S
Sheng-Chih Lin
Researcher at University of California, Santa Barbara
Publications - 17
Citations - 660
Sheng-Chih Lin is an academic researcher from University of California, Santa Barbara. The author has contributed to research in topics: CMOS & Integrated circuit. The author has an hindex of 11, co-authored 17 publications receiving 645 citations. Previous affiliations of Sheng-Chih Lin include Intel.
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Proceedings ArticleDOI
A thermally-aware performance analysis of vertically integrated (3-D) processor-memory hierarchy
Gian Luca Loi,Banit Agrawal,Navin Srivastava,Sheng-Chih Lin,Timothy Sherwood,Kaustav Banerjee +5 more
TL;DR: This work is the first attempt to study the performance benefits of 3D technology under the influence of thermal constraints, and it is shown that the 3D system registers large performance improvement for memory intensive applications.
Journal ArticleDOI
Cool Chips: Opportunities and Implications for Power and Thermal Management
Sheng-Chih Lin,Kaustav Banerjee +1 more
TL;DR: In this article, a comprehensive analysis of chip cooling for various nanometer scale bulk-CMOS and silicon-on-insulator (SOI) technologies is presented, which combines device, circuit and system level considerations.
Proceedings ArticleDOI
A self-consistent junction temperature estimation methodology for nanometer scale ICs with implications for performance and thermal management
TL;DR: The notion of self-consistent solutions of die temperature in estimating the die temperature for sub-100 nm CMOS technologies by taking into account various electrothermal couplings between supply voltage, operating frequency, power dissipation and die temperature is introduced.
Proceedings ArticleDOI
Introspective 3D chips
Shashidhar Mysore,Banit Agrawal,Navin Srivastava,Sheng-Chih Lin,Kaustav Banerjee,Timothy Sherwood +5 more
TL;DR: It is shown that hardware stubs could be inserted into commodity processors at design time that would allow analysis layers to be bonded to development chips, and that these stubs would increase area and power by no more than 0.021mm2 and 0.9% respectively.
Journal ArticleDOI
A Statistical Framework for Estimation of Full-Chip Leakage-Power Distribution Under Parameter Variations
TL;DR: In this paper, the authors present a framework for accurate estimation of key statistical parameters of the subthreshold and gate leakage distributions of a chip under parameter variations while considering both within-die and die-to-die variabilities in process (P), temperature (T), and supply voltage (V).