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Yi-Chiao Lin

dblp:234/2512 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none

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

Systems, architecture and hardware · 1

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
Energy-efficient computing · 56% Memory systems · 44%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Energy-efficient computing
leakage power reduction
0.412019
OCMAS: Online Page Clustering for Multibank Scratchpad Memory · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2019
Energy-efficient computing › power management
low-power mode management
0.412019
OCMAS: Online Page Clustering for Multibank Scratchpad Memory · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2019
Memory systems › on-chip memory
scratchpad memory
0.412019
OCMAS: Online Page Clustering for Multibank Scratchpad Memory · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2019
Memory systems
on-chip memory
0.112019
OCMAS: Online Page Clustering for Multibank Scratchpad Memory · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2019
Memory systems › memory management
software-managed memory
0.112019
OCMAS: Online Page Clustering for Multibank Scratchpad Memory · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2019

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

threshold adaptation · 0.4online clustering · 0.4
YearPublicationVenuePosition
2019 OCMAS: Online Page Clustering for Multibank Scratchpad Memory
abstract
Scratchpad memory (SPM), a software-controlled on-chip memory, is being increasingly used in embedded systems to reduce on-chip memory energy consumption. To further reduce energy consumption, multibank SPM architecture is proposed. In multibank SPM, each bank can be accessed independently, and unused banks can enter the low power mode, thus reducing leakage energy. However, if both frequently and infrequently used data exist in the same bank, the bank will not be able to enter the low power mode, resulting in less energy reduction. To address this issue, we propose online page clustering for multibank SPM (OCMAS) to reduce the leakage energy in multibank SPM. OCMAS groups SPM pages with similar access frequencies into the same bank, allowing banks containing infrequently used data to stay in low power mode longer. We also propose a method to dynamically adjust the thresholds for determining cold pages (pages that contain infrequently used data), so banks that contain cold pages can enter the low power mode with a shorter idle timeout. Compared to conventional timeout-based, periodic drowsy, and bank-based methods, OCMAS can reduce the energy delay product by up to 37.67% (18.14% on average), 39.53% (22.38% on average), and 132.32% (23.34% on average) in 32 KB 4-bank SPM, by up to 25.33% (15.71% on average), 29.87% (15.92% on average), and 72.25% (22.64% on average) in 32 KB 8-bank SPM, by up to 28.99% (13.45% on average), 30.71% (14.74% on average), and 96.67% (19.94% on average) in 16 KB 4-bank SPM, and by up to 30.18% (10.05% on average), 32.13% (11.62% on average), and 65.56% (16.2% on average) in 16 KB 8-bank SPM. The area overhead is approximately 0.72%, which is insignificant.
Da-Wei Chang, Ing-Chao Lin, Yi-Chiao Lin, Wen-Zhi Huang
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.3