution for Accelerating Memory-Intensive Applications
abstract
CXL interface is the up-to-date technology that enables effective memory expansion by providing a memory-sharing protocol in configuring heterogeneous devices. However, its limited physical bandwidth can be a significant bottleneck for emerging data-intensive applications. In this work, we propose a novel CXL-based memory disaggregation architecture with a real-world prototype demonstration, which overcomes the bandwidth limitation of the CXL interface using near-data processing. The experimental results demonstrate that our design achieves up to 1.9× better performance/power efficiency than the existing CPU system.
Joonseop Sim, Soohong Ahn, Taeyoung Ahn, Seungyong Lee 0005, Myunghyun Rhee, Kwangsik Shin, Donguk Moon, Euiseok Kim, Kyoung Park
HPCA4